Report of Directors Financial Review Risk Report

12 Months Ended

Dec. 31, 2024

Report of Directors Financial Review Risk Report [Abstract]

Disclosure of audited information included in report of the directors risk report

Credit Risk sub-function

(Audited)

Credit approval authorities are delegated by the Board to the Group

CEO together with the authority to sub-delegate them. The Credit

Risk sub-function in Group Risk and Compliance is responsible for the

key policies and processes for managing credit risk, which include

formulating Group credit policies and risk rating frameworks, guiding

the Group’s appetite for credit risk exposures, undertaking

independent reviews and objective assessment of credit risk, and

monitoring performance and management of portfolios.

The principal objectives of our credit risk management are:

–to maintain across HSBC a strong culture of responsible lending,

and robust risk policies and control frameworks;

–to both partner and challenge our businesses in defining,

implementing and continually re-evaluating our risk appetite under

actual and scenario conditions; and

–to ensure there is independent, expert scrutiny of credit risks, their

costs and their mitigation.

Concentration of exposure

(Audited)

Concentrations of credit risk arise when a number of counterparties or

exposures have comparable economic characteristics, or such

counterparties are engaged in similar activities or operate in the same

geographical areas or industry sectors so that their collective ability to

meet contractual obligations is similarly affected by changes in

economic, political or other conditions. We use a number of controls

and measures to minimise undue concentration of exposure in our

portfolios across industries, countries and global businesses. These

include portfolio and counterparty limits, approval and review controls,

and stress testing.

Credit quality of financial instruments

(Audited)

Our risk rating system facilitates the internal ratings-based approach

under the Basel framework adopted by the Group to support the

calculation of our minimum credit regulatory capital requirement. The

five credit quality classifications encompass a range of granular

internal credit rating grades assigned to wholesale and retail

customers, and the external ratings attributed by external agencies to

debt securities.

For debt securities and certain other financial instruments, external

ratings have been aligned to the five quality classifications based upon

the mapping of related customer risk rating (‘CRR’) to external credit

rating.

Forborne loans and advances

(Audited)

Forbearance measures consist of concessions towards an obligor that

is experiencing or about to experience difficulties in meeting its

financial commitments.

We continue to class loans as forborne when we modify the

contractual payment terms due to having concerns about the

borrowers’ ability to meet contractual payments when they were due.

Our definition of forborne captures non-payment-related concessions,

such as covenant waivers.

For details of our policy on forbearance, see Note 1.2(i) in the financial

statementsForborne loans and recognition of expected

credit losses

(Audited)

Forborne loans expected credit loss assessments reflect the higher

rates of losses typically experienced with these types of loans such

that they are in stage 2 and stage 3. The higher rates are more

pronounced in unsecured retail lending requiring further

segmentation. For wholesale lending, forborne loans are typically

assessed individually. Credit risk ratings are intrinsic to the

impairment assessments. The individual impairment assessment

takes into account the higher risk of the future non-payment inherent

in forborne loans.

Impairment assessment

(Audited)

For details of our impairment policies on loans and advances and

financial investments, see Note 1.2(i) on the financial statements.

Write-off of loans and advances

(Audited)

Under IFRS 9, write-off should occur when there is no reasonable

expectation of recovering further cash flows from the financial asset.

This principle does not prohibit early write-off, which is defined in

local policies to ensure effectiveness in the management of

customers in the collections process.

Unsecured personal facilities, including credit cards, are generally

written off at between 150 and 210 days past due. The standard

period runs until the end of the month in which the account becomes

180 days contractually delinquent. However, in exceptional

circumstances, to avoid unfair customer outcomes, deliver customer

duty or meet regulatory expectations, the period may be extended

further.

For secured facilities, write-off should occur upon repossession of

collateral, receipt of proceeds via settlement, or determination that

recovery of the collateral will not be pursued. Where these assets are

maintained on the balance sheet beyond 60 months of consecutive

delinquency-driven default, the prospect of recovery is reassessed.

Recovery activity, on both secured and unsecured assets, may

continue after write-off.

Any unsecured exposures that are not written off at 180 days past

due, and any secured exposures that are in ‘default’ status for 60

months or greater but are not written off, are subject to additional

monitoring via the appropriate governance forums.

Summary of financial instruments to which the impairment requirements in IFRS 9 are applied
(Audited)
	31 Dec 2024		At 31 Dec 2023
	Gross carrying/ nominal amount	Allowance for ECL1	Gross carrying/ nominal amount	Allowance for ECL1
	$m	$m	$m	$m
Loans and advances to customers at amortised cost	940,373	(9,715)	949,609	(11,074)
Loans and advances to banks at amortised cost	102,052	(13)	112,917	(15)
Other financial assets measured at amortised cost	828,580	(92)	960,271	(422)
–  cash and balances at central banks	267,674	—	285,868	—
–  Hong Kong Government certificates of indebtedness	42,293	—	42,024	—
–  reverse repurchase agreements – non-trading	252,549	—	252,217	—
–  financial investments	153,982	(9)	148,346	(20)
–  assets held for sale2	3,273	(4)	103,186	(324)
–  prepayments, accrued income and other assets3	108,809	(79)	128,630	(78)
Total gross carrying amount on-balance sheet	1,871,005	(9,820)	2,022,797	(11,511)
Loans and other credit-related commitments	619,367	(348)	661,015	(367)
Financial guarantees	16,998	(29)	17,009	(39)
Total nominal amount off-balance sheet4	636,365	(377)	678,024	(406)
	2,507,370	(10,197)	2,700,821	(11,917)
	Fair value	Memorandum allowance for ECL5	Fair value	Memorandum allowance for ECL5
	$m	$m	$m	$m
Debt instruments measured at fair value through other comprehensive income (‘FVOCI’)	346,124	(54)	302,348	(97)

1The total ECL is recognised in the loss allowance for the financial asset unless the total ECL exceeds the gross carrying amount of the financial asset, in which

case the ECL is recognised as a provision.

2For further details on gross carrying amounts and allowances for ECL related to assets held for sale, see ‘Assets held for sale’ on page 176. At 31 December

2024, the gross carrying amount comprised $1,113m of loans and advances to customers and banks (2023: $84,075m) and $2,160m of other financial assets at

amortised cost (2023: $19,111m). The corresponding allowance for ECL comprised $4m of loans and advances to customers and banks (2023: $303m) and

$0.3m of other financial assets at amortised cost (2023: $21m).

3Includes only those financial instruments that are subject to the impairment requirements of IFRS 9. ‘Prepayments, accrued income and other assets’ as

presented within the consolidated balance sheet on page 365 comprises both financial and non-financial assets, including cash collateral and settlement

accounts. It also includes ‘Items in the course of collection from other banks’ which was presented separately in 2023.

4Represents the maximum amount at risk should the contracts be fully drawn upon and clients default.

5Debt instruments measured at FVOCI continue to be measured at fair value with the allowance for ECL as a memorandum item. Change in ECL is recognised in

‘Change in expected credit losses and other credit impairment charges’ in the income statement.

Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 December 2024
(Audited)
	Gross carrying/nominal amount1					Allowance for ECL					ECL coverage %
	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%	%
Loans and advances to customers at amortised cost	824,420	93,248	22,615	90	940,373	(1,078)	(2,546)	(6,040)	(51)	(9,715)	0.1	2.7	26.7	56.7	1.0
–  personal	403,746	39,919	3,560	—	447,225	(570)	(1,158)	(796)	—	(2,524)	0.1	2.9	22.4	—	0.6
–  corporate and commercial	340,987	51,231	18,376	90	410,684	(463)	(1,358)	(4,883)	(51)	(6,755)	0.1	2.7	26.6	56.7	1.6
–  non-bank financial institutions	79,687	2,098	679	—	82,464	(45)	(30)	(361)	—	(436)	0.1	1.4	53.2	—	0.5
Loans and advances to banks at amortised cost	101,852	198	2	—	102,052	(9)	(2)	(2)	—	(13)	—	1.0	100.0	—	—
Other financial assets measured at amortised cost	826,621	1,806	153	—	828,580	(64)	(5)	(23)	—	(92)	—	0.3	15.0	—	—
Loan and other credit-related commitments	597,231	21,175	958	3	619,367	(137)	(121)	(90)	—	(348)	—	0.6	9.4	—	0.1
–  personal	251,489	1,680	86	—	253,255	(17)	—	(5)	—	(22)	—	—	5.8	—	—
–  corporate and commercial	231,201	17,453	838	3	249,495	(111)	(116)	(83)	—	(310)	—	0.7	9.9	—	0.1
–  financial	114,541	2,042	34	—	116,617	(9)	(5)	(2)	—	(16)	—	0.2	5.9	—	—
Financial guarantees	15,353	1,397	248	—	16,998	(8)	(5)	(16)	—	(29)	0.1	0.4	6.5	—	0.2
–  personal	1,416	11	—	—	1,427	—	—	—	—	—	—	—	—	—	—
–  corporate and commercial	10,048	1,232	195	—	11,475	(7)	(5)	(15)	—	(27)	0.1	0.4	7.7	—	0.2
–  financial	3,889	154	53	—	4,096	(1)	—	(1)	—	(2)	—	—	1.9	—	—
At 31 Dec 2024	2,365,477	117,824	23,976	93	2,507,370	(1,296)	(2,679)	(6,171)	(51)	(10,197)	0.1	2.3	25.7	54.8	0.4

1Represents the maximum amount at risk should the contracts be fully drawn upon and clients default.

2Purchased or originated credit-impaired (‘POCI’).

Stage 2 days past due analysis at 31 December 2024
(Audited)
	Gross carrying amount				Allowance for ECL				ECL coverage %
	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1
	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%
Loans and advances to customers at amortised cost	93,248	90,157	1,888	1,203	(2,546)	(2,147)	(192)	(207)	2.7	2.4	10.2	17.2
–  personal	39,919	37,676	1,361	882	(1,158)	(799)	(169)	(190)	2.9	2.1	12.4	21.5
–  corporate and commercial	51,231	50,486	506	239	(1,358)	(1,326)	(21)	(11)	2.7	2.6	4.2	4.6
–  non-bank financial institutions	2,098	1,995	21	82	(30)	(22)	(2)	(6)	1.4	1.1	9.5	7.3
Loans and advances to banks at amortised cost	198	198	—	—	(2)	(2)	—	—	1.0	1.0	—	—
Other financial assets measured at amortised cost	1,806	1,794	3	9	(5)	(5)	—	—	0.3	0.3	—	—

1The days past due amounts presented above are on a contractual basis.

Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 December 2023
(Audited)
	Gross carrying/nominal amount1					Allowance for ECL					ECL coverage %
	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%	%
Loans and advances to customers at amortised cost	809,384	120,871	19,273	81	949,609	(1,130)	(2,964)	(6,950)	(30)	(11,074)	0.1	2.5	36.1	37.0	1.2
–  personal	396,534	47,483	3,505	—	447,522	(579)	(1,434)	(854)	—	(2,867)	0.1	3.0	24.4	—	0.6
–corporate and commercial	342,878	69,738	14,958	81	427,655	(499)	(1,500)	(5,774)	(30)	(7,803)	0.1	2.2	38.6	37.0	1.8
–  non-bank financial institutions	69,972	3,650	810	—	74,432	(52)	(30)	(322)	—	(404)	0.1	0.8	39.8	—	0.5
Loans and advances to banks at amortised cost	111,479	1,436	2	—	112,917	(10)	(3)	(2)	—	(15)	—	0.2	100.0	—	—
Other financial assets measured at amortised cost	946,873	12,734	664	—	960,271	(109)	(132)	(181)	—	(422)	—	1.0	27.3	—	—
Loan and other credit- related commitments	630,949	28,922	1,140	4	661,015	(153)	(128)	(86)	—	(367)	—	0.4	7.5	—	0.1
–  personal	253,183	3,459	355	—	256,997	(23)	—	(2)	—	(25)	—	—	0.6	—	—
–  corporate and commercial	246,210	20,928	736	4	267,878	(120)	(119)	(83)	—	(322)	—	0.6	11.3	—	0.1
–  financial	131,556	4,535	49	—	136,140	(10)	(9)	(1)	—	(20)	—	0.2	2.0	—	—
Financial guarantees	14,746	1,879	384	—	17,009	(7)	(7)	(25)	—	(39)	—	0.4	6.5	—	0.2
–  personal	1,106	13	—	—	1,119	—	—	—	—	—	—	—	—	—	—
–  corporate and commercial	10,157	1,290	330	—	11,777	(6)	(6)	(24)	—	(36)	0.1	0.5	7.3	—	0.3
–  financial	3,483	576	54	—	4,113	(1)	(1)	(1)	—	(3)	—	0.2	1.9	—	0.1
At 31 Dec 2023	2,513,431	165,842	21,463	85	2,700,821	(1,409)	(3,234)	(7,244)	(30)	(11,917)	0.1	2.0	33.8	35.3	0.4

1Represents the maximum amount at risk should the contracts be fully drawn upon and clients default.

2Purchased or originated credit-impaired (‘POCI’).

Stage 2 days past due analysis at 31 December 2023
(Audited)
	Gross carrying amount				Allowance for ECL				ECL coverage %
	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1
	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%
Loans and advances to customers at amortised cost	120,871	116,320	2,571	1,980	(2,964)	(2,458)	(245)	(261)	2.5	2.1	9.5	13.2
–  personal	47,483	44,634	1,785	1,064	(1,434)	(974)	(214)	(246)	3.0	2.2	12.0	23.1
–  corporate and commercial	69,738	68,446	697	595	(1,500)	(1,454)	(31)	(15)	2.2	2.1	4.4	2.5
–  non-bank financial institutions	3,650	3,240	89	321	(30)	(30)	—	—	0.8	0.9	—	—
Loans and advances to banks at amortised cost	1,436	1,424	—	12	(3)	(3)	—	—	0.2	0.2	—	—
Other financial assets measured at amortised cost	12,734	12,417	171	146	(132)	(113)	(9)	(10)	1.0	0.9	5.3	6.8

1The days past due amounts presented above are on a contractual basis.

Assets held for sale

(Audited)

At 31 December 2024, the most material balances held for sale arose

from our business in South Africa and our private banking business in

Germany.

Disclosures relating to assets held for sale are provided in the

following credit risk tables, primarily where the disclosure is relevant

to the measurement of these financial assets:

–‘Maximum exposure to credit risk’ (page 178); and

–‘Distribution of financial instruments by credit quality at

31 December’ (page 196);

Although there was a reclassification on the balance sheet, there was

no separate income statement reclassification. As a result, charges

for changes in expected credit losses and other credit impairment

charges shown in the credit risk disclosures include charges relating

to financial assets classified as ‘assets held for sale’.

‘Loans and other credit-related commitments’, ‘financial guarantees’

and ‘Debt instruments measured at fair value through other

comprehensive income’ as reported in credit disclosures, also include

exposures and allowances relating to financial assets classified as

‘assets held for sale’.

Loans and advances to customers and banks measured at amortised cost
(Audited)
	2024		2023
	Total gross loans and advances	Allowance for ECL	Total gross loans and advances	Allowance for ECL
	$m	$m	$m	$m
As reported	1,042,425	(9,728)	1,062,526	(11,089)
Reported in ‘Assets held for sale’	1,113	(4)	84,075	(303)
At 31 December	1,043,538	(9,732)	1,146,601	(11,392)

At 31 December 2024, gross loans and advances of our business in

South Africa were $660m and the related allowance for ECL was

$4m. Gross loans and advances of our private banking business in

Germany were $309m and of our French life insurance business were

$144m, both with negligible allowance for ECL.

Lending balances held for sale continue to be measured at amortised

cost less allowances for impairment and, therefore, such carrying

amounts may differ from fair value.

These lending balances are part of associated disposal groups that are

measured in their entirety at the lower of carrying amount and fair

value less costs to sell. Any difference between the carrying amount

of these assets and their sales price is part of the overall gain or loss

on the associated disposal group as a whole.

For further details of the carrying amount and the fair value at 31 December

2024 of loans and advances to banks and customers classified as held for

sale, see Note 23 on the financial statements.

Gross loans and allowance for ECL on loans and advances to customers and banks reported in ‘Assets held for sale’
(Audited)
	South Africa		German Private Banking Business		Other		Total
	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	660	(4)	309	—	—	—	969	(4)
–  personal	—	—	130	—	—	—	130	—
–  corporate and commercial	586	(4)	19	—	—	—	605	(4)
–  non-bank financial institutions	74	—	160	—	—	—	234	—
Loans and advances to banks at amortised cost	—	—	—	—	144	—	144	—
At 31 Dec 20241	660	(4)	309	—	144	—	1,113	(4)
	Banking business in Canada		Retail banking operations in France		Other		Total
	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL	Gross carrying amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	56,349	(220)	16,984	(82)	255	(1)	73,588	(303)
–  personal	27,071	(95)	13,920	(79)	140	(1)	41,131	(175)
–  corporate and commercial	27,789	(120)	3,012	(3)	—	—	30,801	(123)
–  non-bank financial institutions	1,489	(5)	52	—	115	—	1,656	(5)
Loans and advances to banks at amortised cost	154	—	10,333	—	—	—	10,487	—
At 31 Dec 2023	56,503	(220)	27,317	(82)	255	(1)	84,075	(303)

1The table above does not include disposals completed during 2024 including the sale of our retail banking operations in France completed on 1 January 2024 and

our banking business in Canada completed on 28 March 2024. The sale of our business in Argentina was announced in the first quarter of 2024 and completed

on 6 December 2024. The gross loans and advances to customers and banks in Argentina were $1,760m and the associated allowance for ECL was $34m at

31 March 2024. For more details, please refer to business disposals as disclosed in Note 23 on page 433.

The table below analyses the amount of ECL (charges)/releases arising from assets held for sale. The charges during the period relate to our

businesses in Canada ($41m) and in Argentina ($40m).

Changes in expected credit losses and other credit impairment
(Audited)
	2024	2023
	$m	$m
ECL (charges)/releases arising from:
–  assets held for sale	(81)	(49)
–  assets not held for sale	(3,333)	(3,398)
Year ended 31 Dec	(3,414)	(3,447)

Credit exposure

Maximum exposure to credit risk

(Audited)

This section provides information on balance sheet items and their offsets as well as loan and other credit-related commitments. Commentary

on consolidated balance sheet movements in 2024 is provided on page 93.

Maximum exposure to credit risk
(Audited)
	2024			2023
	Maximum exposure	Offset	Net	Maximum exposure	Offset	Net
	$m	$m	$m	$m	$m	$m
Loans and advances to customers held at amortised cost	930,658	(22,822)	907,836	938,535	(22,607)	915,928
–  personal	444,701	(2,256)	442,445	444,655	(2,470)	442,185
–  corporate and commercial	403,929	(18,897)	385,032	419,852	(18,771)	401,081
–  non-bank financial institutions	82,028	(1,669)	80,359	74,028	(1,366)	72,662
Loans and advances to banks at amortised cost	102,039	—	102,039	112,902	—	112,902
Other financial assets held at amortised cost	854,427	(4,383)	850,044	973,316	(13,919)	959,397
–  cash and balances at central banks	267,674	—	267,674	285,868	—	285,868
–  Hong Kong Government certificates of indebtedness	42,293	—	42,293	42,024	—	42,024
–  reverse repurchase agreements – non-trading	252,549	(4,383)	248,166	252,217	(13,919)	238,298
–  financial investments	153,973	—	153,973	148,326	—	148,326
–  assets held for sale	27,234	—	27,234	114,134	—	114,134
–  prepayments, accrued income and other assets	110,704	—	110,704	130,747	—	130,747
Derivatives	268,637	(254,257)	14,380	229,714	(222,059)	7,655
Total on-balance sheet exposure to credit risk	2,155,761	(281,462)	1,874,299	2,254,467	(258,585)	1,995,882
Total off-balance sheet	970,610	—	970,610	1,007,885	—	1,007,885
–  financial and other guarantees	109,380	—	109,380	111,102	—	111,102
–  loan and other credit-related commitments	861,230	—	861,230	896,783	—	896,783
At 31 Dec	3,126,371	(281,462)	2,844,909	3,262,352	(258,585)	3,003,767

Credit deterioration of financial

instruments

(Audited)

A summary of our current policies and practices regarding the identification,

treatment and measurement of stage 1, stage 2, stage 3 (credit impaired)

and POCI financial instruments can be found in Note 1.2 on the financial

statements.

Measurement uncertainty and sensitivity analysis of ECL estimates(Audited)

The recognition and measurement of ECL involves the use of

judgement and estimation. We form multiple economic scenarios,

apply these forecasts to credit risk models to estimate future credit

losses, and probability weight the results to determine an unbiased

ECL estimate.

Management assessed the current economic environment, reviewed

the latest forecasts and discussed key risks before selecting the

appropriate economic scenarios and their weightings. 

The Central scenario is constructed to reflect the latest

macroeconomic expectations. Outer scenarios incorporate the

crystallisation of economic and geopolitical risks.

In the fourth quarter of 2024, the four economic scenarios were

modified to reflect heightened policy uncertainty following the US

election and to overcome any lags in consensus forecasts. An

adjustment factor based on more recent views of expected tariffs and

other policy changes was modelled and then applied to each of the

economic scenarios. The effect was to lower growth expectations in

our major markets, while the impact on inflation and interest rates

was varied.

