Risk management	6 Months Ended
Jun. 30, 2022
Risk management [abstract]
Risk management	Credit risk Portfolio quality and concentration Our lending portfolio is diversified over various sectors and countries. The total gross carrying amounts is composed of approximately 65 % business lending and 35 % consumer lending. For a detailed breakdown of ING’s credit risk portfolio by Sector and Geographical area, refer to the section “Credit Risk portfolio” reported in the ‘Risk management’ section of the 2021 Annual Report. ING’s total gross carrying amounts increased compared to year-end 2021 due to higher customer lending and cash and balances with central banks. Loan loss provisioning () ING recognises loss allowances based on the expected credit loss (ECL) model of IFRS 9, which is designed to be forward-looking. The IFRS 9 impairment requirements are applicable to on-balance sheet financial assets measured at amortised cost or fair value through other comprehensive income (FVOCI), such as loans, debt securities and lease receivables, as well as off-balance sheet items such as undrawn loan commitments, certain financial guarantees issued, and undrawn committed re volving credit facilities. The table below describes the portfolio composition over the different IFRS 9 stages and rating classes. The Stage 1 portfolio represents 93.4 % (2021: 93.5 %) of the total gross carrying amounts, mainly composed of investment grade, while Stage 2 makes up 5.4 % (2021: 5.2 %) and Stage 3 makes up 1.2 % (2021: 1.3 %) total gross carrying amounts, respectively. Gross carrying amount per IFRS 9 stage and rating class () 1 in EUR million 12-month ECL (Stage 1) Lifetime ECL not credit impaired (Stage 2) Lifetime ECL credit impaired (Stage 3) Total 30 June 2022 Rating class Gross Carrying Amount Provisions Gross Carrying Amount Provisions Gross Carrying Amount Provisions Gross Carrying Amount Provisions Investment grade 1 (AAA) 116,616 1 0 0 116,616 1 2-4 (AA) 112,044 3 259 0 112,303 3 5-7 (A) 170,785 13 1,402 1 172,187 14 8-10 (BBB) 336,871 62 9,745 21 346,616 83 Non-Investment grade 11-13 (BB) 164,326 231 13,745 82 178,071 314 14-16 (B) 27,239 180 16,083 367 43,322 548 17 (CCC) 6,267 7 4,391 213 10,658 220 Substandard grade 18 (CC) 5,654 780 5,654 780 19 (C) 2,710 420 2,710 420 Non-performing loans 20-22 (D) 11,831 3,640 11,831 3,640 Total 934,148 497 53,989 1,885 11,831 3,640 999,968 6,022 1 IAS 37 provisions are established for non-credit replacement guarantees not in the scope of IFRS 9. Total IAS 37 provisions (€ 117 million) are excluded. Gross carrying amount per IFRS 9 stage and rating class () 1 in EUR million 12-month ECL (Stage 1) Lifetime ECL not credit impaired (Stage 2) Lifetime ECL credit impaired (Stage 3) Total 31 December 2021 Rating class Gross Carrying Amount Provisions Gross Carrying Amount Provisions Gross Carrying Amount Provisions Gross Carrying Amount Provisions Investment grade 1 (AAA) 107,788 3 0 107,788 3 2-4 (AA) 106,673 5 197 106,870 5 5-7 (A) 152,167 17 1,000 1 153,167 17 8-10 (BBB) 328,302 73 7,232 14 335,533 87 Non-Investment grade 11-13 (BB) 163,228 208 14,679 86 177,908 294 14-16 (B) 26,852 185 17,931 404 44,783 589 17 (CCC) 5,377 10 4,354 198 9,730 207 Substandard grade 18 (CC) 2,314 173 2,314 173 19 (C) 1,769 142 1,769 142 Non-performing loans 20-22 (D) 12,072 3,851 12,072 3,851 Total 890,387 501 49,476 1,016 12,072 3,851 951,934 5,368 1 IAS 37 provisions are established for non-credit replacement guarantees not in the scope of IFRS 9. Total IAS 37 provisions (€ 114.4 million) are excluded. Changes in gross carrying amounts and loan loss provisions () The table below provides a reconciliation by stage of the gross carrying amount and allowances for loans and advances to banks and customers, including loan commitments and financial guarantees. The transfers of financial instruments represent the impact of stage transfers upon the gross carrying/nominal amount and associated allowance for ECL. This includes the net-remeasurement of ECL arising from stage transfers, for example, moving from a 12-month (Stage 1) to a lifetime (Stage 2) ECL measurement basis. The net- remeasurement line represents the changes in provisions for facilities that remain in the same stage. Please note the following comments with respect to the movements observed in the table below: ◾ Stage 3 gross carrying amount decreased by € 0.2 billion from € 12.1 billion as per 31 December 2021 mainly as a result of write-offs and generally low inflow into NPL in the first half of 2022; ◾ Stage 2 gross carrying amount increased by € 4.5 billion from € 49.5 billion as per 31 December 2021. This is mainly caused by the Significant Lifetime PD trigger (€ 6.4 billion) driven by downgrades of the Russian portfolio and to a lesser extent the 30 Days past due trigger (€ 1.9 bn), offset by decreases in other triggers mainly the Forbearance (-/-€ 4.0 billion) trigger. For the latter, a 2-year probation period is required before a client can move back to Stage 1 and the decrease relates to the fact that the start of the COVID pandemic is now more than 2 years ago; ◾ In the first half year of 2022, the largest increases in Stage 2 were in Natural Resources, Non-Bank Financial Institutions and Telecom of € 3.9 billion, € 0.9 billion and € 0.6 billion respectively, materially impacted by the Russian portfolio. Largest decreases were in Automotive and Utilities with € 0.7 bn release each. The largest Stage 2 outstandings per economic sector as per 30 June 2022 are Natural Resources, Transportation & Logistics, Real Estate and Services representing 13 %, 9 %, 8 % and 8 % of the total Stage 2 gross carrying amounts respectively. Additional information on macroeconomic scenarios is included in the section ‘Macro-economic scenarios and sensitivity analysis of