Management judgemental adjustments are used where modelled

ECL does not fully reflect the identified risks and related uncertainty,

or to capture significant late-breaking events.

At 31 December 2024, there was an overall reduction in management

judgemental adjustments compared with 31 December 2023, as

modelled outcomes better reflected the key risks at 31 December 2024.

Methodology

At 31 December 2024, four scenarios were used to capture the latest

economic expectations and to articulate management’s view of the

range of risks and potential outcomes. Each scenario is updated with

the latest economic forecasts and distributional estimates every

quarter.

Three scenarios, the Upside, Central and Downside, are drawn from 

consensus forecasts, market data and distributional estimates of the

entire range of economic outcomes. The fourth scenario, the

Downside 2, represents management’s view of severe downside

risks. Consensus estimates are deployed as conditioning variables in a

proprietary expansion of the scenario variables. 

The Central scenario is deemed the ‘most likely’ scenario, and usually

attracts the largest probability weighting. It is created using consensus

forecasts, which is the average of a panel of external forecasts.

The outer scenarios represent the tails of the distribution and are less

likely to occur. The consensus Upside and Downside scenarios are

created with reference to forecast probability distributions for select

markets that capture economists’ views of the entire range of

economic outcomes. In the later years of these scenarios, projections

revert to long-term consensus trend expectations. Reversion to trend

expectations is done with reference to historically observed quarterly

changes in the values of macroeconomic variables.

The fourth scenario, the Downside 2, represents management’s view of

severe downside risks. It is a globally consistent, narrative-driven

scenario that explores a more extreme economic outcome than those

captured by the consensus scenarios. In this scenario, variables do not,

by design, revert to long-term trend expectations and may instead

explore alternative states of equilibrium, where economic variables move

permanently away from past trends.

The consensus Downside and the consensus Upside scenarios are each

constructed to be consistent with a 10% probability. The Downside 2 is

calibrated to a 5% probability. The Central scenario is assigned the

remaining 75%. This weighting scheme is deemed appropriate for the

unbiased estimation of ECL in most circumstances. However,

management may depart from this probability-based scenario weighting

approach when the economic outlook and forecasts are determined to

be particularly uncertain and risks are elevated.

For the fourth quarter of 2024, we assessed that consensus forecasts

and distributional estimates did not adequately reflect the

consequences of the US election on the global economic outlook.

Due to the lag in forecasts there was increased uncertainty as to how

tariffs would be implemented and economic policy would change. As

such, scenarios have been constructed using the described standard

methodology and an adjustment – to account for policy changes –

applied. The adjustment was based on a modelled update to the

Central scenario and incorporated a detailed narrative of US economic

policy proposals, including specific tariff rates. The modelled results

were then layered onto the Central scenario, which resulted in

changes to most variables. To quantify the impact, the adjustment

reduces GDP growth in our key markets by an average of 30bps and

50bps respectively, in the first two years of the Central scenario

forecast. Outer scenarios were adjusted in parallel.

The scenario adjustment entailed no change in scenario probability

weights, which remained in line with our Forward Economic Guidance

(’FEG’) framework. Uncertainties relating to the policy outlook have been

addressed in the scenarios directly. Measures of dispersion and

uncertainty have remained low but may reflect lags in the consensus

economic forecasting process.

Scenarios produced to calculate ECL are aligned to HSBC’s top and

emerging risks.

Description of economic scenarios

The economic assumptions presented in this section have been

formed by HSBC with reference to external forecasts and estimates,

specifically for the purpose of calculating ECL.

Forecasts may change and remain subject to uncertainty. Outer

scenarios are designed to capture the potential crystallisation of key

economic and financial risks and alternative paths for economic

variables.

In our key markets, the Central scenario incorporates potential

impacts from anticipated changes to US economic and trade policy,

including higher tariffs. The overall effect of the adjustment in our key

markets is to lower GDP and raise inflation and unemployment

estimates, relative to the consensus. Consequently, GDP growth and

unemployment forecasts have deteriorated in the fourth quarter of

2024, compared with the fourth quarter of 2023. With regards to

monetary policy, the expected path for interest rates in many of our

markets is based on market futures. Interest rate expectations have

increased relative to the fourth quarter of 2023, with fewer rate cuts

forecast. The exception is mainland China, where the headwinds to

growth ensure that forecast interest rates are lower.

At the end of 2024, risks to the economic outlook included a number

of significant geopolitical issues. Within our Downside scenarios, the

economic consequences from the crystallisation of those risks were

captured by higher commodity and goods prices, the re-acceleration

of inflation, a further rise in interest rates and a global recession.

The scenarios used to calculate ECL are described below.

The consensus Central scenario

HSBC’s Central scenario reflects expectations for slower growth and

higher inflation and unemployment across many of our key markets.

Expectations of lower GDP growth during 2025 are driven by the

assumed effects of higher tariffs, which impede trade flows, weaken

consumption and deter investment. In the scenario, the US applies tariffs

on key trading partners, focusing on mainland China and Mexico at the

outset of the new administration’s term, before moving attention to

other trading partners. Countries are expected to respond in kind. As a

direct consequence of tariffs, trade growth is expected to be lower,

which in turn weighs on GDP growth.

Mainland China, Hong Kong and Mexico experience the greatest

negative consequences given their deeper trade and financial

interlinkages, with the US economy. Indirect consequences from tariffs

dampen growth elsewhere. Tariffs, or the threat of them, increases

uncertainty, leading to lower confidence and reduced investment.

Tighter restrictions on immigration into the US are also expected to

reduce the size of the labour force, putting upward pressure on wage

growth. At the same time, higher tariff rates drive US inflation. Higher

inflation is assumed to erode purchasing power and reduces GDP

growth. In other markets, including in Mexico, higher inflation is also

expected due to currency depreciation. The higher projected rates of

inflation ensure that central banks are expected to slow the pace of

interest rate reductions. The exception is in mainland China, where

the PBoC cuts interest rates as the excess of domestic supply is

expected to become more acute and drives prices lower.

Global GDP is expected to grow by 2.5% in 2025 in the Central

scenario, and the average rate of global GDP growth is forecast to be

2.6% over the five-year forecast period. This is below the average

growth rate over the five-year period prior to the onset of the pandemic

of 2.9%.

The key features of our Central scenario are:

–GDP growth rates across the majority of our main markets are

expected to slow in 2025 and 2026, due to the implementation of

higher tariffs as well as underlying structural weaknesses in some

economies. The most significant slowdowns in activity are expected

to occur in the markets with the highest trade dependence with the

US.  Elevated interest rates and higher price levels are also expected

to continue to weigh on some consumer and corporate segments.

–In most markets, unemployment is forecast to rise moderately in

2025 as economic activity slows, although it will remain low by

historical standards. 

–Inflation is forecast to increase in several of our main markets, as a

result of tariffs, even as services price inflation is expected to ease as

wage growth moderates. However, inflation largely remains within

central banks’ target ranges from 2025. The main exceptions are

Hong Kong and mainland China, where inflation is expected to remain

subdued, despite higher tariffs, due to weak domestic demand.

–Housing market conditions remain mixed, with price weakness

expected to persist in Hong Kong and mainland China, stronger

growth in the UAE and Mexico, and more muted price growth in the

UK, US and France. High inventory levels remain the biggest drag on

Hong Kong and mainland China residential property and this is

expected to lead to another year of price declines in 2025, before a

gradual recovery from 2026.

–Challenging conditions are also forecast to continue in certain

segments of the commercial property sector in a number of our key

markets. Structural changes to demand in the office segment in

particular have driven lower valuations.

–Policy interest rates in key markets are forecast to gradually decline

further in 2025. In the longer term, they are expected to remain at a

higher level than in recent years.

–The Brent crude oil price is forecast to average around $69 per barrel

over the projection period.

The Central scenario was created with forecasts available in late November, and reviewed continually until the end of December 2024. In accordance

with HSBC’s scenario framework, a probability weight of 75% has been assigned to the Central scenario across all major markets.

The following tables describe key macroeconomic variables in the consensus Central scenario.

Consensus Central scenario 2025–2029 (as at 4Q24)
	UK	US	Hong Kong	Mainland China	France	UAE	Mexico
GDP (annual average growth rate, %)
2025	1.2	2.0	1.7	4.0	0.9	4.4	0.9
2026	1.3	1.6	1.8	3.7	0.9	4.2	1.2
2027	1.8	1.6	3.5	4.3	1.4	3.9	1.7
2028	1.6	1.8	3.1	3.9	1.5	3.6	1.9
2029	1.6	2.0	2.7	3.7	1.4	3.6	2.0
5-year average1	1.5	1.8	2.6	3.9	1.2	3.9	1.5
Unemployment rate (%)
2025	4.9	4.4	3.3	5.2	7.5	2.7	3.5
2026	4.7	4.3	3.7	5.4	7.3	2.6	3.5
2027	4.5	4.3	3.3	5.2	7.2	2.6	3.5
2028	4.3	4.2	3.0	5.0	7.0	2.5	3.5
2029	4.3	4.1	2.9	5.0	7.0	2.5	3.5
5-year average1	4.5	4.2	3.2	5.2	7.2	2.6	3.5
House prices (annual average growth rate, %)
2025	1.4	4.4	(0.5)	(5.9)	2.1	9.3	7.6
2026	3.8	3.2	2.4	(0.7)	4.4	5.1	4.5
2027	4.6	2.4	3.0	3.2	4.4	3.6	4.2
2028	3.5	2.5	2.7	4.1	3.8	1.8	4.0
2029	2.7	2.6	2.7	2.9	3.1	1.3	4.0
5-year average1	3.2	3.0	2.1	0.7	3.6	4.2	4.9
Inflation (annual average growth rate, %)
2025	2.4	2.4	1.4	0.3	1.2	2.1	5.0
2026	2.1	2.8	1.9	1.0	1.6	1.9	3.9
2027	2.1	2.5	2.2	1.5	2.0	1.8	3.4
2028	2.0	2.2	2.2	1.7	2.3	1.9	3.4
2029	2.0	2.1	2.3	1.6	2.2	1.8	3.4
5-year average	2.1	2.4	2.0	1.2	1.9	1.9	3.8
Central bank policy rate (annual average, %)
2025	4.2	4.1	4.5	2.9	2.1	4.1	9.4
2026	3.9	3.7	4.1	2.9	1.8	3.8	8.8
2027	3.8	3.7	4.0	3.0	2.0	3.7	8.8
2028	3.7	3.6	4.0	3.2	2.0	3.6	8.9
2029	3.7	3.6	4.0	3.3	2.1	3.6	8.9
5-year average1	3.9	3.7	4.1	3.1	2.0	3.8	8.9

1The five-year average is calculated over a projected period of 20 quarters from 1Q25 to 4Q29.

2For mainland China, the rate shown is the Loan Prime Rate.

Consensus Central scenario 2024–2028 (as at 4Q23)
	UK	US	Hong Kong	Mainland China	France	UAE	Mexico
GDP (annual average growth rate, %)
2024	0.3	1.0	2.6	4.5	0.8	3.7	1.9
2025	1.2	1.8	2.7	4.4	1.5	4.0	2.2
2026	1.7	2.1	2.6	4.3	1.6	3.8	2.3
2027	1.6	2.0	2.6	3.8	1.5	3.4	2.4
2028	1.6	2.0	2.6	3.9	1.5	3.4	2.4
5-year average1	1.3	1.8	2.6	4.2	1.4	3.6	2.2
Unemployment rate (%)
2024	4.7	4.3	3.0	5.2	7.5	2.6	2.9
2025	4.6	4.2	3.0	5.1	7.3	2.6	2.9
2026	4.3	4.0	3.2	5.1	7.0	2.6	2.9
2027	4.2	4.0	3.2	5.1	6.8	2.6	2.9
2028	4.2	4.0	3.2	5.1	6.8	2.6	2.9
5-year average1	4.4	4.1	3.1	5.1	7.1	2.6	2.9
House prices (annual average growth rate, %)
2024	(5.5)	2.9	(6.6)	(0.6)	(1.0)	12.6	6.5
2025	0.1	2.7	(0.7)	1.1	2.4	7.7	4.2
2026	3.5	3.1	2.6	2.6	4.0	4.4	4.2
2027	3.0	2.7	2.8	4.0	4.4	2.6	4.0
2028	3.0	2.1	3.0	4.5	4.0	2.3	4.0
5-year average1	0.8	2.7	0.2	2.3	2.8	5.9	4.6
Inflation (annual average growth  rate,%)
2024	3.2	2.7	2.1	1.8	2.7	2.3	4.2
2025	2.2	2.2	2.1	2.0	1.8	2.2	3.6
2026	2.2	2.3	2.2	2.1	1.7	2.1	3.5
2027	2.3	2.2	2.4	2.0	1.9	2.1	3.5
2028	2.3	2.2	2.4	2.0	2.1	2.1	3.5
5-year average1	2.4	2.3	2.2	2.0	2.0	2.1	3.7
Central bank policy rate (annual average, %)
2024	5.0	5.0	5.4	3.2	3.6	5.1	10.4
2025	4.3	4.0	4.4	3.3	2.8	4.1	8.6
2026	3.9	3.7	4.1	3.5	2.6	3.7	7.9
2027	3.8	3.7	4.1	3.7	2.6	3.7	7.9
2028	3.7	3.8	4.1	3.9	2.7	3.8	8.1
5-year average1	4.1	4.1	4.4	3.5	2.9	4.1	8.6

1The five-year average is calculated over a projected period of 20 quarters from 1Q24 to 4Q28.

2For mainland China, the rate shown is the Loan Prime Rate. In prior periods, including the 4Q23 disclosure, the reference rate shown for mainland China was the

Lending Rate.

The graphs compare the Central scenario at the year end 2023 with economic expectations at the end of 2024.

GDP growth: Comparison of Central scenarios

Hong Kong

Note: Real GDP shown as year-on-year percentage change.

Mainland China

Note: Real GDP shown as year-on-year percentage change.

UK

Note: Real GDP shown as year-on-year percentage change.

US

Note: Real GDP shown as year-on-year percentage change.

The consensus Upside scenario

Compared with the Central scenario, the consensus Upside scenario

features stronger economic activity in the near term, before

converging to long-run trend expectations. It also incorporates a faster

fall in the rate of inflation than in the Central scenario.

The scenario is consistent with a number of key upside risk themes.

These include only limited increases in tariffs and a faster fall in the

rate of inflation that allows central banks to reduce interest rates

more quickly. The Upside scenario would also be consistent with a

de-escalation in geopolitical tensions, where the Russia-Ukraine war

moves quickly towards a conclusion, tensions in the Middle East

subside and US-China relations become more cordial.

The following tables describe key macroeconomic variables in the

consensus Upside scenario.

Consensus Upside scenario 2025–2029 (as at 4Q24)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-peak)1	11.3	(4Q29)	13.6	(4Q29)	21.4	(4Q29)	27.5	(4Q29)	8.9	(4Q29)	28.9	(4Q29)	13.6	(4Q29)
Unemployment rate (%, min)2	3.5	(3Q26)	3.6	(1Q26)	2.9	(4Q29)	4.9	(4Q26)	6.4	(4Q26)	2.2	(4Q26)	3.0	(1Q25)
House price index (%, start-to-peak)1	24.2	(4Q29)	23.6	(4Q29)	25.3	(4Q29)	9.8	(4Q29)	22.8	(4Q29)	26.1	(4Q29)	31.7	(4Q29)
Inflation rate (YoY % change, min)3	1.4	(1Q26)	1.6	(2Q26)	(0.1)	(4Q25)	(1.0)	(4Q25)	0.1	(4Q25)	0.6	(4Q25)	3.1	(2Q26)
Central bank policy rate (%, min)2	3.6	(4Q25)	3.6	(1Q29)	4.0	(1Q29)	2.7	(1Q26)	1.4	(3Q25)	3.6	(1Q29)	7.6	(1Q26)

1Cumulative change to the highest level of the series during the 20-quarter projection.

2Lowest projected unemployment or policy interest rate in the scenario. For mainland China, rate shown is the Loan Prime Rate.

3Lowest projected year-on-year percentage change in inflation in the scenario.

Consensus Upside scenario 2024–2028 (as at 4Q23)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-peak)1	10.8	(4Q28)	14.3	(4Q28)	21.8	(4Q28)	30.4	(4Q28)	10.4	(4Q28)	30.7	(4Q28)	17.8	(4Q28)
Unemployment rate (%, min)2	3.1	(4Q24)	3.1	(2Q25)	2.4	(3Q24)	4.8	(4Q25)	6.2	(4Q25)	2.0	(4Q25)	2.4	(3Q24)
House price index (%, start-to-peak)1	13.0	(4Q28)	21.9	(4Q28)	17.9	(4Q28)	19.7	(4Q28)	19.6	(4Q28)	34.2	(4Q28)	30.6	(4Q28)
Inflation rate (YoY % change, min)3	1.3	(2Q25)	1.4	(1Q25)	0.3	(4Q24)	0.6	(3Q24)	1.5	(3Q24)	1.4	(1Q25)	2.7	(1Q25)
Central bank policy rate (%, min)2	3.7	(3Q28)	3.7	(2Q27)	4.1	(1Q27)	3.1	(3Q24)	2.6	(2Q26)	3.7	(1Q27)	7.8	(2Q25)

1Cumulative change to the highest level of the series during the 20-quarter projection.

2Lowest projected unemployment or policy interest rate in the scenario. For mainland China, the rate shown is the Loan Prime Rate. In prior periods, including the

4Q23 disclosure, the reference rate shown for mainland China was the Lending Rate.

3Lowest projected year-on-year percentage change in inflation in the scenario.

Downside scenarios

Downside scenarios explore the intensification and crystallisation of a

number of key economic and financial risks. These include a more

material escalation of tariff policies and geopolitical tensions, which

disrupt key commodity and goods markets, causing inflation and

interest rates to rise, and creating a global recession.

As the geopolitical environment remains volatile and complex, risks

include:

–an increase in protectionist policies, as countries that impose

tariffs are met with retaliatory actions. This lowers investment,

complicates international supply chains, and impedes trade flows;

–broader and more prolonged conflicts in the Middle East and

between Russia and Ukraine, which further disrupt energy and

food supplies; and

–continued differences between the US and China, which could

affect economic confidence, and the global goods trade and supply

chains for critical technologies.

High inflation and higher interest rates also remain key risks. Should

tariffs increase significantly and geopolitical tensions escalate, energy

and food prices could rise and increase pressure on household

budgets and firms’ costs. Higher inflation and labour supply shortages

could also trigger a wage-price spiral and put sustained pressure on

household incomes and corporate margins. In turn, it raises the risk

that central banks react by raising interest rates, leading to higher

defaults and an economic recession.

The consensus Downside scenario

In the consensus Downside scenario, economic activity is weaker

compared with the Central scenario. In this scenario, GDP declines,

unemployment rates rise, and asset prices fall. The scenario features

an increase in tariffs over and above those assumed in the Central

scenario and an escalation of geopolitical tensions, which causes a

rise in inflation, as supply chain constraints intensify and energy prices

rise. The scenario also features a temporary increase in interest rates

above the Central scenario, before the effects of weaker consumption

demand begin to dominate and commodity prices and inflation fall

again.

The following tables describe key macroeconomic variables in the

consensus Downside scenario.

Consensus Downside scenario 2025–2029 (as at 4Q24)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(1.0)	(4Q26)	(0.6)	(3Q25)	(4.5)	(4Q25)	(2.5)	(3Q25)	(0.6)	(1Q26)	0.3	(1Q25)	(2.1)	(4Q26)
Unemployment rate (%, max)2	6.1	(4Q25)	5.3	(3Q25)	5.1	(2Q26)	6.9	(4Q26)	8.3	(3Q25)	3.4	(1Q26)	4.1	(4Q25)
House price index (%, start-to- trough)1	(4.5)	(1Q26)	(0.2)	(1Q25)	(1.9)	(2Q26)	(12.8)	(3Q26)	(0.3)	(1Q25)	(0.4)	(1Q25)	2.1	(1Q25)
Inflation rate (YoY % change, max)3	3.4	(4Q25)	4.5	(1Q26)	3.1	(1Q26)	2.0	(1Q26)	2.6	(3Q25)	2.8	(1Q26)	7.4	(4Q25)
Central bank policy rate (%, max)2	5.0	(1Q25)	4.8	(1Q25)	5.2	(1Q25)	3.0	(1Q25)	3.2	(1Q25)	4.8	(1Q25)	11.5	(3Q25)

1Cumulative change to the lowest level of the series during the 20-quarter projection.

2The highest projected unemployment or policy interest rate in the scenario. For mainland China, the rate shown is the Loan Prime Rate.

3The highest projected year-on-year percentage change in inflation in the scenario.

Consensus Downside scenario 2024–2028 (as at 4Q23)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(1.0)	(2Q25)	(1.4)	(3Q24)	(1.6)	(3Q25)	(1.5)	(1Q24)	(0.3)	(2Q24)	1.4	(1Q24)	(0.3)	(4Q24)
Unemployment rate (%, max)2	6.4	(1Q25)	5.6	(4Q24)	4.7	(4Q25)	6.9	(4Q25)	8.5	(4Q24)	3.7	(4Q25)	3.5	(4Q25)
House price index (%, start-to- trough)1	(12.0)	(2Q25)	(1.3)	(3Q24)	(9.6)	(4Q24)	(7.1)	(3Q25)	(1.2)	(3Q24)	0.3	(1Q24)	1.2	(1Q24)
Inflation rate (YoY % change, max)3	4.1	(1Q24)	3.5	(4Q24)	3.8	(3Q24)	3.5	(4Q24)	3.8	(2Q24)	3.0	(1Q24)	6.5	(4Q24)
Central bank policy rate (%, max)2	5.7	(1Q24)	5.6	(1Q24)	6.0	(1Q24)	3.2	(3Q24)	4.2	(1Q24)	5.7	(1Q24)	12.0	(3Q24)

1Cumulative change to the lowest level of the series during the 20-quarter projection.

2The highest projected unemployment or policy interest rate in the scenario. For mainland China, the rate shown is the Loan Prime Rate. In prior periods, including

the 4Q23 disclosure, the reference rate shown for mainland China was the Lending Rate.

3The highest projected year-on-year percentage change in inflation in the scenario.

Downside 2 scenario

The Downside 2 scenario features a deep global recession and

reflects management’s view of the tail of the economic distribution. It

incorporates the crystallisation of a number of risks simultaneously,

including significant increases in tariffs globally, where the US

imposes particularly high and punitive tariffs on imports from

mainland China and Mexico. A further escalation of geopolitical crises

is also assumed, which creates severe supply disruptions to goods

and energy markets.

In the scenario, as inflation surges and central banks tighten monetary

policy further, consumer and business confidence falls. However, this

impulse is assumed to be short-lived, as recession takes hold, causing

a fall in demand, leading commodity prices to correct sharply and

global price inflation to fall.

The following tables describe key macroeconomic variables in the

Downside 2 scenario.

Downside 2 scenario 2025–2029 (as at 4Q24)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(9.1)	(2Q26)	(4.1)	(2Q26)	(10.1)	(4Q25)	(8.7)	(4Q25)	(7.9)	(2Q26)	(6.8)	(2Q26)	(10.5)	(3Q26)
Unemployment rate (%, max)2	8.4	(2Q26)	9.3	(2Q26)	7.1	(1Q26)	7.1	(4Q26)	10.4	(1Q27)	5.0	(3Q25)	5.6	(1Q26)
House price index (%, start-to- trough)1	(27.2)	(4Q26)	(15.8)	(4Q25)	(34.4)	(3Q27)	(30.5)	(4Q26)	(14.0)	(2Q27)	(13.2)	(2Q27)	2.0	(1Q25)
Inflation rate (YoY % change, max)3	10.1	(2Q25)	4.9	(4Q25)	3.6	(1Q26)	3.8	(4Q25)	7.6	(2Q25)	3.7	(2Q25)	7.9	(4Q25)
Central bank policy rate (%, max)2	5.5	(1Q25)	5.5	(1Q25)	5.9	(1Q25)	3.5	(3Q25)	4.2	(1Q25)	5.6	(1Q25)	12.1	(3Q25)

1Cumulative change to the lowest level of the series during the 20-quarter projection.

2 The highest projected unemployment or policy interest rate in the scenario. For mainland China, the rate shown is the Loan Prime Rate.

3 The highest projected year-on-year percentage change in inflation in the scenario.

Downside 2 scenario 2024–2028 (as at 4Q23)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(8.8)	(2Q25)	(4.6)	(1Q25)	(8.2)	(1Q25)	(6.4)	(1Q25)	(6.6)	(1Q25)	(4.9)	(2Q25)	(8.1)	(2Q25)
Unemployment rate (%, max)2	8.4	(2Q25)	9.3	(2Q25)	6.4	(4Q24)	7.0	(4Q25)	10.2	(4Q25)	4.3	(3Q24)	4.9	(2Q25)
House price index (%, start-to- trough)1	(30.2)	(4Q25)	(14.7)	(4Q24)	(32.8)	(3Q26)	(25.5)	(4Q25)	(14.5)	(2Q26)	(2.9)	(4Q25)	1.2	(1Q24)
Inflation rate (YoY % change, max)3	10.1	(2Q24)	4.8	(2Q24)	4.1	(3Q24)	4.1	(4Q24)	8.6	(2Q24)	3.5	(2Q24)	7.0	(4Q24)
Central bank policy rate (%, max)2	6.0	(1Q24)	6.1	(1Q24)	6.4	(1Q24)	4.1	(3Q24)	5.2	(1Q24)	6.1	(1Q24)	12.7	(3Q24)

1Cumulative change to the lowest level of the series during the 20-quarter projection.

2 The highest projected unemployment or policy interest rate in the scenario. For mainland China, rate shown is the Loan Prime Rate. In prior periods, including the

4Q23 disclosure, the reference rate shown for mainland China was the Lending Rate.

3 The highest projected year-on-year percentage change in inflation in the scenario.

The following graphs show the historical and forecasted GDP growth rate for the various economic scenarios in our four largest markets.

Hong Kong

Mainland China

UK

US

Scenario weighting

Scenario weightings are calibrated to probabilities that are determined

with reference to consensus forecast probability distributions.

Management may then choose to vary weights if they assess that the

calibration lags more recent events, or does not reflect their view of

the distribution of economic and geopolitical risk. Management’s view

of the scenarios and the probability distribution takes into

consideration the relationship of the consensus scenario to both

internal and external assessments of risk.

In assessing the economic environment and the level of risk and

uncertainty, management has considered both global and country-

specific factors.

In the fourth quarter of 2024, key considerations around uncertainty

focused on:

–US import tariffs and bilateral tariff escalations globally, and the

impact on trade and manufacturing supply chains;

–the extent and success of mainland China in deploying fiscal and

monetary support to secure economic growth and underpin a

recovery in the real estate market;

–prospects for recovery in the Hong Kong residential property

market;

–the implications of changes to monetary policy expectations on

growth and employment;

–estimation and forecast uncertainty for UK unemployment given

ongoing methodology updates at the Office for National Statistics;

and

–risks of an asset price correction given elevated valuations across

different asset classes.

Although these factors are significant, management assessed that

following the tariff-based adjustment, the Central scenario reflected

the most likely future economic outcome and that outer scenarios

were sufficiently well calibrated to address the crystallisation of more

severe risks.

This led management to assign scenario probabilities that are aligned

to the standard scenario probability calibration framework in all major

markets. The Central scenario was assigned a 75% probability

weighting in our major markets. The consensus Upside scenario was

assigned a 10% weighting, and the consensus Downside scenario

was given 10%. The Downside 2 was assigned a 5% weighting.

In support of the decision, it was noted that the effect of higher tariffs

would be most negative in mainland China and Hong Kong, as it

would limit trade growth (a significant growth driver in 2024)

substantially and lead to weaker domestic demand. The adjustment to

the Central scenario reflected this assumption.

In the UK, tariffs have a small direct impact on GDP growth forecasts

in the Central scenario, but indirect effects would be larger through

weaker trade and lower global growth. The outlook also remains weak

given the only partially offsetting impacts from measures announced

in the 2024-25 Budget and higher US interest rates.

For the US, the Central scenario reflects expectations that economic

growth will slow in 2025 as households and businesses adjust to

higher inflation, lower labour supply and elevated interest rates.

The impact from tariffs is minimal for the UAE, as trade with the US is

small, but it is assumed to be affected through secondary channels,

including a stronger US dollar and higher interest rates. It was also

observed that geopolitical risks have remained high since the

outbreak of conflict in the Middle East, but economic and market

impacts have been limited and oil production remains unaffected.

Escalation risks were assessed to be consistent with the probabilities

assigned to the Downside scenario.

Management concluded that Mexico is likely to be one of the most

heavily affected countries from US tariff policies and that the impacts

are reflected in the scenarios. GDP growth forecasts in the Central

scenario are lower than in previous periods, and inflation and interest

rates are higher, in part due to an expected deprecation of the

Mexican peso.

In France, recent domestic political uncertainty is the main factor

weighing on reduced growth prospects, and as with other European

markets, there are also assumed to be negative impacts stemming

from higher US tariffs.

Scenario weightings, %
	Standard weights	UK	US	Hong Kong	Mainland China	Canada	France	UAE	Mexico
4Q24
Upside scenario	10	10	10	10	10	10	10	10	10
Central scenario	75	75	75	75	75	75	75	75	75
Downside scenario	10	10	10	10	10	10	10	10	10
Downside 2 scenario	5	5	5	5	5	5	5	5	5
4Q23
Upside scenario	10	10	10	10	10	10	10	10	10
Central scenario	75	75	75	75	75	75	75	75	75
Downside scenario	10	10	10	10	10	10	10	10	10
Downside 2 scenario	5	5	5	5	5	5	5	5	5

At 31 December 2024, the consensus Upside and Central scenarios for all markets had a combined weighting of 85%, unchanged as at

31 December 2023. Weightings assigned to downside scenarios also remained unchanged.

Critical estimates and judgements

The calculation of ECL under IFRS 9 involved significant judgements,

assumptions and estimates at 31 December 2024. These included:

–the selection and configuration of economic scenarios, given the

constant change in economic conditions and distribution of

economic risks; and

–estimating the economic effects of those scenarios on ECL, where

similar observable historical conditions cannot be captured by the

credit risk models.

How economic scenarios are

reflected in ECL calculations

Models are used to reflect economic scenarios in ECL estimates. As

described above, modelled assumptions and linkages based on historical

information could not alone produce relevant information under the

conditions experienced in 2024, and management judgemental

adjustments were still required to support modelled outcomes. 

We have developed globally consistent methodologies for the

application of forward economic guidance into the calculation of ECL

for wholesale and retail credit risk. These standard approaches are

described below, followed by the management judgemental

adjustments made, including those to reflect the circumstances

experienced in 2024.

For our wholesale portfolios, a global methodology is used for the

estimation of the term structure of probability of default (‘PD’) and

loss given default (‘LGD’). For PDs, we consider the correlation of

forward economic guidance to default rates for a particular industry in

a country. For LGD calculations, we consider the correlation of

forward economic guidance to collateral values and realisation rates

for a particular country and industry. PDs and LGDs are estimated for

the entire term structure of each instrument.

For impaired loans, allowance for ECL estimates are derived based on

discounted cash flow (‘DCF’) calculations for internal forward-looking

scenarios specific to individual borrower circumstances (see page

381). Probability-weighted outcomes are applied, and depending on

materiality and status of the borrower, the number of scenarios

considered will change. Where relevant for the case being assessed,

forward economic guidance is incorporated as part of these scenarios.

LGD-driven proxy and modelled estimates are used for certain less

material cases.

For our retail portfolios, the models are predominantly based on

historical observations and correlations with default rates and

collateral values.

For PD, the impact of economic scenarios is modelled for each

portfolio, using historical relationships between default rates and

macroeconomic variables. These are included within IFRS 9 ECL

estimates using either economic response models or models that

contain internal, external and macroeconomic variables. The

macroeconomic impact on PD is modelled over the period equal to

the remaining maturity of the assets.

For LGD, the impact is modelled for mortgage portfolios by

forecasting future loan-to-value profiles for the remaining maturity of

the asset, using national level house price index forecasts and

applying the corresponding LGD expectation relative to the updated

forecast collateral values.

For unsecured retail portfolios historically observed recovery rates are

leveraged to measure loss. For both mortgages and unsecured, a

limited number of portfolios utilise a macroeconomic dependent

stressed LGD applied to the Downside 2 scenario.

Management judgemental

adjustments

In the context of IFRS 9, management judgemental adjustments are

typically short-term increases or decreases to the modelled allowance

for ECL at either a customer, segment or portfolio level where

management believes allowances do not sufficiently reflect the credit

risk/expected credit losses at the reporting date. These can relate to

risks or uncertainties that are not reflected in the models and/or to

any late-breaking events with significant uncertainty, subject to

management review and challenge.

This includes refining model inputs and outputs and using

adjustments to ECL based on management judgement and

quantitative analysis for impacts that are difficult to model.

The effects of management judgemental adjustments are considered for both

balances and allowance for ECL when determining whether or not a significant

increase in credit risk has occurred and is allocated to a stage where

appropriate. This is in accordance with the internal adjustments framework.

Management judgemental adjustments are reviewed under the

governance process for IFRS 9 (as detailed in the section ‘Credit risk

management’ on page 169). Review and challenge focuses on the

rationale and quantum of the adjustments with a further review

carried out by the second line of defence where significant. For some

management judgemental adjustments, internal frameworks establish

the conditions under which these adjustments should no longer be

required and as such are considered as part of the governance

process. This internal governance process allows management

judgemental adjustments to be reviewed regularly and, where

possible, to reduce the reliance on these through model recalibration

or redevelopment, as appropriate.

The drivers of management judgemental adjustments continue to

evolve with the economic environment and as new risks emerge.

In addition to management judgemental adjustments there are also

‘Other adjustments’, which are made to address process limitations

and data/model deficiencies and can also include, where appropriate,

the impact of new models where governance has sufficiently

progressed to allow an accurate estimate of ECL allowance to be

incorporated into the total reported ECL.

‘Management judgemental adjustments’ and ‘Other adjustments’

constitute the total value of adjustments to modelled allowance for

ECL. For the wholesale portfolio, defaulted exposures are assessed

individually and management judgemental adjustments are made only

to the performing portfolio.

At 31 December 2024, there was a $0.6bn reduction in management

judgemental adjustments compared with 31 December 2023. This

was driven by retail due to reductions in economic uncertainty,

primarily in the UK and Asia, and model redevelopments which

captured macro-economic risks more effectively.

Management judgemental adjustments made in estimating the

scenario-weighted reported allowance for ECL at 31 December 2024

are set out in the following table.

Management judgemental adjustments to ECL at 31 December 20241
	Retail	Wholesale2	Total
	$bn	$bn	$bn
Modelled ECL (A)3	2.6	2.0	4.6
Banks, sovereigns, government entities and low-risk counterparties		0.0	0.0
Corporate lending adjustments		0.1	0.1
Inflation related adjustments	0.0		0.0
Other credit judgements	0.0		0.0
Total management judgemental adjustments (B)4	0.0	0.1	0.1
Other adjustments (C)5	(0.0)	0.1	0.1
Final ECL (A + B + C)6	2.6	2.2	4.8

Management judgemental adjustments to ECL at 31 December 20231,7
	Retail	Wholesale2	Total
	$bn	$bn	$bn
Modelled ECL (A)3	2.6	2.4	5.0
Banks, sovereigns, government entities and low-risk counterparties		0.0	0.0
Corporate lending adjustments		0.1	0.1
Inflation-related adjustments	0.1		0.1
Other credit judgements	0.5		0.5
Total management judgemental adjustments (B)4	0.6	0.1	0.7
Other adjustments (C)5	(0.0)	0.0	0.0
Final ECL (A + B + C)6	3.2	2.5	5.7

1Management judgemental adjustments presented in the table reflect increases or (decreases) to allowance for ECL, respectively.

2The wholesale portfolio corresponds to adjustments to the performing portfolio (stage 1 and stage 2).

3(A) refers to probability-weighted allowance for ECL before any adjustments are applied.

4(B) refers to adjustments that are applied where management believes allowance for ECL does not sufficiently reflect the credit risk/expected credit losses of

any given portfolio at the reporting date. These can relate to risks or uncertainties that are not reflected in the model and/or to any late-breaking events.

5(C) refers to adjustments to allowance for ECL made to address process limitations and data/model deficiencies and can also include where appropriate, the

impact of new models where governance has sufficiently progressed to allow an accurate estimate of ECL allowance to be incorporated into the total reported

ECL.

6As presented within our internal credit risk governance (see page 169).

731 December 2023 includes the Canada, Argentina, Armenia and Oman businesses and retail banking operations in France.

Management judgemental adjustments at 31 December 2024 were

an increase to allowance for ECL of $0.1bn for the wholesale portfolio

and $0.0bn for the retail portfolio.

At 31 December 2024, wholesale management judgemental

adjustments were an increase to allowance for ECL of $0.1bn

(31 December 2023: $0.1bn increase). These were mainly to

corporate exposures to reflect heightened uncertainty in specific

sectors and geographies, including offsetting adjustments to the real

estate sector in mainland China, Hong Kong and the US, and

adjustments to exposures to the automotive and industrial sectors in

Germany.

At 31 December 2024, retail management judgemental adjustments

to allowance for ECL were $0.0bn (31 December 2023 $0.6bn). The

reduction in adjustments compared with 31 December 2023 for

inflation-related adjustments was primarily due to the reduction of

inflation related risk in the UK and the sale of the Canadian banking

business. Other credit judgements decreased due to reductions in

economic uncertainty, primarily in the UK and Asia, and model

redevelopments which captured macro-economic risks more

effectively.

Economic scenarios sensitivity

analysis of ECL estimates

Management considered the sensitivity of the ECL outcome against

the economic forecasts as part of the ECL governance process by

recalculating the allowance for ECL under each scenario described

above for selected portfolios, applying a 100% weighting to each

scenario in turn. The weighting is reflected in both the determination

of a significant increase in credit risk and the measurement of the

resulting allowances.

The allowance for ECL calculated for the Upside and Downside

scenarios should not be taken to represent the upper and lower limits

of possible ECL outcomes. The impact of defaults that might occur in

the future under different economic scenarios is captured by

recalculating allowances for loans at the balance sheet date.

There is a particularly high degree of estimation uncertainty in

numbers representing tail risk scenarios when assigned a 100%

weighting.

For wholesale credit risk exposures, the sensitivity analysis excludes

allowance for ECL and financial instruments related to defaulted

(stage 3) obligors. The measurement of stage 3 ECL is relatively more

sensitive to credit factors specific to the obligor than future economic

scenarios, and therefore the effects of macroeconomic factors are not

necessarily the key consideration when performing individual

assessments of allowances for obligors in default. Loans to defaulted

obligors are a small portion of the overall wholesale lending exposure,

even if representing the majority of the allowance for ECL. Due to the

range and specificity of the credit factors to which the ECL is

sensitive, it is not possible to provide a meaningful alternative

sensitivity analysis for a consistent set of risks across all defaulted

obligors.

For retail mortgage exposures the sensitivity analysis includes

allowance for ECL for defaulted obligors of loans and advances. This 

is because the retail ECL for secured mortgage portfolios, including

loans in all stages, is sensitive to macroeconomic variables.

Wholesale and retail sensitivity

The wholesale and retail sensitivity tables present the 100%

weighted results. These exclude portfolios held by the insurance

business and small portfolios, and as such cannot be directly

compared with personal and wholesale lending presented in other

credit risk tables. In both the wholesale and retail analysis, the

comparative period results for Downside 2 scenarios are also not

directly comparable with the current period, because they reflect

different risks relative to the consensus scenarios for the period end.

The wholesale and retail sensitivity analysis is stated inclusive of

management judgemental adjustments, as appropriate to each

scenario.

For both retail and wholesale portfolios, the gross carrying amount of

financial instruments are the same under each scenario. For

exposures with similar risk profile and product characteristics, the

sensitivity impact is therefore largely the result of changes in

macroeconomic assumptions.

Wholesale analysis

IFRS 9 ECL sensitivity to future economic conditions1,2,3
	Reported Gross carrying amount4	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL
By geography at 31 Dec 2024	$m	$m	$m	$m	$m	$m
UK	432,160	717	667	526	850	2,389
US	202,888	216	201	205	247	461
Hong Kong	450,966	659	616	465	906	1,496
Mainland China	137,960	178	141	84	329	886
Mexico	34,713	69	61	46	86	302
UAE	58,909	51	49	40	58	120
France	184,591	82	80	69	97	125
Other geographies5	455,823	234	216	176	304	774
Total	1,958,010	2,205	2,031	1,612	2,877	6,555
of which:
Stage 1	1,830,264	689	632	494	797	803
Stage 2	127,746	1,516	1,399	1,118	2,080	5,751

By geography at 31 Dec 2023
UK	426,427	820	754	599	1,041	2,487
US	191,104	215	199	189	268	441
Hong Kong	447,480	609	566	433	807	1,393
Mainland China	129,945	258	217	142	414	945
Canada5	84,092	89	75	56	107	487
Mexico	30,159	60	56	46	73	226
UAE	52,074	32	32	30	34	40
France	178,827	98	102	90	124	141
Other geographies5,7	450,271	325	298	245	410	882
Total	1,990,378	2,507	2,301	1,829	3,278	7,043
of which:
Stage 1	1,820,843	754	702	553	860	854
Stage 2	169,535	1,753	1,599	1,276	2,418	6,189

1Allowance for ECL sensitivity includes off-balance sheet financial instruments. These are subject to significant measurement uncertainty.

2Includes low credit-risk financial instruments such as debt instruments at FVOCI, which have high carrying amounts but low ECL under all the above scenarios.

3Excludes defaulted obligors. For a detailed breakdown of performing and non-performing wholesale portfolio exposures, see page 200.

4Staging refers only to probability-weighted/reported gross carrying amount. Stage allocation of gross exposures varies by scenario, with higher allocation to stage

2 under the Downside 2 scenario.

5Includes small portfolios that use less complex modelling approaches and are not sensitive to macroeconomic changes.

6Classified as held for sale at 31 December 2023.

7Includes the Argentina and Armenia businesses, which were sold in 2024.

At 31 December 2024, the highest level of 100% scenario-weighted

allowance for ECL was observed in the UK and Hong Kong under the

Downside 2 scenario, driven primarily by a larger exposure to those

geographies, namely in the real estate sector. In relation to the

underlying exposure, mainland China and Mexico have the higher

Downside 2 ECL coverage, mostly due to the relatively larger

proportion of higher risk exposures in those geographies.

Compared with 31 December 2023, the Downside 2 ECL impact

reduced by $0.5bn mostly due to the sale of the Canada business

while observing offsetting impacts driven by updates to our forward

economic scenarios.

In the wholesale portfolio, off-balance sheet financial instruments

have a lower likelihood to be fully converted to a funded exposure at

the point of default, and consequently the sensitivity of the allowance

for ECL is lower in relation to its nominal amount, when compared

with an on-balance sheet exposure with a similar risk profile.

IFRS 9 ECL sensitivity to future economic conditions1
	Reported gross carrying amount	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL
By geography at 31 Dec 2024	$m	$m	$m	$m	$m	$m
UK
Mortgages	163,541	126	117	107	132	288
Credit cards	7,415	280	275	265	276	447
Other	8,249	241	233	217	243	351
Mexico
Mortgages	7,482	165	162	155	168	215
Credit cards	2,227	337	333	330	338	423
Other	3,722	419	416	413	422	593
Hong Kong
Mortgages	106,866	5	5	4	5	10
Credit cards	9,419	293	275	268	300	770
Other	6,210	106	102	101	105	249
UAE
Mortgages	1,993	8	8	8	8	8
Credit cards	536	31	31	31	31	35
Other	688	17	17	17	17	19
US
Mortgages	16,965	6	6	6	6	8
Credit cards	193	15	14	14	15	17
Other geographies
Mortgages	51,064	131	127	124	136	180
Credit cards	3,500	162	159	156	164	223
Other	2,292	72	72	69	73	93
Total	392,361	2,413	2,351	2,285	2,440	3,928
of which: mortgages	347,910	440	425	405	456	708
Stage 1	311,875	51	47	43	58	129
Stage 2	33,761	126	117	107	129	275
Stage 3	2,274	263	261	255	269	304
of which: credit cards	23,290	1,116	1,086	1,064	1,124	1,915
Stage 1	19,915	276	267	258	284	701
Stage 2	3,107	655	634	621	656	1,027
Stage 3	267	185	185	185	185	188
of which: others	21,161	856	839	816	860	1,305
Stage 1	18,574	216	204	193	217	532
Stage 2	2,005	360	355	343	363	483
Stage 3	583	279	279	279	279	290

IFRS 9 ECL sensitivity to future economic conditions1,2
	Reported gross carrying amount	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL
By geography at 31 Dec 2023	$m	$m	$m	$m	$m	$m
UK
Mortgages	161,127	189	180	172	201	334
Credit cards	7,582	344	340	302	353	486
Other	8,183	341	333	273	383	515
Mexico
Mortgages	8,666	188	180	150	235	363
Credit cards	2,445	295	286	206	376	489
Other	4,529	513	503	426	600	731
Hong Kong
Mortgages	106,136	2	2	1	3	5
Credit cards	9,128	287	239	214	395	887
Other	6,269	109	100	88	124	256
UAE
Mortgages	2,001	25	25	25	25	25
Credit cards	471	24	24	22	25	32
Other	721	20	20	19	21	28
France
Mortgages	20,589	50	50	50	51	51
Other	1,328	44	44	43	45	48
US
Mortgages	14,385	8	4	3	4	10
Credit cards	204	15	15	10	15	16
Canada
Mortgages	25,464	67	65	64	70	99
Credit cards	338	13	13	12	16	15
Other	1,368	13	13	12	14	33
Other geographies
Mortgages	55,368	152	149	144	158	198
Credit cards	3,655	173	166	151	202	291
Other	2,416	91	86	83	95	137
Total	442,373	2,962	2,835	2,471	3,411	5,049
of which: mortgages	393,736	681	655	609	747	1,085
Stage 1	347,874	101	92	77	145	303
Stage 2	43,451	264	249	225	280	429
Stage 3	2,412	316	314	307	322	352
of which: credit cards	23,822	1,150	1,082	918	1,381	2,217
Stage 1	18,557	249	232	180	329	604
Stage 2	4,953	707	657	546	859	1,415
Stage 3	312	193	193	192	194	197
of which: others	24,815	1,131	1,098	944	1,283	1,748
Stage 1	19,551	218	205	151	272	501
Stage 2	4,542	540	519	423	636	868
Stage 3	722	373	373	370	375	379

1Allowance for ECL sensitivities exclude portfolios utilising less complex modelling approaches.

2Included balances and allowance for ECL which had been reclassified from ‘loans and advances to customers’ to ‘assets held for sale’ in the balance sheet at

31 December 2023. This also included any balances and allowance for ECL which continued to be reported as personal lending in ‘loans and advances to

customers’ that are in accordance with the basis of inclusion for retail sensitivity analysis. This includes the Canada, Argentina businesses and retail banking

operations in France.

At 31 December 2024, the most significant level of allowance for ECL

sensitivity was observed in the UK, Mexico and Hong Kong. Mortgages

reflected the lowest level of allowance for ECL sensitivity across most

markets given the significant levels of collateral relative to the exposure

values. Credit cards and other unsecured lending across stages 1 and 2

are more sensitive to economic forecasts and therefore reflected the

highest level of allowance for ECL sensitivity during 2024.

There was a reduction in the total sensitivity for ECL allowance in all

scenarios compared with 31 December 2023, due to banking portfolio 

sales, reduction of management judgemental adjustments, model

redevelopments and scenario evolution.

There is limited sensitivity in credit cards and other unsecured lending

in stage 3 as levels of loss on defaulted exposures remain consistent

through various economic conditions. The Downside 2 scenario is

from the tail of the economic distribution where allowance for ECL is

more sensitive based on historical experience and includes a

macroeconomic-dependent stressed LGD for a limited number of

portfolios.

The reported gross carrying amount by stage is representative of the

weighted scenario allowance for ECL. The allowance for ECL

sensitivity to the other scenarios includes changes in allowance for

ECL due to the levels of loss and the migration of additional lending

balances in or out of stage 2.

Group ECL sensitivity results

The allowance for ECL of the scenarios and management judgemental

adjustments is highly sensitive to movements in economic forecasts.

Based upon the sensitivity tables presented above, if the Group allowance

for ECL balance was estimated solely on the basis of the Central scenario,

Downside scenario or the Downside 2 scenario at 31 December 2024, it

would increase/(decrease) as presented in the below table.

Total Group ECL at 31 December 2024
	Retail1	Wholesale1
	$bn	$bn
Reported allowance for ECL	2.4	2.2
Scenarios
100% Consensus Central scenario	(0.1)	(0.2)
100% Consensus Upside scenario	(0.1)	(0.6)
100% Consensus Downside scenario	0.0	0.7
100% Downside 2 scenario	1.5	4.3

Total Group ECL at 31 December 2023
Reported allowance for ECL	3.0	2.5
Scenarios
100% Consensus Central scenario	(0.1)	(0.2)
100% Consensus Upside scenario	(0.5)	(0.7)
100% Consensus Downside scenario	0.4	0.8
100% Downside 2 scenario	2.1	4.5

1On the same basis as retail and wholesale sensitivity analysis.

At 31 December 2024, the Group allowance for ECL decreased in the

retail portfolio by $0.6bn and decreased by $0.3bn in the wholesale

portfolio, compared with 31 December 2023.

There was also a reduction in allowance for ECL sensitivity across all

scenarios within the retail and wholesale portfolios since

31 December 2023, primarily as a result of the sale of our Canada

banking business, the sale of our retail banking operations in France,

and various other business sales during the first half of 2024.

For the wholesale portfolio this was the main driver of the decrease in

Downside 2 ECL sensitivity.

For the retail portfolios the ECL sensitivity decrease across all

scenarios including the Downside 2 was also primarily due to the

reduction of management judgemental adjustments, model

redevelopments and scenario evolution.

Reconciliation from reported exposure and ECL to sensitised exposure and weighted ECL
	Wholesale		Retail		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m
Included in sensitivity analysis	1,958,010	(2,205)	392,361	(2,413)	2,350,371	(4,618)
–  Exclusions from sensitivity as described in the section above1	20,409	(5,419)	309,178	(124)	329,587	(5,543)
–  Debt instruments measured at fair value through other comprehensive income2	(346,124)	54	—	—	(346,124)	54
–  Performance guarantees2	(92,722)	311	—	—	(92,722)	311
–  Other financial assets at amortised cost not presented as wholesale or personal lending, including held for sale2	(568,668)	141	(130)	—	(568,798)	141
–  Other3	5,978	(441)	498	(9)	6,476	(450)
As reported in the Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 Dec 2024	976,883	(7,559)	701,907	(2,546)	1,678,790	(10,105)
Other financial assets at amortised cost					828,580	(92)
Total reported in the Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 Dec 2024					2,507,370	(10,197)

Reconciliation from reported exposure and ECL to sensitised exposure and weighted ECL (continued)
	Wholesale		Retail		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m
Included in sensitivity analysis	1,990,378	(2,507)	442,373	(2,962)	2,432,751	(5,469)
–  Exclusions from sensitivity as described in the section above1	17,024	(6,237)	308,569	(93)	325,593	(6,330)
–  Debt instruments measured at fair value through other comprehensive income2	(302,348)	97	—	—	(302,348)	97
–  Performance guarantees2	(93,312)	35	—	—	(93,312)	35
–  Other financial assets at amortised cost not presented as wholesale or personal lending, including held for sale2	(579,534)	93	(41,129)	174	(620,663)	267
–  Other3	2,704	(84)	(4,175)	(11)	(1,471)	(95)
As reported in the Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 Dec 2023	1,034,912	(8,603)	705,638	(2,892)	1,740,550	(11,495)
Other financial assets at amortised cost					960,271	(422)
Total reported in the Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector at 31 Dec 2023					2,700,821	(11,917)

1Comprises wholesale defaulted obligors, retail portfolios utilising less complex modelling approaches, private banking and insurance.

2The sensitivity analysis includes certain items reported in Other assets at amortised cost, which are not allocated to an industry in the credit tables. It also

includes FVOCI and performance guarantees, which are presented separately in the credit tables.

3Includes FX and other operational variances.

Reconciliations of changes in gross carrying/nominal amount and allowances

for loans and advances to banks and customers including loan commitments

and financial guarantees

The following disclosure provides a reconciliation by stage of the

Group’s gross carrying/nominal amount and allowances for loans and

advances to banks and customers, including loan commitments and

financial guarantees.

In addition, a reconciliation by stage of the Group’s gross carrying

amount and allowances for loans and advances to banks and

customers and a reconciliation by stage of the Group’s nominal

amount and allowances for loan commitments and financial

guarantees, were included in this section following adoption of the

recommendations of the third report from The Taskforce on

Disclosures about Expected Credit Losses (‘DECL’).

Movements are calculated on a quarterly basis and therefore fully

capture stage movements between quarters. If movements were

calculated on a year-to-date basis they would only reflect the opening

and closing position of the financial instrument.

The transfers of financial instruments represents the impact of stage

transfers upon the gross carrying/nominal amount and associated

allowance for ECL.

The net remeasurement of ECL arising from transfer of stage

represents the increase or decrease due to these transfers, for

example, moving from a 12-month (stage 1) to a lifetime (stage 2)

ECL measurement basis. Net remeasurement excludes the

underlying customer risk rating (‘CRR’)/probability of default (‘PD’)

movements of the financial instruments transferring stage. This is

captured, along with other credit quality movements in the ‘changes

to risk parameters – credit quality’ line item.

Changes in ‘Net new and further lending/repayments’ represents the

impact from volume movements within the Group’s lending portfolio

and includes ‘New financial assets originated or purchased’, ‘assets

derecognised (including final repayments)’ and ‘changes to risk

parameters – further lending/repayment’.

Reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	1,496,805	(1,300)	153,084	(3,102)	20,799	(7,063)	85	(30)	1,670,773	(11,495)
Transfers of financial instruments:	(19,629)	(1,259)	6,652	2,302	12,977	(1,043)	—	—	—	—
–transfers from stage 1 to stage 2	(116,211)	419	116,211	(419)	—	—	—	—	—	—
–transfers from stage 2 to stage 1	98,731	(1,627)	(98,731)	1,627	—	—	—	—	—	—
–  transfers to stage 3	(2,799)	16	(12,230)	1,321	15,029	(1,337)	—	—	—	—
–  transfers from stage 3	650	(67)	1,402	(227)	(2,052)	294	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	959	—	(831)	—	(144)	—	—	—	(16)
Changes due to modifications not derecognised	—	—	—	—	(25)	—	—	—	(25)	—
Net new and further lending/repayments	87,833	(168)	(37,731)	589	(5,246)	1,689	7	(7)	44,863	2,103
Changes to risk parameters – credit quality	—	363	—	(1,773)	—	(3,945)	—	(11)	—	(5,366)
Changes to models used for ECL calculation	—	68	—	(4)	—	(20)	—	—	—	44
Assets written off	—	—	—	—	(4,459)	4,459	—	—	(4,459)	4,459
Credit-related modifications that resulted in derecognition	—	—	—	—	—	—	—	—	—	—
Foreign exchange and others1, 2, 3	(75,322)	105	(6,107)	145	(223)	(81)	1	(3)	(81,651)	166
At 31 Dec 2024	1,489,687	(1,232)	115,898	(2,674)	23,823	(6,148)	93	(51)	1,629,501	(10,105)
ECL income statement change for the period		1,222		(2,019)		(2,420)		(18)		(3,235)
Recoveries										260
Others										(158)
Total ECL income statement change for the period										(3,133)

1Total includes $3.7bn of gross carrying loans and advances to customers and banks, which were classified to assets held for sale, and a corresponding allowance

for ECL of $46m, reflecting business disposals as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for sale’ on page 433.

2Total includes $35.3bn of nominal amount and $21m of corresponding allowance for ECL related to derecognition of loan commitments and financial guarantees

following the sale of our banking business in Canada during 2024.

3Total includes $2.7bn of nominal amount related to derecognition of loan commitments and financial guarantees following the sale of our banking business in

Argentina during 2024.

	At 31 Dec 2024		12 months ended 31 Dec 2024
	Gross carrying/ nominal amount	Allowance for ECL	ECL charge
	$m	$m	$m
As above	1,629,501	(10,105)	(3,133)
Other financial assets measured at amortised cost	828,580	(92)	(114)
Non-trading reverse purchase agreement commitments	49,289	—	—
Performance and other guarantees not considered for IFRS 9	—	—	(173)
Summary of financial instruments to which the impairment requirements in IFRS 9 are applied/Summary consolidated income statement	2,507,370	(10,197)	(3,420)
Debt instruments measured at FVOCI	346,124	(54)	6
Total allowance for ECL/total income statement ECL change for the period	n/a	(10,251)	(3,414)

As shown in the previous table, the allowance for ECL for loans and

advances to customers and banks and relevant loan commitments

and financial guarantees decreased $1,390m during the period from

$11,495m at 31 December 2023 to $10,105m at 31 December 2024.

This decrease was driven by:

–$4,459m of assets written off;

–$2,103m relating to volume movements, which included the

allowance for ECL associated with new originations, assets

derecognised and further lending/repayment;

–foreign exchange and other movements of $166m; and

–$44m of changes to models used for ECL calculation.

These were partly offset by:

–$5,366m relating to credit quality changes, including the credit

quality impact of financial instruments transferring between

stages; and

–$16m relating to the net remeasurement impact of stage

transfers.

The ECL charge for the period of $3,235m presented in the previous

table consisted of $5,366m relating to credit quality changes,

including the credit quality impact of financial instruments transferring

between stages and $16m relating to the net remeasurement impact

of stage transfers.

This was partly offset by $2,103m relating to underlying net book

volume movement and $44m in changes to models used for ECL

calculation.

Summary views of the movement in wholesale and personal lending

are presented on pages 203 and 215.

Reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross exposure	Allowance/ provision for ECL	Gross exposure	Allowance/ provision for ECL	Gross exposure	Allowance/ provision for ECL	Gross exposure	Allowance/ provision for ECL	Gross exposure	Allowance/ provision for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2023	1,433,643	(1,257)	177,223	(3,710)	21,207	(6,949)	129	(38)	1,632,202	(11,954)
Transfers of financial instruments:	(18,948)	(1,048)	10,286	2,228	8,662	(1,180)	—	—	—	—
–  transfers from stage 1 to stage 2	(150,728)	442	150,728	(442)	—	—	—	—	—	—
–  transfers from stage 2 to stage 1	133,079	(1,467)	(133,079)	1,467	—	—	—	—	—	—
–  transfers to stage 3	(1,986)	23	(8,600)	1,379	10,586	(1,402)	—	—	—	—
–  transfers from stage 3	687	(46)	1,237	(176)	(1,924)	222	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	917	—	(973)	—	(124)	—	—	—	(180)
Net new and further lending/ repayments	77,693	(185)	(36,795)	661	(4,956)	1,117	(36)	3	35,906	1,596
Changes to risk parameters – credit quality	—	307	—	(1,262)	—	(3,896)	—	21	—	(4,830)
Changes to models used for ECL calculation	—	(22)	—	46	—	7	—	—	—	31
Assets written off	—	—	—	—	(3,922)	3,922	—	—	(3,922)	3,922
Credit-related modifications that resulted in derecognition	—	—	—	—	(119)	95	—	—	(119)	95
Foreign exchange and others1	4,417	(12)	2,370	(92)	(73)	(55)	(8)	(16)	6,706	(175)
At 31 Dec 2023	1,496,805	(1,300)	153,084	(3,102)	20,799	(7,063)	85	(30)	1,670,773	(11,495)
ECL income statement change for the period		1,017		(1,528)		(2,896)		24		(3,383)
Recoveries										268
Others	—	—	—	—	—	—	—	—	—	(195)
Total ECL income statement change for the period										(3,310)

1Total includes $7.7bn of gross carrying loans and advances to customers and banks, which were classified to assets held for sale, and a corresponding allowance

for ECL of $70m, reflecting business disposals as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for sale’ on page 433.

(Audited)
	At 31 Dec 2023		12 months ended 31 Dec 2023
	Gross carrying/ nominal amount	Allowance for ECL	ECL charge
	$m	$m	$m
As above	1,670,773	(11,495)	(3,310)
Other financial assets measured at amortised cost	960,271	(422)	(35)
Non-trading reverse purchase agreement commitments	69,777	—	—
Performance and other guarantees not considered for IFRS 9	—	—	(44)
Summary of financial instruments to which the impairment requirements in IFRS 9 are applied/Summary consolidated income statement	2,700,821	(11,917)	(3,389)
Debt instruments measured at FVOCI	302,348	(97)	(58)
Total allowance for ECL/total income statement ECL change for the period	n/a	(12,014)	(3,447)

Credit quality

Credit quality of financial instruments

(Audited)

We assess the credit quality of all financial instruments that are

subject to credit risk. The credit quality of financial instruments is a

point-in-time assessment of PD, whereas stages 1 and 2 are

determined based on relative deterioration of credit quality since initial

recognition for the majority of portfolios. Accordingly, for non-credit-

impaired financial instruments, there is no direct relationship between

the credit quality assessment and stages 1 and 2, although typically

the lower credit quality bands exhibit a higher proportion in stage 2.

The five credit quality classifications provided below each encompass

a range of granular internal credit rating grades assigned to wholesale

and personal lending businesses and the external ratings attributed by

external agencies to debt securities, as shown in the table on

page 170.

Distribution of financial instruments by credit quality at 31 December 2024
(Audited)
	Gross carrying/notional amount						Allowance for ECL/ other credit provisions	Net
	Strong	Good	Satisfactory	Sub- standard	Credit impaired	Total
	$m	$m	$m	$m	$m	$m	$m	$m
In-scope for IFRS 9 ECL
Loans and advances to customers held at amortised cost	515,266	193,080	186,416	22,906	22,705	940,373	(9,715)	930,658
–  personal	360,317	53,595	27,774	1,979	3,560	447,225	(2,524)	444,701
–  corporate and commercial	114,504	118,785	138,705	20,224	18,466	410,684	(6,755)	403,929
–  non-bank financial institutions	40,445	20,700	19,937	703	679	82,464	(436)	82,028
Loans and advances to banks held at amortised cost	92,621	4,255	5,040	134	2	102,052	(13)	102,039
Cash and balances at central banks	266,713	949	12	—	—	267,674	—	267,674
Hong Kong Government certificates of indebtedness	42,293	—	—	—	—	42,293	—	42,293
Reverse repurchase agreements – non-trading	155,831	70,877	25,799	42	—	252,549	—	252,549
Financial investments	146,970	3,681	3,331	—	—	153,982	(9)	153,973
Assets held for sale	2,425	458	367	1	22	3,273	(4)	3,269
Other assets	88,338	9,735	10,151	454	131	108,809	(79)	108,730
–  endorsements and acceptances	2,101	2,663	3,090	243	10	8,107	(14)	8,093
–  accrued income and other	86,237	7,072	7,061	211	121	100,702	(65)	100,637
Debt instruments measured at fair value through other comprehensive income1	336,313	9,448	7,768	380	—	353,909	(54)	353,855
Out-of-scope for IFRS 9 ECL
Trading assets	119,546	21,951	15,804	2,300	47	159,648	—	159,648
Other financial assets designated and otherwise mandatorily measured at fair value through profit or loss	53,282	11,862	4,390	231	11	69,776	—	69,776
Derivatives	224,870	34,124	9,373	258	12	268,637	—	268,637
Assets held for sale	3,019	—	—	—	—	3,019	—	3,019
Total gross carrying amount on balance sheet	2,047,487	360,420	268,451	26,706	22,930	2,725,994	(9,874)	2,716,120
Percentage of total credit quality (%)	75.1	13.2	9.9	1.0	0.8	100
Loan and other credit-related commitments	400,120	131,396	77,220	9,670	961	619,367	(348)	619,019
Financial guarantees	7,365	4,263	4,399	723	248	16,998	(29)	16,969
In-scope: Irrevocable loan commitments and financial guarantees	407,485	135,659	81,619	10,393	1,209	636,365	(377)	635,988
Loan and other credit-related commitments	96,952	76,340	65,619	2,847	453	242,211	—	242,211
Performance and other guarantees	39,940	32,956	17,339	1,671	817	92,723	(312)	92,411
Out-of-scope: Revocable loan commitments and non-financial guarantees	136,892	109,296	82,958	4,518	1,270	334,934	(312)	334,622

1For the purposes of this disclosure, gross carrying amount is defined as the amortised cost of a financial asset before adjusting for any loss allowance. As such,

the gross carrying amount of debt instruments at FVOCI as presented above will not reconcile to the balance sheet as it excludes fair value gains and losses.

Distribution of financial instruments by credit quality at 31 December 2023
(Audited)
	Gross carrying/notional amount						Allowance for ECL/ other credit provisions	Net
	Strong	Good	Satisfactory	Sub- standard	Credit impaired	Total
	$m	$m	$m	$m	$m	$m	$m	$m
In-scope for IFRS 9 ECL
Loans and advances to customers held at amortised cost	497,665	206,476	197,582	28,532	19,354	949,609	(11,074)	938,535
–  personal	346,562	62,656	32,314	2,485	3,505	447,522	(2,867)	444,655
–  corporate and commercial	118,123	123,713	145,249	25,531	15,039	427,655	(7,803)	419,852
–  non-bank financial institutions	32,980	20,107	20,019	516	810	74,432	(404)	74,028
Loans and advances to banks held at amortised cost	101,057	4,640	6,363	855	2	112,917	(15)	112,902
Cash and balances at central banks	284,723	1,068	77	—	—	285,868	—	285,868
Hong Kong Government certificates of indebtedness	42,024	—	—	—	—	42,024	—	42,024
Reverse repurchase agreements –  non-trading	170,494	46,884	34,206	633	—	252,217	—	252,217
Financial investments	143,333	3,814	1,137	62	—	148,346	(20)	148,326
Assets held for sale	68,501	16,403	14,812	2,939	531	103,186	(324)	102,862
Other assets	106,184	11,982	9,965	366	133	128,630	(78)	128,552
–  endorsements and acceptances	2,405	2,666	2,707	161	18	7,957	(18)	7,939
–  accrued income and other	103,779	9,316	7,258	205	115	120,673	(60)	120,613
Debt instruments measured at fair value through other comprehensive income1	288,959	12,037	7,897	805	5	309,703	(97)	309,606
Out-of-scope for IFRS 9 ECL
Trading assets	122,695	20,595	20,746	1,326	135	165,497	—	165,497
Other financial assets designated and otherwise mandatorily measured at fair value through profit or loss	52,649	11,517	4,733	84	6	68,989	—	68,989
Derivatives	196,098	27,377	6,041	187	11	229,714	—	229,714
Assets held for sale	12,495	—	—	—	—	12,495	—	12,495
Total gross carrying amount on balance sheet	2,086,877	362,793	303,559	35,789	20,177	2,809,195	(11,608)	2,797,587
Percentage of total credit quality (%)	74.3	12.9	10.8	1.3	0.7	100
Loan and other credit-related commitments	436,359	142,500	73,230	7,782	1,144	661,015	(367)	660,648
Financial guarantees	7,700	4,146	4,080	699	384	17,009	(39)	16,970
In-scope: Irrevocable loan commitments and financial guarantees	444,059	146,646	77,310	8,481	1,528	678,024	(406)	677,618
Loan and other credit-related commitments	92,509	77,891	61,462	3,896	377	236,135	—	236,135
Performance and other guarantees	39,784	32,231	19,445	1,853	964	94,277	(145)	94,132
Out-of-scope: Revocable loan commitments and non-financial guarantees	132,293	110,122	80,907	5,749	1,341	330,412	(145)	330,267

1For the purposes of this disclosure, gross carrying amount is defined as the amortised cost of a financial asset before adjusting for any loss allowance. As such,

the gross carrying amount of debt instruments at FVOCI as presented above will not reconcile to the balance sheet as it excludes fair value gains and losses.

Distribution of financial instruments to which the impairment requirements in IFRS 9 are applied, by credit quality and stage allocation
(Audited)
	Gross carrying/notional amount						Allowance  for ECL	Net
	Strong	Good	Satisfactory	Sub- standard	Credit impaired	Total
	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	515,266	193,080	186,416	22,906	22,705	940,373	(9,715)	930,658
–  stage 1	498,415	170,420	150,818	4,767	—	824,420	(1,078)	823,342
–  stage 2	16,851	22,660	35,598	18,139	—	93,248	(2,546)	90,702
–  stage 3	—	—	—	—	22,615	22,615	(6,040)	16,575
–  POCI	—	—	—	—	90	90	(51)	39
Loans and advances to banks at amortised cost	92,621	4,255	5,040	134	2	102,052	(13)	102,039
–  stage 1	92,528	4,226	4,981	117	—	101,852	(9)	101,843
–  stage 2	93	29	59	17	—	198	(2)	196
–  stage 3	—	—	—	—	2	2	(2)	—
–  POCI	—	—	—	—	—	—	—	—
Other financial assets measured at amortised cost	702,570	85,700	39,660	497	153	828,580	(92)	828,488
–  stage 1	702,373	85,032	38,977	239	—	826,621	(64)	826,557
–  stage 2	197	668	683	258	—	1,806	(5)	1,801
–  stage 3	—	—	—	—	153	153	(23)	130
–  POCI	—	—	—	—	—	—	—	—
Loan and other credit-related commitments	400,120	131,396	77,220	9,670	961	619,367	(348)	619,019
–  stage 1	398,779	125,956	67,949	4,547	—	597,231	(137)	597,094
–  stage 2	1,341	5,440	9,271	5,123	—	21,175	(121)	21,054
–  stage 3	—	—	—	—	958	958	(90)	868
–  POCI	—	—	—	—	3	3	—	3
Financial guarantees	7,365	4,263	4,399	723	248	16,998	(29)	16,969
–  stage 1	7,352	4,192	3,625	184	—	15,353	(8)	15,345
–  stage 2	13	71	774	539	—	1,397	(5)	1,392
–  stage 3	—	—	—	—	248	248	(16)	232
–  POCI	—	—	—	—	—	—	—	—
At 31 Dec 2024	1,717,942	418,694	312,735	33,930	24,069	2,507,370	(10,197)	2,497,173
Debt instruments at FVOCI1
–  stage 1	336,264	9,448	7,290	—	—	353,002	(31)	352,971
–  stage 2	49	—	478	380	—	907	(23)	884
–  stage 3	—	—	—	—	—	—	—	—
–  POCI	—	—	—	—	—	—	—	—
At 31 Dec 2024	336,313	9,448	7,768	380	—	353,909	(54)	353,855

Loans and advances to customers at amortised cost	497,665	206,476	197,582	28,532	19,354	949,609	(11,074)	938,535
–  stage 1	478,422	177,410	147,940	5,612	—	809,384	(1,130)	808,254
–  stage 2	19,243	29,066	49,642	22,920	—	120,871	(2,964)	117,907
–  stage 3	—	—	—	—	19,273	19,273	(6,950)	12,323
–  POCI	—	—	—	—	81	81	(30)	51
Loans and advances to banks at amortised cost	101,057	4,640	6,363	855	2	112,917	(15)	112,902
–  stage 1	101,011	4,631	5,550	287	—	111,479	(10)	111,469
–  stage 2	46	9	813	568	—	1,436	(3)	1,433
–  stage 3	—	—	—	—	2	2	(2)	—
–  POCI	—	—	—	—	—	—	—	—
Other financial assets measured at amortised cost	815,259	80,151	60,197	4,000	664	960,271	(422)	959,849
–  stage 1	814,776	78,486	53,095	516	—	946,873	(109)	946,764
–  stage 2	483	1,665	7,102	3,484	—	12,734	(132)	12,602
–  stage 3	—	—	—	—	664	664	(181)	483
–  POCI	—	—	—	—	—	—	—	—
Loan and other credit-related commitments	436,359	142,500	73,230	7,782	1,144	661,015	(367)	660,648
–  stage 1	432,017	135,192	61,213	2,527	—	630,949	(153)	630,796
–  stage 2	4,342	7,308	12,017	5,255	—	28,922	(128)	28,794
–  stage 3	—	—	—	—	1,140	1,140	(86)	1,054
–  POCI	—	—	—	—	4	4	—	4
Financial guarantees	7,700	4,146	4,080	699	384	17,009	(39)	16,970
–  stage 1	7,497	3,943	3,204	102	—	14,746	(7)	14,739
–  stage 2	203	203	876	597	—	1,879	(7)	1,872
–  stage 3	—	—	—	—	384	384	(25)	359
–  POCI	—	—	—	—	—	—	—	—
At 31 Dec 2023	1,858,040	437,913	341,452	41,868	21,548	2,700,821	(11,917)	2,688,904
Debt instruments at FVOCI1
–  stage 1	288,909	12,037	7,579	—	—	308,525	(37)	308,488
–  stage 2	50	—	318	805	—	1,173	(59)	1,114
–  stage 3	—	—	—	—	5	5	(1)	4
–  POCI	—	—	—	—	—	—	—	—
At 31 Dec 2023	288,959	12,037	7,897	805	5	309,703	(97)	309,606

1For the purposes of this disclosure, gross carrying amount is defined as the amortised cost of a financial asset before adjusting for any loss allowance. As such,

the gross carrying amount of debt instruments at FVOCI as presented above will not reconcile to the balance sheet as it excludes fair value gains and losses.

Credit-impaired loans

(Audited)

We determine that a financial instrument is credit impaired and in

stage 3 by considering relevant objective evidence, primarily whether:

–contractual payments of either principal or interest are past due for

more than 90 days;

–there are other indications that the borrower is unlikely to pay,

such as when a concession has been granted to the borrower for

economic or legal reasons relating to the borrower’s financial

condition; and

–the loan is otherwise considered to be in default. If such

unlikeliness to pay is not identified at an earlier stage, it is deemed

to occur when an exposure is 90 days past due. Therefore, the

    definitions of credit impaired and default are aligned as far as

possible so that stage 3 represents all loans that are considered

defaulted or otherwise credit impaired.

Wholesale lending – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross carrying/ nominal amount	Allowanc e for ECL	Gross carrying/ nominal amount	Allowanc e for ECL	Gross carrying/ nominal amount	Allowanc e for ECL	Gross carrying/ nominal amount	Allowanc e for ECL	Gross carrying/ nominal amount	Allowanc e for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	845,982	(698)	102,129	(1,668)	16,939	(6,207)	85	(30)	965,135	(8,603)
Transfers of financial instruments:	(17,606)	(214)	6,997	825	10,609	(611)	—	—	—	—
–transfers from stage 1 to stage 2	(70,991)	173	70,991	(173)	—	—	—	—	—	—
–transfers from stage 2 to stage 1	55,182	(380)	(55,182)	380	—	—	—	—	—	—
–  transfers to stage 3	(2,056)	7	(9,515)	636	11,571	(643)	—	—	—	—
–  transfers from stage 3	259	(14)	703	(18)	(962)	32	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	214	—	(226)	—	(12)	—	—	—	(24)
Net new and further lending/ repayments	58,044	(151)	(29,842)	311	(4,450)	1,219	7	(7)	23,759	1,372
Change to risk parameters – credit quality	—	112	—	(899)	—	(2,508)	—	(11)	—	(3,306)
Changes to models used for ECL calculation	—	39	—	105	—	—	—	—	—	144
Assets written off	—	—	—	—	(2,925)	2,925	—	—	(2,925)	2,925
Credit-related modifications that resulted in derecognition	—	—	—	—	—	—	—	—	—	—
Foreign exchange and others1 2 3	(53,384)	53	(4,996)	36	4	(153)	1	(3)	(58,375)	(67)
At 31 Dec 2024	833,036	(645)	74,288	(1,516)	20,177	(5,347)	93	(51)	927,594	(7,559)
ECL income statement change for the period		214		(709)		(1,301)		(18)		(1,814)
Recoveries										40
Others										(126)
Total ECL income statement change for the period										(1,900)

1Total includes $2.9bn of gross carrying loans and advances to customers and banks, which were classified to assets held for sale during the year, and a

corresponding allowance for ECL of $23m, reflecting business disposals as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for

sale’ on page 433.

2Total includes $28.9bn of nominal amount and $20m of corresponding allowance for ECL related to derecognition of loan commitments and financial guarantees

following the sale of our banking business in Canada during 2024.

3Total includes $0.3bn of nominal amount related to derecognition of loan commitments and financial guarantees following the sale of our banking business in

Argentina during 2024.

As shown in the above table, the allowance for ECL for loans and

advances to customers and banks and relevant loan commitments

and financial guarantees decreased by $1,044m during the period

from $8,603m at 31 December 2023 to $7,559m at 31 December

2024.

This decrease was driven by:

–$2,925m of assets written off;

–$1,372m relating to volume movements, which included the

allowance for ECL associated with new originations, assets

derecognised and further lending/repayments; and

–$144m relating to changes to models used for ECL calculation.

These were partly offset by:

–$3,306m relating to credit quality changes, including the credit

quality impact of financial instruments transferring between

stages;

–foreign exchange and other movements of $67m; and

–$24m relating to the net remeasurement impact of stage

transfers.

The ECL charge for the period of $1,814m presented in the previous

table consisted of $3,306m relating to credit quality changes,

including the credit quality impact of financial instruments transferring

between stages and $24m relating to the net remeasurement impact

of stage transfers. This was partly offset by $1,372m relating to

underlying net book volume movement and $144m in changes to

models used for ECL calculation.

During the period, there was a net transfer between stage 1 and

stage 2 of $15,809m gross carrying/nominal amounts. It was primarily

driven by our entities in Asia ($12,878m), mainly due to deterioration

in the real estate and construction sectors, and in our main entity in

the US ($1,986m) and Mexico ($1,805m), partly offset by

improvements in the economic outlook that led to upgrades to stage

1 exposures, primarily in our legal entities in the UK($3,077m).

A summary of basis of preparation is available on page 191.

Wholesale lending – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2023	830,322	(670)	124,660	(2,205)	17,068	(6,144)	129	(38)	972,179	(9,057)
Transfers of financial instruments:	(16,804)	(429)	10,247	1,141	6,557	(712)	—	—	—	—
–  transfers from stage 1 to stage 2	(93,511)	172	93,511	(172)	—	—	—	—	—	—
–  transfers from stage 2 to stage 1	77,772	(605)	(77,772)	605	—	—	—	—	—	—
–  transfers to stage 3	(1,444)	20	(6,255)	765	7,699	(785)	—	—	—	—
–  transfers from stage 3	379	(16)	763	(57)	(1,142)	73	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	354	—	(294)	—	(45)	—	—	—	15
Net new and further lending/ repayments	43,282	(138)	(32,082)	311	(3,787)	973	(36)	3	7,377	1,149
Changes to risk parameters – credit quality	—	203	—	(621)	—	(2,941)	—	21	—	(3,338)
Changes to models used for ECL calculation	—	(9)	—	25	—	—	—	—	—	16
Assets written off	—	—	—	—	(2,596)	2,596			(2,596)	2,596
Credit-related modifications that resulted in derecognition	—	—	—	—	(119)	95	—	—	(119)	95
Foreign exchange and others1	(10,818)	(9)	(696)	(25)	(184)	(29)	(8)	(16)	(11,706)	(79)
At 31 Dec 2023	845,982	(698)	102,129	(1,668)	16,939	(6,207)	85	(30)	965,135	(8,603)
ECL income statement change for the period		410		(579)		(2,013)		24		(2,158)
Recoveries										42
Others	—	—	—	—	—	—	—	—	—	(203)
Total ECL income statement change for the period										(2,319)

1Total includes $13.5bn of gross carrying loans and advances to customers and banks, which were classified to assets held for sale during the year, and a

corresponding allowance for ECL of $61m, reflecting business disposals as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for

sale’ on page 433.

Mainland China commercial real estate
(Audited)
	Hong Kong	Mainland China	Rest of the Group	Total
	$m	$m	$m	$m
Loans and advances to customers1	3,161	3,694	303	7,158
Guarantees issued and others2	80	16	5	101
Total mainland China commercial real estate exposure at 31 Dec 2024	3,241	3,710	308	7,259
Distribution of mainland China commercial real estate exposure by credit quality
Strong	118	1,817	109	2,044
Good	578	595	1	1,174
Satisfactory	196	899	49	1,144
Sub-standard	777	136	149	1,062
Credit impaired	1,572	263	—	1,835
At 31 Dec 2024	3,241	3,710	308	7,259
Allowance for ECL by credit quality
Strong	—	(4)	—	(4)
Good	—	(3)	—	(3)
Satisfactory	—	(13)	—	(13)
Sub-standard	(261)	(30)	(17)	(308)
Credit impaired	(749)	(81)	—	(830)
At 31 Dec 2024	(1,010)	(131)	(17)	(1,158)
Allowance for ECL by stage distribution
Stage 1	—	(9)	—	(9)
Stage 2	(261)	(41)	(17)	(319)
Stage 3	(743)	(81)	—	(824)
POCI	(6)	—	—	(6)
At 31 Dec 2024	(1,010)	(131)	(17)	(1,158)
ECL coverage %	31.2	3.5	5.5	16.0

Loans and advances to customers1	6,033	4,917	839	11,789
Guarantees issued and others2	255	66	37	358
Total mainland China commercial real estate exposure at 31 Dec 2023	6,288	4,983	876	12,147
Distribution of mainland China commercial real estate exposure by credit quality
Strong	781	1,723	6	2,510
Good	604	953	421	1,978
Satisfactory	679	1,704	261	2,644
Sub-standard	1,298	327	188	1,813
Credit impaired	2,926	276	—	3,202
At 31 Dec 2023	6,288	4,983	876	12,147
Allowance for ECL by credit quality
Strong	—	(3)	—	(3)
Good	—	(5)	(1)	(6)
Satisfactory	(3)	(27)	—	(30)
Sub-standard	(66)	(87)	(16)	(169)
Credit impaired	(1,726)	(125)	—	(1,851)
At 31 Dec 2023	(1,795)	(247)	(17)	(2,059)
Allowance for ECL by stage distribution
Stage 1	—	(10)	—	(10)
Stage 2	(69)	(112)	(17)	(198)
Stage 3	(1,726)	(125)	—	(1,851)
At 31 Dec 2023	(1,795)	(247)	(17)	(2,059)
ECL coverage %	28.5	5.0	1.9	17.0

1Amounts represent gross carrying amount.

2Amounts represent nominal amount for guarantees and other contingent liabilities.

The mainland China commercial real estate portfolio continues to face

challenges as market fundamentals remain weak and refinancing risks

continue. The portfolio remains closely managed, with reductions in

exposures driven by a combination of de-risking measures,

repayments by performing customers and write-offs in the ‘credit

impaired’ category.

The portfolio of mainland China CRE loans booked in Hong Kong

remains relatively higher risk, with allowances for ECL substantially

against unsecured exposures. For secured exposures, allowances for

ECL are minimal, reflecting the nature and value of the security held.

Approximately half of the performing exposure in the mainland China

CRE portfolio booked in Hong Kong is lending to state-owned

enterprises and relatively strong privately-owned enterprises. This is

reflected in the relatively low allowances for ECL in this part of the

portfolio.

Mainland China real estate market activity remains depressed with

continued weakness in underlying buyer demand for housing. Various

government stimulus measures were introduced in 2024 to underpin

market confidence. Despite some early signs of price stabilisation in

certain cities, these measures have not yet triggered a meaningful

recovery in transaction levels. Financing conditions and liquidity for

borrowers operating in the real estate sector therefore remains

constrained, particularly for privately-owned enterprises. A market

recovery is likely to be protracted and contingent on further

government support. 

The Group has additional exposures to mainland China commercial

real estate as a result of lending to multinational corporates booked

outside of mainland China, which is not incorporated in the table

above.

Collateral and other credit enhancements

(Audited)

Although collateral can be an important mitigant of credit risk, it is the

Group’s practice to lend on the basis of the customer’s ability to meet

their obligations out of cash flow resources rather than placing

primary reliance on collateral and other credit risk enhancements.

Depending on the customer’s standing and the type of product,

facilities may be provided without any collateral or other credit

enhancements. For other lending, a charge over collateral is obtained

and considered in determining the credit decision and pricing. In the

event of default, the Group may utilise the collateral as a source of

repayment.

Depending on its form, collateral can have a significant financial effect

in mitigating our exposure to credit risk. Where there is sufficient

collateral, an expected credit loss is not recognised. This is the case

for reverse repurchase agreements and for certain loans and

advances to customers where the loan to value (‘LTV’) is very low.

Mitigants may include a charge on borrowers’ specific assets, such as

real estate or financial instruments. Other credit risk mitigants include

short positions in securities and financial assets held as part of linked

insurance/investment contracts where the risk is predominantly borne

by the policyholder. Additionally, risk may be managed by employing

other types of collateral and credit risk enhancements, such as

second charges, other liens and unsupported guarantees. Guarantees

are normally taken from corporates and export credit agencies.

Corporates would normally provide guarantees as part of a parent/

subsidiary relationship and span a number of credit grades. The export

credit agencies will normally be investment grade.

Certain credit mitigants are used strategically in portfolio management

activities. While single name concentrations arise in portfolios

managed by Global Banking and Corporate Banking, it is only in Global

Banking that their size requires the use of portfolio level credit

mitigants. Across Global Banking, risk limits and utilisations, maturity

profiles and risk quality are monitored and managed proactively. This

process is key to the setting of risk appetite for these larger, more

complex, geographically distributed customer groups. While the

principal form of risk management continues to be at the point of

exposure origination, through the lending decision-making process,

Global Banking also utilises loan sales and credit default swap (‘CDS’)

hedges to manage concentrations and reduce risk.

These transactions are the responsibility of a dedicated Global

Banking portfolio management team. Hedging activity is carried out

within agreed credit parameters, and is subject to market risk limits

and a robust governance structure. Where applicable, CDSs are

entered into directly with a central clearing house counterparty.

Otherwise, the Group’s exposure to CDS protection providers is

diversified among mainly banking counterparties with strong credit

ratings.

CDS mitigants are held at portfolio level and are not included in the

expected credit loss calculations. CDS mitigants are not reported in

the following tables.

Collateral on loans and advances

Collateral held is analysed separately for commercial real estate and

for other corporate, commercial and financial (non-bank) lending. The

following tables include off-balance sheet loan commitments,

primarily undrawn credit lines.

The collateral measured in the following tables consists of fixed first

charges on real estate, and charges over cash and marketable

financial instruments. The values in the tables represent the expected

market value on an open market basis, actual values realised are a

function of market conditions. No adjustment has been made to the

collateral for any expected costs of recovery. Marketable securities

are measured at their fair value.

Other types of collateral, such as unsupported guarantees and floating

charges over the assets of a customer’s business, are not measured

in the following tables. While such mitigants have value, often

providing rights in insolvency, their assignable value is not sufficiently

certain and they are therefore assigned no value for disclosure

purposes.

The LTV ratios presented are calculated by directly associating loans

and advances with the collateral that individually and uniquely

supports each facility. When collateral assets are shared by multiple

loans and advances, whether specifically or, more generally, by way

of an all monies charge, the collateral value is pro-rated across the

loans and advances protected by the collateral.

For credit-impaired loans, the collateral values cannot be directly

compared with impairment allowances recognised. The LTV figures

use open market values with no adjustments, actual values realised

are a function of market conditions. Impairment allowances are

calculated on a different basis, by considering other cash flows and

adjusting collateral values for costs of realising collateral as explained

further on page 381.

Commercial real estate loans and advances

The value of commercial real estate collateral is determined by using

a combination of external and internal valuations and physical

inspections. For commercial real estate, where the facility exceeds

regulatory threshold requirements, Group policy requires an

independent review of the valuation at least every three years, or

more frequently as the need arises.

In Hong Kong, market practice is typically for lending to major

property companies to be either secured by guarantees or unsecured.

In Europe, facilities of a working capital nature are generally not

secured by a first fixed charge, and are therefore disclosed as not

collateralised.

Wholesale lending – commercial real estate loans and advances to customers including loan commitments by level of collateral for key countries/territories (by stage)
(Audited)
	Gross carrying/nominal amount					ECL coverage
	Stage 1	Stage 2	Stage 3	POCI	Total	Stage 1	Stage 2	Stage 3	POCI	Total
	$m	$m	$m	$m	$m	%	%	%	%	%
Not collateralised	36,168	4,709	1,704	—	42,581	0.1	9.0	47.5	—	3.0
Fully collateralised by LTV ratio	37,090	11,909	5,254	—	54,253	0.1	1.7	7.8	—	1.2
–  less than 50%	20,522	5,154	2,413	—	28,089	0.1	1.7	5.7	—	0.9
–  51% to 75%	11,392	3,840	1,691	—	16,923	0.1	2.2	7.6	—	1.3
–  76% to 90%	2,554	2,277	767	—	5,598	0.1	0.9	12.5	—	2.1
–  91% to 100%	2,622	638	383	—	3,643	0.2	2.3	12.3	—	1.8
Partially collateralised (A):  LTV > 100%	2,119	698	815	64	3,696	0.2	2.8	19.7	45.8	5.8
–  collateral value on A	1,255	457	570	29	2,311
Total at 31 Dec 2024	75,377	17,316	7,773	64	100,530	0.1	3.8	17.7	45.8	2.1
of which: UK
Not collateralised	4,487	1,890	127	—	6,504	0.4	3.8	27.8	—	1.9
Fully collateralised by LTV ratio	9,139	3,194	305	—	12,638	0.2	1.1	8.2	—	0.6
–  less than 50%	2,903	761	160	—	3,824	0.2	1.5	8.0	—	0.8
–  51% to 75%	4,202	1,693	69	—	5,964	0.2	1.2	12.0	—	0.6
–  76% to 90%	1,173	732	24	—	1,929	0.1	0.4	10.2	—	0.3
–  91% to 100%	861	8	52	—	921	0.1	7.7	2.7	—	0.3
Partially collateralised (B):  LTV > 100%	503	565	119	46	1,233	0.2	2.9	21.1	48.6	5.3
–  collateral value on B	296	350	69	26	741
Total UK at 31 Dec 2024	14,129	5,649	551	46	20,375	0.2	2.2	15.5	48.6	1.3
of which: Hong Kong
Not collateralised	16,380	2,312	1,404	—	20,096	—	14.3	47.9	—	5.0
Fully collateralised by LTV ratio	17,115	6,045	4,127	—	27,287	0.1	1.4	5.8	—	1.2
–  less than 50%	12,935	3,589	2,102	—	18,626	0.1	1.3	3.8	—	0.7
–  51% to 75%	3,534	1,059	1,243	—	5,836	0.1	2.2	6.2	—	1.8
–  76% to 90%	336	1,050	654	—	2,040	0.1	1.1	11.8	—	4.4
–  91% to 100%	310	347	128	—	785	—	0.5	2.4	—	0.6
Partially collateralised (C):  LTV > 100%	185	62	562	18	827	—	1.9	17.6	38.1	12.9
–  collateral value on C	119	41	397	3	560
Total Hong Kong at 31 Dec 2024	33,680	8,419	6,093	18	48,210	—	4.9	16.6	38.1	3.0
Not collateralised	36,754	5,128	2,543	—	44,425	0.1	3.9	72.4	—	4.7
Fully collateralised by LTV ratio	46,212	15,177	1,963	—	63,352	0.1	2.5	12.0	—	1.0
–  less than 50%	24,391	7,413	574	—	32,378	0.1	1.9	13.1	—	0.7
–  51% to 75%	16,086	5,240	657	—	21,983	0.1	3.1	9.3	—	1.1
–  76% to 90%	3,140	1,437	454	—	5,031	0.1	3.5	11.8	—	2.1
–  91% to 100%	2,595	1,087	278	—	3,960	0.2	2.3	16.6	—	1.9
Partially collateralised (A):  LTV > 100%	7,075	1,487	156	50	8,768	0.1	1.8	30.2	14.5	1.0
–  collateral value on A	4,004	1,061	115	26	5,206
Total at 31 Dec 2023	90,041	21,792	4,662	50	116,545	0.1	2.8	45.6	14.5	2.4
of which: UK
Not collateralised	4,644	1,288	97	—	6,029	0.4	2.0	12.4	—	0.9
Fully collateralised by LTV ratio	9,762	2,512	295	—	12,569	0.1	1.3	13.9	—	0.7
–  less than 50%	3,514	507	51	—	4,072	0.1	1.9	21.6	—	0.6
–  51% to 75%	4,826	1,418	103	—	6,347	0.1	1.1	16.4	—	0.6
–  76% to 90%	749	292	80	—	1,121	0.1	1.3	14.9	—	1.5
–  91% to 100%	673	295	61	—	1,029	0.1	1.6	1.9	—	0.6
Partially collateralised (B):  LTV > 100%	1,580	239	82	35	1,936	0.1	1.1	34.2	20.7	2.0
–  collateral value on B	524	171	62	17	774
Total UK at 31 Dec 2023	15,986	4,039	474	35	20,534	0.2	1.5	17.1	20.7	0.9
of which: Hong Kong
Not collateralised	16,889	2,323	2,215	—	21,427	—	6.5	78.7	—	8.8
Fully collateralised by LTV ratio	20,783	8,447	989	—	30,219	—	2.1	5.0	—	0.8
–  less than 50%	15,425	5,604	294	—	21,323	—	1.5	1.4	—	0.5
–  51% to 75%	4,102	2,140	312	—	6,554	0.1	3.8	2.1	—	1.4
–  76% to 90%	657	619	315	—	1,591	0.1	1.8	8.0	—	2.3
–  91% to 100%	599	84	68	—	751	—	0.1	20.5	—	1.9
Partially collateralised (C):  LTV > 100%	1,770	616	52	15	2,453	—	0.8	24.5	—	0.7
–  collateral value on C	1,569	535	39	8	2,151
Total Hong Kong at 31 Dec 2023	39,442	11,386	3,256	15	54,099	—	2.9	55.5	—	4.0

Wholesale lending – other corporate, commercial and financial (non-bank) loans and advances including loan commitments by level of collateral for key countries/territories (by stage)
(Audited)
	Gross carrying/nominal amount					ECL coverage
	Stage 1	Stage 2	Stage 3	POCI	Total	Stage 1	Stage 2	Stage 3	POCI	Total
	$m	$m	$m	$m	$m	%	%	%	%	%
Not collateralised	713,028	62,844	6,870	5	782,747	0.1	0.9	41.5	14.2	0.5
Fully collateralised by LTV ratio	87,488	11,992	3,394	21	102,895	0.1	2.0	8.0	98.1	0.6
–  less than 50%	39,432	4,360	1,703	—	45,495	0.1	1.6	6.9	—	0.5
–  51% to 75%	20,169	4,643	778	21	25,611	0.1	2.8	12.0	98.1	1.0
–  76% to 90%	9,016	1,515	512	—	11,043	0.1	1.6	7.1	—	0.6
–  91% to 100%	18,871	1,474	401	—	20,746	—	0.8	6.3	—	0.2
Partially collateralised (A):  LTV > 100%	51,536	5,772	2,411	3	59,722	0.1	0.8	34.3	7.0	1.5
–  collateral value on A	22,800	2,519	1,162	1	26,482
Total at 31 Dec 2024	852,052	80,608	12,675	29	945,364	0.1	1.1	31.2	72.8	0.6
of which: UK
Not collateralised	134,075	10,822	2,661	4	147,562	0.1	2.5	32.4	—	0.9
Fully collateralised by LTV ratio	24,552	3,046	968	—	28,566	0.1	2.4	5.8	—	0.6
–  less than 50%	9,183	1,288	473	—	10,944	0.1	2.2	2.8	—	0.5
–  51% to 75%	7,544	1,216	244	—	9,004	0.1	2.7	7.0	—	0.7
–  76% to 90%	2,942	367	129	—	3,438	0.1	2.3	15.3	—	0.9
–  91% to 100%	4,883	175	122	—	5,180	0.1	2.1	5.3	—	0.3
Partially collateralised (B):  LTV > 100%	7,016	1,055	395	—	8,466	0.2	1.3	10.8	—	0.8
–  collateral value on B	3,832	581	252	—	4,665
Total UK at 31 Dec 2024	165,643	14,923	4,024	4	184,594	0.1	2.4	23.9	—	0.8
of which: Hong Kong
Not collateralised	117,849	6,389	1,313	—	125,551	—	0.6	58.1	—	0.7
Fully collateralised by LTV ratio	28,291	5,866	1,877	21	36,055	0.1	2.1	5.3	98.1	0.7
–  less than 50%	14,500	1,774	903	—	17,177	0.1	1.4	5.1	—	0.5
–  51% to 75%	7,331	2,766	449	21	10,567	0.1	3.0	8.3	98.1	1.4
–  76% to 90%	2,896	752	372	—	4,020	0.1	1.9	3.6	—	0.7
–  91% to 100%	3,564	574	153	—	4,291	—	0.3	1.7	—	0.1
Partially collateralised (C):  LTV > 100%	17,125	1,535	1,048	—	19,708	—	0.4	46.8	—	2.6
–  collateral value on C	6,741	627	639	—	8,007
Total Hong Kong at 31 Dec 2024	163,265	13,790	4,238	21	181,314	—	1.2	31.9	98.1	0.9
Not collateralised	672,142	76,261	7,702	8	756,113	0.1	0.9	40.0	6.8	0.6
Fully collateralised by LTV ratio	113,339	19,747	2,629	23	135,738	0.1	1.4	10.7	89.8	0.5
–  less than 50%	42,953	7,069	1,168	—	51,190	0.1	1.5	11.8	—	0.5
–  51% to 75%	24,011	8,222	887	—	33,120	0.1	1.3	6.4	—	0.6
–  76% to 90%	10,194	2,531	421	23	13,169	0.1	1.6	10.3	90.6	0.9
–  91% to 100%	36,181	1,925	153	—	38,259	—	1.1	27.6	—	0.2
Partially collateralised (A):  LTV > 100%	53,686	9,019	2,233	3	64,941	0.1	0.7	32.2	38.4	1.3
–  collateral value on A	24,505	4,266	993	1	29,765
Total at 31 Dec 2023	839,167	105,027	12,564	34	956,792	0.1	1.0	32.5	67.1	0.6
of which: UK
Not collateralised	117,824	20,401	3,423	—	141,648	0.2	1.9	23.2	—	1.0
Fully collateralised by LTV ratio	22,217	5,912	1,162	—	29,291	0.1	1.7	3.7	—	0.6
–  less than 50%	7,385	2,340	601	—	10,326	0.1	1.2	1.3	—	0.5
–  51% to 75%	6,966	2,292	434	—	9,692	0.1	1.7	3.6	—	0.7
–  76% to 90%	2,256	809	106	—	3,171	0.2	2.5	15.8	—	1.3
–  91% to 100%	5,610	471	21	—	6,102	0.1	2.1	14.5	—	0.3
Partially collateralised (B):  LTV > 100%	6,335	1,732	299	—	8,366	0.2	1.8	18.4	—	1.2
–  collateral value on B	3,508	1,080	175	—	4,763
Total UK at 31 Dec 2023	146,376	28,045	4,884	—	179,305	0.2	1.8	18.3	—	0.9
of which: Hong Kong
Not collateralised	114,025	7,523	906	—	122,454	—	0.4	57.5	—	0.5
Fully collateralised by LTV ratio	32,857	8,918	877	22	42,674	0.1	1.3	6.6	94.7	0.5
–  less than 50%	16,175	2,898	230	—	19,303	0.1	1.4	11.8	—	0.4
–  51% to 75%	9,461	4,515	336	—	14,312	0.1	1.2	3.1	—	0.5
–  76% to 90%	4,245	863	253	22	5,383	0.1	1.8	2.0	94.7	0.9
–  91% to 100%	2,976	642	58	—	3,676	—	0.4	27.0	—	0.5
Partially collateralised (C):  LTV > 100%	16,152	2,887	704	—	19,743	—	0.6	30.2	—	1.2
–  collateral value on C	6,619	1,306	318	—	8,243
Total Hong Kong at 31 Dec 2023	163,034	19,328	2,487	22	184,871	0.1	0.8	31.8	94.7	0.6

Personal lending – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	650,823	(602)	50,955	(1,434)	3,860	(856)	705,638	(2,892)
Transfers of financial instruments:	(2,023)	(1,045)	(345)	1,477	2,368	(432)	—	—
–  transfers from stage 1 to stage 2	(45,220)	246	45,220	(246)	—	—	—	—
–  transfers from stage 2 to stage 1	43,549	(1,247)	(43,549)	1,247	—	—	—	—
–  transfers to stage 3	(743)	9	(2,715)	685	3,458	(694)	—	—
–  transfers from stage 3	391	(53)	699	(209)	(1,090)	262	—	—
Net remeasurement of ECL arising from transfer of stage	—	745	—	(605)	—	(132)	—	8
Changes due to modifications not derecognised	—	—	—	—	(25)	—	(25)	—
Net new and further lending/repayments	29,789	(17)	(7,889)	278	(796)	470	21,104	731
Change to risk parameters – credit quality	—	251	—	(874)	—	(1,437)	—	(2,060)
Changes to models used for ECL calculation	—	29	—	(109)	—	(20)	—	(100)
Assets written off	—	—	—	—	(1,534)	1,534	(1,534)	1,534
Foreign exchange and others1,2,3	(21,938)	52	(1,111)	109	(227)	72	(23,276)	233
At 31 Dec 2024	656,651	(587)	41,610	(1,158)	3,646	(801)	701,907	(2,546)
ECL income statement change for the period		1,008		(1,310)		(1,119)		(1,421)
Recoveries								220
Others								(32)
Total ECL income statement change for the period								(1,233)

1Total includes $0.8bn of gross carrying loans and advances to customers, which were classified to assets held for sale, and a corresponding allowance for ECL of

$23m, reflecting business disposals, as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for sale’ on page 433.

2Total includes $6.4bn of nominal amount and $1m of corresponding allowance for ECL related to derecognition of loan commitments and financial guarantees

following the sale of our banking business in Canada during 2024.

3Total includes $2.4bn of nominal amount related to derecognition of loan commitments and financial guarantees following the sale of our banking business in

Argentina during 2024.

As shown in the above table, the allowance for ECL for loans and advances to customers and relevant loan commitments and financial

guarantees decreased by $346m during the period from $2,892m at 31 December 2023 to $2,546m at 31 December 2024.

This decrease was driven by:

–$1,534m of assets written off;

–$731m relating to volume movements, which included the

allowance for ECL associated with new originations, assets

derecognised and further lending/repayment;

–foreign exchange and other movements of $233m; and

–$8m relating to the net remeasurement impact of stage transfers.

These were partly offset by:

–$2,060m relating to credit quality changes, including the credit

quality impact of financial instruments transferring between

stages; and

–$100m of changes to models used for ECL calculation.

The ECL charge for the period of $1,421m presented in the above

table consisted of $2,060m relating to credit quality changes,

including the credit quality impact of financial instruments transferring

between stages, and $100m relating to changes to models used for

the calculation of ECL. This was partly offset by $731m relating to

underlying net book volume movements and $8m relating to the net

remeasurement impact of stage transfer.

During the period, there was a net transfer between stage 1 and

stage 2 of $1,671m gross carrying/nominal amounts. This increase

was mainly driven by HSBC UK ($3,410m) due to mortgages portfolio

and Mexico ($860m) due to a slight deterioration in unsecured lending

portfolio, partly offset by Hong Kong ($2,983m) due to improvement

in credit cards and other unsecured lending portfolio.

A summary of basis of preparation is available on page 191.

Personal lending – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to customers including loan commitments and financial guarantees
(Audited)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2023	603,321	(587)	52,563	(1,505)	4,139	(805)	660,023	(2,897)
Transfers of financial instruments:	(2,144)	(619)	39	1,087	2,105	(468)	—	—
–  transfers from stage 1 to stage 2	(57,217)	270	57,217	(270)	—	—	—	—
–  transfers from stage 2 to stage 1	55,307	(862)	(55,307)	862	—	—	—	—
–  transfers to stage 3	(542)	3	(2,345)	614	2,887	(617)	—	—
–  transfers from stage 3	308	(30)	474	(119)	(782)	149	—	—
Net remeasurement of ECL arising from transfer of stage	—	563	—	(679)	—	(79)	—	(195)
Net new and further lending/repayments	34,411	(47)	(4,713)	350	(1,169)	144	28,529	447
Change to risk parameters – credit quality	—	104	—	(641)	—	(955)	—	(1,492)
Changes to models used for ECL calculation	—	(13)	—	21	—	7	—	15
Assets written off	—	—	—	—	(1,326)	1,326	(1,326)	1,326
Foreign exchange and others1,2	15,235	(3)	3,066	(67)	111	(26)	18,412	(96)
At 31 Dec 2023	650,823	(602)	50,955	(1,434)	3,860	(856)	705,638	(2,892)
ECL income statement change for the period		607		(949)		(883)		(1,225)
Recoveries								226
Others								8
Total ECL income statement change for the period								(991)

1Total includes $7.8bn of gross carrying loans and advances and a corresponding allowance for ECL of $11m, due to the retention of certain balances previously

classified as assets held for sale of our retail banking operations in France. For further details, see Note 23 ‘Assets held for sale and liabilities of disposal groups

held for sale’ on page 433.

2Total includes $2.0bn of gross carrying loans and advances to customers, which were classified to assets held for sale, and a corresponding allowance for ECL of

$20m, reflecting business disposals, as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for sale’ on page 433.

First lien residential mortgages – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to customers including loan commitments and financial guarantees
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	340,764	(109)	38,513	(202)	2,258	(264)	381,535	(575)
Transfers of financial instruments:	(3,561)	(232)	2,694	232	867	—	—	—
–  transfers from stage 1 to stage 2	(33,524)	23	33,524	(23)	—	—	—	—
–  transfers from stage 2 to stage 1	30,113	(244)	(30,113)	244	—	—	—	—
–  transfers to stage 3	(290)	6	(1,127)	90	1,417	(96)	—	—
–  transfers from stage 3	140	(17)	410	(79)	(550)	96	—	—
Net remeasurement of ECL arising from transfer of stage	—	163	—	(152)	—	(30)	—	(19)
Changes due to modifications not derecognised	—	—	—	—	—	—	—	—
Net new and further lending/repayments	14,008	20	(6,336)	26	(523)	33	7,149	79
Change to risk parameters – credit quality	—	115	—	(73)	—	(103)	—	(61)
Changes to models used for ECL calculation	—	(8)	—	29	—	1	—	22
Assets written off	—	—	—	—	(63)	63	(63)	63
Foreign exchange and others	(6,535)	(7)	(530)	10	(65)	15	(7,130)	18
At 31 Dec 2024	344,676	(58)	34,341	(130)	2,474	(285)	381,491	(473)
ECL income statement change for the period		290		(170)		(99)		21
Recoveries								7
Others								(1)
Total ECL income statement change for the period								27

At 1 Jan 2023	317,666	(74)	40,048	(231)	2,230	(270)	359,944	(575)
Transfers of financial instruments:	(1,182)	(109)	421	138	761	(29)	—	—
–  transfers from stage 1 to stage 2	(41,207)	28	41,207	(28)	—	—	—	—
–  transfers from stage 2 to stage 1	40,164	(117)	(40,164)	117	—	—	—	—
–  transfers to stage 3	(354)	1	(958)	100	1,312	(101)	—	—
–  transfers from stage 3	215	(21)	336	(51)	(551)	72	—	—
Net remeasurement of ECL arising from transfer of stage	—	72	—	(79)	—	(67)	—	(74)
Net new and further lending/repayments	15,447	(3)	(3,939)	22	(751)	322	10,757	341
Change to risk parameters – credit quality	—	16	—	(67)	—	(269)	—	(320)
Changes to models used for ECL calculation	—	(2)	—	28	—	—	—	26
Assets written off	—	—	—	—	(53)	53	(53)	53
Foreign exchange and others	8,833	(9)	1,983	(13)	71	(4)	10,887	(26)
At 31 Dec 2023	340,764	(109)	38,513	(202)	2,258	(264)	381,535	(575)
ECL income statement change for the period		83		(96)		(14)		(27)
Recoveries								10
Others								13
Total ECL income statement change for the period								(4)

Credit cards – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to customers including loan commitments
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	153,292	(253)	6,547	(698)	450	(144)	160,289	(1,095)
Transfers of financial instruments:	796	(453)	(1,469)	717	673	(264)	—	—
–  transfers from stage 1 to stage 2	(6,427)	129	6,427	(129)	—	—	—	—
–  transfers from stage 2 to stage 1	7,255	(569)	(7,255)	569	—	—	—	—
–  transfers to stage 3	(179)	2	(765)	327	944	(329)	—	—
–  transfers from stage 3	147	(15)	124	(50)	(271)	65	—	—
Net remeasurement of ECL arising from transfer of stage	—	280	—	(256)	—	(45)	—	(21)
Changes due to modifications not derecognised	—	—	—	—	(2)	—	(2)	—
Net new and further lending/repayments	9,604	18	(1,122)	127	(1)	194	8,481	339
Change to risk parameters – credit quality	—	79	—	(476)	—	(694)	—	(1,091)
Changes to models used for ECL calculation	—	22	—	(122)	—	1	—	(99)
Assets written off	—	—	—	—	(736)	736	(736)	736
Foreign exchange and others1	(7,380)	27	(196)	50	(41)	17	(7,617)	94
At 31 Dec 2024	156,312	(280)	3,760	(658)	343	(199)	160,415	(1,137)
ECL income statement change for the period		399		(727)		(544)		(872)
Recoveries								106
Others								(10)
Total ECL income statement change for the period								(776)

	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2023	140,519	(244)	6,747	(777)	353	(160)	147,619	(1,181)
Transfers of financial instruments:	199	(292)	(848)	496	649	(204)	—	—
–  transfers from stage 1 to stage 2	(7,855)	102	7,855	(102)	—	—	—	—
–  transfers from stage 2 to stage 1	8,124	(391)	(8,124)	391	—	—	—	—
–  transfers to stage 3	(82)	1	(621)	227	703	(228)	—	—
–  transfers from stage 3	12	(4)	42	(20)	(54)	24	—	—
Net remeasurement of ECL arising from transfer of stage	—	185	—	(301)	—	(5)	—	(121)
Net new and further lending/repayments	13,206	27	621	169	12	(41)	13,839	155
Change to risk parameters – credit quality	—	82	—	(281)	—	(301)	—	(500)
Changes to models used for ECL calculation	—	(9)	—	15	—	1	—	7
Assets written off	—	—	—	—	(571)	571	(571)	571
Foreign exchange and others	(632)	(2)	27	(19)	7	(5)	(598)	(26)
At 31 Dec 2023	153,292	(253)	6,547	(698)	450	(144)	160,289	(1,095)
ECL income statement change for the period		285		(398)		(346)		(459)
Recoveries								108
Others								(200)
Total ECL income statement change for the period								(551)

Other personal lending – reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to customers including loan commitments and financial guarantees
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	156,767	(240)	5,895	(534)	1,152	(448)	163,814	(1,222)
Transfers of financial instruments:	742	(360)	(1,570)	528	828	(168)	—	—
–  transfers from stage 1 to stage 2	(5,269)	94	5,269	(94)	—	—	—	—
–  transfers from stage 2 to stage 1	6,181	(434)	(6,181)	434	—	—	—	—
–  transfers to stage 3	(274)	1	(823)	268	1,097	(269)	—	—
–  transfers from stage 3	104	(21)	165	(80)	(269)	101	—	—
Net remeasurement of ECL arising from transfer of stage	—	302	—	(197)	—	(57)	—	48
Changes due to modifications not derecognised	—	—	—	—	(23)	—	(23)	—
Net new and further lending/repayments	6,177	(55)	(431)	125	(272)	243	5,474	313
Change to risk parameters – credit quality	—	57	—	(325)	—	(640)	—	(908)
Changes to models used for ECL calculation	—	15	—	(16)	—	(22)	—	(23)
Assets written off	—	—	—	—	(735)	735	(735)	735
Foreign exchange and others1,2	(8,023)	32	(385)	49	(121)	40	(8,529)	121
At 31 Dec 2024	155,663	(249)	3,509	(370)	829	(317)	160,001	(936)
ECL income statement change for the period		319		(413)		(476)		(570)
Recoveries								107
Others								(21)
Total ECL income statement change for the period								(484)

1Total includes $0.3bn of gross carrying loans and advances, which were classified to assets held for sale, and a corresponding allowance for ECL of $10m,

reflecting business disposals, as disclosed in Note 23 ‘Assets held for sale and liabilities of disposal groups held for sale’ on page 433.

2Total includes $4.4bn of nominal amount related to derecognition of loan commitments and financial guarantees following the sale of our banking business in

Canada during 2024.

	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2023	145,136	(269)	5,768	(497)	1,556	(375)	152,460	(1,141)
Transfers of financial instruments:	(1,161)	(218)	466	453	695	(235)	—	—
–  transfers from stage 1 to stage 2	(8,155)	140	8,155	(140)	—	—	—	—
–  transfers from stage 2 to stage 1	7,019	(354)	(7,019)	354	—	—	—	—
–  transfers to stage 3	(106)	1	(766)	287	872	(288)	—	—
–  transfers from stage 3	81	(5)	96	(48)	(177)	53	—	—
Net remeasurement of ECL arising from transfer of stage	—	306	—	(299)	—	(7)	—	—
Net new and further lending/repayments	5,758	(71)	(1,395)	159	(430)	(137)	3,933	(49)
Change to risk parameters – credit quality	—	6	—	(293)	—	(385)	—	(672)
Changes to models used for ECL calculation	—	(2)	—	(22)	—	6	—	(18)
Assets written off	—	—	—	—	(702)	702	(702)	702
Foreign exchange and others1	7,034	8	1,056	(35)	33	(17)	8,123	(44)
At 31 Dec 2023	156,767	(240)	5,895	(534)	1,152	(448)	163,814	(1,222)
ECL income statement change for the period		239		(455)		(523)		(739)
Recoveries								108
Others								195
Total ECL income statement change for the period								(436)

1Total includes $7.2bn of gross carrying loans and advances and a corresponding allowance for ECL of $10m, due to the retention of certain balances previously

classified as assets held for sale of our retail banking operations in France. For further details, see Note 23 ‘Assets held for sale and liabilities of disposal groups

held for sale’ on page 433.

Collateral on loans and advances

(Audited)

The following table provides a quantification of the value of fixed

charges we hold over specific assets where we have a history

of enforcing, and are able to enforce, collateral in satisfying a debt in

the event of the borrower failing to meet its contractual obligations,

and where the collateral is cash or can be realised by sale in an

established market. The collateral valuation excludes any adjustments

for obtaining and selling the collateral and, in particular, loans shown

as not collateralised or partially collateralised may also benefit from

other forms of credit mitigants.

Personal lending – residential mortgage loans including loan commitments by level of collateral for key countries/territories by stage
(Audited)
	Gross carrying/nominal amount				ECL coverage
	Stage 1	Stage 2	Stage 3	Total	Stage 1	Stage 2	Stage 3	Total
	$m	$m	$m	$m	%	%	%	%
Fully collateralised by LTV ratio	332,641	34,203	2,371	369,215	—	0.4	10.0	0.1
–  less than 50%	141,331	18,076	1,238	160,645	—	0.2	7.6	0.1
–  51% to 70%	111,963	11,507	698	124,168	—	0.4	11.2	0.1
–  71% to 80%	39,374	3,040	242	42,656	—	0.7	13.1	0.1
–  81% to 90%	25,514	1,264	131	26,909	—	0.9	15.0	0.1
–  91% to 100%	14,459	316	62	14,837	—	1.8	22.4	0.1
Partially collateralised (A): LTV > 100%	12,031	139	103	12,273	—	3.2	46.2	0.4
–  collateral value on A	11,274	126	70	11,470
Total at 31 Dec 2024	344,672	34,342	2,474	381,488	—	0.4	11.5	0.1
of which: UK
Fully collateralised by LTV ratio	151,264	30,574	747	182,585	—	0.2	8.5	0.1
–  less than 50%	62,753	16,689	445	79,887	—	0.1	6.9	0.1
–  51% to 70%	50,374	10,456	206	61,036	—	0.2	9.7	0.1
–  71% to 80%	20,552	2,423	64	23,039	—	0.4	12.1	0.1
–  81% to 90%	15,965	939	23	16,927	—	0.6	13.0	0.1
–  91% to 100%	1,620	67	9	1,696	—	0.7	16.7	0.1
Partially collateralised (B): LTV > 100%	146	15	5	166	—	1.0	27.7	0.9
–  collateral value on B	109	12	4	125
Total UK at 31 Dec 2024	151,410	30,589	752	182,751	—	0.2	8.6	0.1
of which: Hong Kong
Fully collateralised	95,751	756	138	96,645	—	—	1.3	—
–  less than 50%	38,894	372	79	39,345	—	—	0.4	—
–  51% to 70%	30,088	227	31	30,346	—	—	0.4	—
–  71% to 80%	6,783	47	11	6,841	—	—	5.1	—
–  81% to 90%	7,602	42	9	7,653	—	0.2	1.1	—
–  91% to 100%	12,384	68	8	12,460	—	0.1	8.8	—
Partially collateralised (C): LTV > 100%	11,744	103	14	11,861	—	0.2	19.1	—
–  collateral value on C	11,034	96	12	11,142
Total Hong Kong at 31 Dec 2024	107,495	859	152	108,506	—	0.1	2.9	—

Fully collateralised by LTV ratio	331,279	38,378	2,129	371,786	—	0.5	10.1	0.1
–  less than 50%	140,992	19,715	1,165	161,872	—	0.3	7.1	0.1
–  51% to 70%	113,043	12,636	568	126,247	—	0.6	10.9	0.1
–  71% to 80%	37,866	4,111	229	42,206	—	0.9	15.2	0.2
–  81% to 90%	23,278	1,499	109	24,886	—	1.2	17.3	0.2
–  91% to 100%	16,100	417	58	16,575	—	1.6	28.9	0.2
Partially collateralised (A): LTV > 100%	9,529	136	129	9,794	—	3.4	42.0	0.6
–  collateral value on A	8,968	123	104	9,195
Total at 31 Dec 2023	340,808	38,514	2,258	381,580	—	0.5	11.9	0.1
of which: UK
Fully collateralised by LTV ratio	146,739	33,597	759	181,095	—	0.3	9.7	0.1
–  less than 50%	60,403	17,629	458	78,490	—	0.2	7.9	0.1
–  51% to 70%	49,945	11,248	207	61,400	—	0.4	9.4	0.1
–  71% to 80%	20,293	3,275	61	23,629	—	0.6	13.4	0.1
–  81% to 90%	12,946	1,161	18	14,125	—	0.8	17.5	0.1
–  91% to 100%	3,152	284	15	3,451	—	1.0	41.6	0.3
Partially collateralised (B): LTV > 100%	317	19	27	363	0.1	1.7	17.5	1.4
–  collateral value on B	244	15	22	281
Total UK at 31 Dec 2023	147,056	33,616	786	181,458	—	0.3	9.9	0.1
of which: Hong Kong
Fully collateralised by LTV ratio	97,414	1,354	93	98,861	—	—	0.3	—
–  less than 50%	41,903	831	66	42,800	—	—	0.1	—
–  51% to 70%	29,762	330	15	30,107	—	—	0.5	—
–  71% to 80%	5,260	48	2	5,310	—	0.1	0.4	—
–  81% to 90%	8,161	61	4	8,226	—	0.1	1.9	—
–  91% to 100%	12,328	84	6	12,418	—	0.3	1.8	—
Partially collateralised (C): LTV > 100%	8,973	86	4	9,063	—	0.9	7.8	—
–  collateral value on C	8,535	81	4	8,620
Total Hong Kong at 31 Dec 2023	106,387	1,440	97	107,924	—	0.1	0.7	—

HSBC Holdings

(Audited)

Credit risk in HSBC Holdings primarily arises from transactions with

Group subsidiaries.

In HSBC Holdings, the maximum exposure to credit risk arises from

two components:

–financial assets on the balance sheet, where maximum exposure

equals the carrying amount (see page 372); and

–financial guarantees and other guarantees, where the maximum

exposure is the maximum that we would have to pay if the

guarantees were called upon (see Note 33).

In the case of our derivative asset balances (see page 372), there is a

legally enforceable right of offset in the event of counterparty default

and where, as a result, there is a net exposure for credit risk

purposes. However, as there is no intention to settle these balances

on a net basis under normal circumstances, they do not qualify for net

presentation for accounting purposes. These offsets also include

collateral received in cash and other financial assets.

The total offset relating to our derivative asset balances was $3.0bn at

31 December 2024 (2023: $3.0bn).

The credit quality of loans and advances and financial investments,

both of which consist of intra-Group lending and US Treasury bills and

bonds, is assessed as ‘strong’, with 100% of the exposure being

neither past due nor impaired (2023: 100%). For further details of

credit quality classification, see page 170.Approach and policy

(Audited)

Our objective in the management of treasury risk is to maintain

appropriate levels of capital, liquidity, funding, foreign exchange and

market risk to support our business strategy, and meet our regulatory

and stress testing-related requirements.

Our approach to treasury management is driven by our strategic and

organisational requirements, and considers the regulatory, economic

and commercial environment. We aim to maintain a strong capital and

liquidity base to support the risks inherent in our business and invest

in accordance with our strategy, meeting both consolidated and local

regulatory requirements at all times.

Our policy is underpinned by our risk management framework. The

risk management framework incorporates a number of measures

aligned to our assessment of risks for both internal and regulatory

purposes. These risks include credit, market, operational, pensions,

structural and transactional foreign exchange risk, and interest rate

risk in the banking book.

For further details, refer to our Pillar 3 Disclosures at 31 December 2024.

Own funds disclosure
(Audited)		At
		31 Dec 2024	31 Dec 2023
Ref*		$m	$m
	Common equity tier 1 capital: instruments and reserves
1	Capital instruments and the related share premium accounts	22,378	22,964
	–  ordinary shares	22,378	22,964
2	Retained earnings1	138,959	135,614
3	Accumulated other comprehensive income (and other reserves)1	(8,410)	(7,195)
5	Minority interests (amount allowed in consolidated CET1)	3,960	3,917
5a	Independently reviewed net profits net of any foreseeable charge or dividend	7,184	10,568
6	Common equity tier 1 capital before regulatory adjustments	164,071	165,868
28	Total regulatory adjustments to common equity tier 1	(39,160)	(39,367)
29	Common equity tier 1 capital	124,911	126,501
36	Additional tier 1 capital before regulatory adjustments	19,286	17,732
43	Total regulatory adjustments to additional tier 1 capital	(70)	(70)
44	Additional tier 1 capital	19,216	17,662
45	Tier 1 capital	144,127	144,163
51	Tier 2 capital before regulatory adjustments	29,334	28,148
57	Total regulatory adjustments to tier 2 capital	(1,075)	(1,107)
58	Tier 2 capital	28,259	27,041
59	Total capital	172,386	171,204

*The references identify lines prescribed in the PRA template, which are applicable and where there is a value.

1We have updated the classification between components of shareholders’ equity to present ‘Retained Earnings’ in Row 2 and ‘Accumulated other

comprehensive income (and other reserves)’ in Row 3. The comparatives have been aligned.

Funding sources
(Audited)
	2024	2023
	$m	$m
Customer accounts	1,654,955	1,611,647
Deposits by banks	73,997	73,163
Repurchase agreements – non-trading	180,880	172,100
Debt securities in issue	105,785	93,917
Cash collateral, margin, settlement accounts and items in course of transmission to other banks	82,732	92,550
Liabilities of disposal groups held for sale	29,011	108,406
Subordinated liabilities	25,958	24,954
Financial liabilities designated at fair value	138,727	141,426
Insurance contract liabilities	107,629	120,851
Trading liabilities	65,982	73,150
–  repos	14,806	12,198
–  stock lending	3,525	3,322
–  other trading liabilities	47,651	57,630
Total equity	192,273	192,610
Other balance sheet liabilities	359,119	333,903
At 31 Dec	3,017,048	3,038,677

Funding uses
(Audited)
	2024	2023
	$m	$m
Loans and advances to customers	930,658	938,535
Loans and advances to banks	102,039	112,902
Reverse repurchase agreements – non-trading	252,549	252,217
Cash collateral, margin, settlement accounts and items in course of collection from other banks	78,538	96,253
Assets held for sale	27,234	114,134
Trading assets	314,842	289,159
–  reverse repos	16,823	16,575
–  stock borrowing	8,374	14,609
–  other trading assets	289,645	257,975
Financial investments	493,166	442,763
Cash and balances with central banks	267,674	285,868
Other balance sheet assets	550,348	506,846
At 31 Dec	3,017,048	3,038,677

The Group non-trading VaR for 2024 is shown in the table below.

Non-trading VaR, 99% 10 day
(Audited)
	Interest rate	Credit spread	Portfolio diversification1	Total2
	$m	$m	$m	$m
Balance at 31 Dec 2024	528.4	246.1	(220.7)	553.8
Average	603.7	315.1	(222.9)	695.8
Maximum	1,000.6	369.1		1,097.6
Minimum	292.1	242.4		408.7
Balance at 31 Dec 2023	549.6	356.7	(329.5)	576.7
Average	494.0	266.1	(201.6)	558.6
Maximum	638.6	368.0	—	709.4
Minimum	344.0	174.5	—	401.5

1Portfolio diversification is the market risk dispersion effect of holding a portfolio containing different risk types. It represents the reduction in unsystematic

market risk that occurs when combining a number of different risk types – such as interest rate and credit spreads – together in one portfolio. It is measured as

the difference between the sum of the VaR by individual risk type and the combined total VaR. A negative number represents the benefit of portfolio

diversification. As the maximum and minimum occurs on different days for different risk types, it is not meaningful to calculate a portfolio diversification benefit

for these measures.

2The total VaR is non-additive across risk types due to diversification effects.

Value at risk

(Audited)

VaR is a technique for estimating potential losses on risk positions as

a result of movements in market rates and prices over a specified

time horizon and to a given level of confidence. The use of VaR is

integrated into market risk management and calculated for all trading

positions regardless of how we capitalise them. Where we do not

calculate VaR explicitly, we use alternative tools as summarised in

the ‘Stress testing’ section below.

Our models are predominantly based on historical simulation that

incorporates the following features:

–historical market rates and prices, which are calculated with

reference to foreign exchange rates, commodity prices, interest

rates, equity prices and the associated volatilities;

–potential market movements that are calculated with reference to

data from the past two years; and

–calculations to a 99% confidence level and using a one-day holding

period.

The models also incorporate the effect of option features on the

underlying exposures. The nature of the VaR models means that an

increase in observed market volatility will lead to an increase in VaR

without any changes in the underlying positions.

VaR model limitations

Although a valuable guide to risk, VaR is used with awareness of its

limitations. For example:

–The use of historical data as a proxy for estimating future market

moves may not encompass all potential market events, particularly

those that are extreme in nature. As the model is calibrated on the

last 500 business days, it does not adjust instantaneously to a

change in the market regime.

–The use of a one-day holding period for risk management

purposes of trading books assumes that this short period is

sufficient to hedge or liquidate all positions.

–The use of a 99% confidence level by definition does not take into

account losses that might occur beyond this level of confidence.

–VaR is calculated on the basis of exposures outstanding at the close of

business and therefore does not reflect intra-day exposures.

Risk not in VaR framework

The risks not in VaR (‘RNIV’) framework captures and capitalises material

market risks that are not adequately covered in the VaR model.

Risk factors are reviewed on a regular basis and are either incorporated

directly into the VaR models, where possible, or quantified through either

the VaR-based RNIV approach or a stress test approach within the RNIV

framework. While VaR-based RNIVs are calculated by using historical

scenarios, stress-type RNIVs are estimated on the basis of stress

scenarios whose severity is calibrated to be in line with the capital

adequacy requirements. The outcome of the VaR-based RNIV approach

is included in the overall VaR calculation but excluded from the VaR

measure used for regulatory back-testing.

Stress-type RNIVs include a deal contingent derivatives capital charge

to capture risk for these transactions and a de-peg risk measure to

capture risk to pegged and heavily-managed currencies.

Stress testing

Stress testing is an important procedure that is integrated into our

market risk management framework to evaluate the potential impact on

portfolio values of more extreme, although plausible, events or

movements in a set of financial variables. In such scenarios, losses can

be much greater than those predicted by VaR modelling. Stress testing

and reverse stress testing provide senior management with insights

regarding the ‘tail risk’ beyond VaR.

Stress testing is implemented at legal entity, regional and overall Group

levels. A set of scenarios is used consistently across all regions within

the Group. Market risk stress testing incorporates both historical and

hypothetical events. Market risk reverse stress tests are designed to

identify vulnerabilities in our portfolios by looking for scenarios that lead

to loss levels considered severe for the relevant portfolio. These

scenarios may be local or idiosyncratic in nature and complement the

systematic top-down stress testing.

The risk appetite around potential stress losses for the Group is set

and monitored against limits.

The Group trading VaR for the year is shown in the table below.

Trading VaR, 99% 1 day1
(Audited)
	Foreign exchange and commodity	Interest rate	Equity	Credit spread	Portfolio diversification2	Total3
	$m	$m	$m	$m	$m	$m
Balance at 31 Dec 2024	14.6	34.9	16.3	8.2	(35.7)	38.3
Average	15.2	48.3	14.8	9.9	(35.1)	53.1
Maximum	29.8	78.1	20.5	13.1		83.3
Minimum	6.9	24.8	12.7	6.6		37.0
Balance at 31 Dec 2023	13.4	55.9	15.2	7.2	(38.9)	52.8
Average	16.2	53.9	19.0	11.6	(40.8)	59.8
Maximum	24.6	86.0	27.8	16.5		98.2
Minimum	9.3	25.5	13.4	6.6		34.4

1Trading portfolios comprise positions arising from the market-making and warehousing of customer-derived positions.

2Portfolio diversification is the market risk dispersion effect of holding a portfolio containing different risk types. It represents the reduction in unsystematic

market risk that occurs when combining a number of different risk types – such as interest rate, equity and foreign exchange – together in one portfolio. It is

measured as the difference between the sum of the VaR by individual risk type and the combined total VaR. A negative number represents the benefit of

portfolio diversification. As the maximum and minimum occurs on different days for different risk types, it is not meaningful to calculate a portfolio diversification

benefit for these measures.

3The total VaR is non-additive across risk types due to diversification effects.

Governance and structure

(Audited)

Insurance manufacturing risks are managed to a defined risk appetite,

which is aligned to the Group’s risk appetite and risk management

framework, including its three lines of defence model. For details of

the Group’s governance framework, see page 145. The Global

Insurance Risk Management Meeting oversees the control

framework globally and is accountable to the WPB Risk Management

Meeting on risk matters relating to the insurance business.

The monitoring of the risks within our insurance operations is carried

out by Insurance Risk teams. The Group’s risk stewardship functions

support the Insurance Risk teams in their respective areas of

expertise.

Stress and scenario testing

(Audited)

Stress testing forms a key part of the risk management framework

for the insurance business. We participate in local and Group-wide

regulatory stress tests, as well as internally developed stress and

scenario tests, including Group internal stress test exercises.

The results of these stress tests and the adequacy of management

action plans to mitigate these risks are considered in the Group’s

ICAAP and the entities’ regulatory Own Risk and Solvency

Assessments, which are produced by all material entities.

Key risk management processes

Market risk

(Audited)

All our insurance manufacturing subsidiaries have market risk

mandates and limits that specify the investment instruments in which

they are permitted to invest and the maximum quantum of market

risk that they may retain. They manage market risk by using some or

all of the techniques listed below, among others, depending on the

nature of the contracts written.

–We are able to adjust bonus rates to manage the liabilities to

policyholders for products with participating features. The effect is

that a significant proportion of the market risk is borne by the

policyholder.

–We use asset and liability matching where asset portfolios are

structured to support projected liability cash flows. The Group

manages its assets using an approach that considers asset quality,

diversification, cash flow matching, liquidity, volatility and target

investment return. We use models to assess the effect of a range

of future scenarios on the values of financial assets and

associated liabilities, and ALCOs employ the outcomes in

determining how best to structure asset holdings to support

liabilities.

–We use derivatives and other financial instruments to protect

against adverse market movements.

–We design new products to mitigate market risk, such as

changing the investment return sharing proportion between

policyholders and the shareholder.

Credit risk

(Audited)

Our insurance manufacturing subsidiaries also have credit risk

mandates and limits within which they are permitted to operate,

which consider the credit risk exposure, quality and performance of

their investment portfolios. Our assessment of the creditworthiness

of issuers and counterparties is based primarily upon internationally

recognised credit ratings and other publicly available information.

Stress testing is performed on investment credit exposures using

credit spread sensitivities and default probabilities.

We use a number of tools to manage and monitor credit risk. These

include a credit report containing a watch-list of investments with

current credit concerns, primarily investments that may be at risk of

future impairment or where high concentrations to counterparties are

present in the investment portfolio. Sensitivities to credit spread risk

are assessed and monitored regularly.

Capital and liquidity risk

(Audited)

Capital risk for our insurance manufacturing subsidiaries is assessed

in the Group’s ICAAP, based on their financial capacity to support the

risks to which they are exposed. Capital adequacy is assessed on

both the Group’s economic capital basis, and the relevant local

insurance regulatory basis.

Risk appetite buffers are set to ensure that the operations are able to

remain solvent, allowing for business-as-usual volatility and extreme

but plausible stress events.

Liquidity risk is less material for the insurance business. It is managed

by cash flow matching and maintaining sufficient cash resources,

investing in high credit-quality investments with deep and liquid

markets, monitoring investment concentrations and restricting them

where appropriate, and establishing committed contingency

borrowing facilities.

Insurance manufacturing subsidiaries complete quarterly liquidity risk

reports and an annual review of the liquidity risks to which they are

exposed.

Insurance underwriting risk

(Audited)

Our insurance manufacturing subsidiaries primarily use the following

frameworks and processes to manage and mitigate insurance

underwriting risks:

–a formal approval process for launching new products or making

changes to products;

–a product pricing and profitability framework, which requires initial

and ongoing assessment of the adequacy of premiums charged

on new insurance contracts to meet the risks associated with

them;

–a framework for customer underwriting;

–reinsurance, which cedes risks to third-party reinsurers to keep

risks within risk appetite, reduce volatility and improve capital

efficiency; and

–oversight by financial reporting committees and actuarial review

committees in each of our entities of the methodology and

assumptions that underpin IFRS 17 reporting.

Measurement

The following tables show the composition of the fair value of underlying items of the Group’s participating contracts at the reporting date.

Balance sheet of insurance manufacturing subsidiaries by type of contract
(Audited)
	Life direct participating and investment DPF contracts1	Life other contracts2	Other contracts3	Shareholder assets and liabilities	Total
At 31 Dec 2024	$m	$m	$m	$m	$m
Financial assets	98,676	4,452	6,227	5,967	115,322
–  trading assets	—	—	—	—	—
–financial assets designated and otherwise mandatorily measured at fair value through profit or loss	94,327	4,233	4,839	690	104,089
–  derivatives	207	7	1	—	215
–  financial investments – at amortised cost	545	90	1,060	4,335	6,030
–  financial assets at fair value through other comprehensive income	—	—	6	73	79
–  other financial assets	3,597	122	321	869	4,909
Insurance contract assets	14	104	—	—	118
Reinsurance contract assets	—	5,013	—	—	5,013
Other assets and investment properties4	24,647	64	36	3,337	28,084
Total assets at 31 Dec 2024	123,337	9,633	6,263	9,304	148,537
Liabilities under investment contracts designated at fair value	—	—	5,931	—	5,931
Insurance contract liabilities	102,605	4,427	—	—	107,032
Reinsurance contract liabilities	—	701	—	—	701
Deferred tax	—	—	—	12	12
Other liabilities4	21,772	39	—	6,035	27,846
Total liabilities	124,377	5,167	5,931	6,047	141,522
Total equity	—	—	—	7,015	7,015
Total liabilities and equity at 31 Dec 2024	124,377	5,167	5,931	13,062	148,537

Balance sheet of insurance manufacturing subsidiaries by type of contract
(Audited)
	Life direct participating and investment DPF contracts1	Life other contracts2	Other contracts3	Shareholder assets and liabilities	Total
At 31 Dec 2023	$m	$m	$m	$m	$m
Financial assets	113,605	3,753	5,812	7,696	130,866
–  trading assets	—	—	—	—	—
–  financial assets designated and otherwise mandatorily measured at fair value through profit or loss	100,427	3,593	4,177	1,166	109,363
–  derivatives	258	10	—	6	274
–  financial investments – at amortised cost	1,351	67	1,157	4,772	7,347
–  financial assets at fair value through other comprehensive income	8,859	—	5	693	9,557
–  other financial assets	2,710	83	473	1,059	4,325
Insurance contract assets	13	213	—	—	226
Reinsurance contract assets	—	4,871	—	—	4,871
Other assets and investment properties	2,782	164	35	1,636	4,617
Total assets at 31 Dec 2023	116,400	9,001	5,847	9,332	140,580
Liabilities under investment contracts designated at fair value	—	—	5,103	—	5,103
Insurance contract liabilities	116,389	3,961	—	—	120,350
Reinsurance contract liabilities	—	819	—	—	819
Deferred tax	—	1	—	3	4
Other liabilities	—	—	—	6,573	6,573
Total liabilities	116,389	4,781	5,103	6,576	132,849
Total equity	—	—	—	7,731	7,731
Total liabilities and equity at 31 Dec 2023	116,389	4,781	5,103	14,307	140,580

1‘Life direct participating and investment DPF contracts’ are life direct participating contracts and investment contracts with discretionary participating features.

These are substantially measured under the variable fee approach measurement model.

2‘Life other contracts’ are measured under the general measurement model and mainly include protection insurance contracts as well as reinsurance contracts.

The reinsurance contracts primarily provide diversification benefits over the life direct participating and investment DPF contracts.

3‘Other contracts’ includes investment contracts for which HSBC does not bear significant insurance risk.

4’Other assets and investment properties’ includes $24,222m and ’Other liabilities’ includes $23,420m in respect of the classification of the French insurance

business assets and liabilities as held for sale at 31 December 2024. Further details are provided on page 433.

Market risk

(Audited)

Description and exposure

Market risk is the risk of changes in market factors affecting HSBC’s

capital or profit. Market factors include interest rates, equity and growth

assets, credit spreads and foreign exchange rates.

Our exposure varies depending on the type of contract issued. Our most

significant life insurance products are contracts with participating

features. These products typically include some form of capital guarantee

or guaranteed return on the sums invested by the policyholders, to which

bonuses are added if allowed by the overall performance of the funds. For

contracts without participating features, some form of guarantee may still

exist but HSBC’s ability to share risks with policyholders will be reduced. 

Funds supporting these savings products are primarily invested in fixed

income, with a proportion in some cases allocated to other asset classes

to provide customers with the potential for enhanced returns.

These products expose HSBC to the risk of variation in asset returns,

which will impact our participation in the investment performance.

In addition, in some scenarios the asset returns can become insufficient

to cover the policyholders’ financial guarantees, and some contracts are

non-participating, in which case the shortfall has to be met by HSBC.

Amounts are held against the cost of such positions, calculated by

stochastic modelling in the larger entities.

The cost of such guarantees are generally not material and are absorbed

by the insurance fulfilment cash flows.

For unit-linked contracts, market risk is substantially borne by the

policyholder, but some market risk exposure typically remains, as fees

earned are related to the market value of the linked assets.

Sensitivities

The following table provides the impacts on the CSM, profit after tax and

equity of our insurance manufacturing subsidiaries from reasonably

possible effects of changes in selected interest rate, credit spread, equity

price, growth assets and foreign exchange rate scenarios for the year.

These sensitivities are prepared in accordance with current IFRS

Accounting Standards and are based on changing one assumption at a

time with other variables being held constant, recognising that in practice

such variables could be correlated.

Due in part to the impact of the cost of guarantees and hedging strategies

which may be in place, the relationship between the CSM, profit after tax

and total equity and the risk factors is non-linear. Therefore, the results

disclosed should not be extrapolated to measure sensitivities to different

levels of stress. For the same reason, the impact of the stress is not

necessarily symmetrical on the upside and downside. The sensitivities

are stated before allowance for management actions, which may mitigate

the effect of changes in the market environment.

The method used for deriving sensitivity information and significant

market risk factors remain unchanged except for updates made to the

foreign exchange rate risk methodology, which now limits the impacts to

within more recent historical ranges. 2023 comparative sensitivities have

been updated to reflect this change.

The sensitivities provided below include the French insurance

business, which was classified as held for sale at 31 December 2024.

Further details are provided on page 433.

Sensitivity of HSBC’s insurance manufacturing subsidiaries to market risk factors
(Audited)
	2024			2023
	Effect on CSM	Effect on profit after tax1	Effect on total equity	Effect on CSM	Effect on profit after tax1	Effect on total equity
	$m	$m	$m	$m	$m	$m
+100 basis point parallel shift in yield curves	(155)	83	52	(92)	66	32
-100 basis point parallel shift in yield curves	(249)	(217)	(186)	(390)	(137)	(103)
+100 basis point shift in credit spreads	(907)	(84)	(115)	(884)	(11)	(45)
-100 basis point shift in credit spreads	876	60	91	806	104	138
10% increase in growth assets2	467	73	73	436	78	78
10% decrease in growth assets2	(514)	(79)	(79)	(507)	(85)	(85)
10% appreciation in US dollar exchange rate against local functional currency3	71	17	17	24	(1)	(1)
10% depreciation in US dollar exchange rate against local functional currency3	(26)	(3)	(3)	(35)	(3)	(3)

1‘Effect on profit after tax‘ in respect for the year.

2‘Growth assets’ primarily comprise equity securities and investment properties. Variability in growth asset fair value constitutes a market risk to insurance

manufacturing subsidiaries.

3During the year 10% US dollar exchange rate methodology changed and the 10% sensitivity range applies to all currencies except for the Hong Kong dollar,

where the extent of change is limited by the impact of the HKD to USD peg. The comparatives have been restated accordingly.

Credit risk

(Audited)

Description and exposure

Credit risk is the risk of financial loss if a customer or counterparty

fails to meet their obligation under a contract. It arises in two main

risks for our insurance manufacturers:

–the risk associated with credit spread volatility and default by debt

security counterparties after investing premiums to generate a

return for policyholders and shareholders; and

–the risk of default by reinsurance counterparties and non-

reimbursement for claims made after ceding insurance risk.

The amounts outstanding at the balance sheet date in respect

of these items are shown in the table on page 262.

The credit quality of the reinsurers’ share of liabilities under insurance

contracts is assessed as ‘satisfactory’ or higher (as defined on

page 170), with none of the exposure being either past due or

impaired (2023: none).

Credit risk on assets supporting unit-linked liabilities is predominantly

borne by the policyholders. Therefore, our exposure is primarily

related to liabilities under non-linked insurance and investment

contracts and shareholders’ funds. The credit quality of insurance

financial assets is included in the table on page 196.

The risk associated with credit spread volatility is to a large extent

mitigated by holding debt securities to maturity, and sharing a degree

of credit spread experience with policyholders.

Liquidity risk

(Audited)

Description and exposure

Liquidity risk is the risk that an insurance operation, though solvent,

either does not have sufficient financial resources available to meet

its obligations when they fall due, or can secure them only at

excessive cost. Liquidity risk may be able to be shared with

policyholders for products with participating features.

The remaining maturity of insurance contract liabilities is included in

Note 4 on page 395.

The amounts of insurance contract liabilities that are payable on demand are set out by the product grouping below; 2024 balances exclude the

French insurance business that was classified as held for sale at 31 December 2024 (further details are provided on page 433).

Amounts payable on demand
(Audited)
	2024		2023
	Amounts payable on demand	Carrying amount for these contracts	Amounts payable on demand	Carrying amount for these contracts
	$m	$m	$m	$m
Life direct participating and investment DPF contracts	98,275	102,605	107,287	116,389
Life other contracts	2,960	4,427	2,765	3,961
At 31 Dec	101,235	107,032	110,052	120,350

Sensitivities

(Audited)

The following table shows the sensitivity of the CSM, profit and total

equity to reasonably foreseeable changes in non-economic

assumptions across all our insurance manufacturing subsidiaries.

These sensitivities are prepared in accordance with current IFRS.

Sensitivity to lapse rates depends on the type of contracts

being written. An increase in lapse rates typically has a negative

effect on CSM (and therefore expected future profits) due to the loss

of future income on the lapsed policies. However, some contract

lapses have a positive effect on profit due to the existence of policy

surrender charges.

Mortality and morbidity risk is typically associated with life insurance

contracts. During the year we have revised the sensitivity to mortality

and morbidity rates from 10% to 5% to align with reasonably

foreseeable changes, and the comparatives have been restated

accordingly. The effect on profit of an increase in mortality or

morbidity depends on the type of business being written.

Expense rate risk is the exposure to a change in the allocated cost

of administering insurance contracts. To the extent that increased

expenses cannot be passed on to policyholders, an increase in

expense rates will have a negative effect on our profits. This risk is

generally greatest for our smaller entities.

The impact of changing insurance underwriting risk factors is primarily

absorbed within the CSM, unless contracts are onerous in which case

the impact is directly to profit. The impact of changes to the CSM is

released to profits over the expected coverage periods of the related

insurance contracts.

The sensitivities provided below include the French insurance

business, which was classified as held for sale at 31 December 2024.

Further details are provided on page 433.

Sensitivity of HSBC’s insurance manufacturing subsidiaries to insurance underwriting risk factors1
(Audited)
	Effect on CSM	Effect on profit after tax2	Effect on total equity
At 31 Dec 2024	$m	$m	$m
10% increase in lapse rates	(282)	(21)	(30)
10% decrease in lapse rates	297	23	36
5% increase in mortality and/or morbidity rates	(92)	(16)	(20)
5% decrease in mortality and/or morbidity rates	102	14	23
10% increase in expense rates	(66)	(11)	(15)
10% decrease in expense rates	68	12	15
At 31 Dec 2023
10% increase in lapse rates	(277)	(24)	(24)
10% decrease in lapse rates	290	29	29
5% increase in mortality and/or morbidity rates3	(87)	(11)	(11)
5% decrease in mortality and/or morbidity rates3	87	16	16
10% increase in expense rates	(68)	(6)	(6)
10% decrease in expense rates	67	11	11

1The sensitivities impacts are provided after considering the impacts of reinsurance contracts held as risk mitigation.

2‘Effect on profit after tax‘ in respect for the year.

3During the year the sensitivity to mortality and morbidity rates have been changed from 10% to 5% and the comparatives have been restated accordingly.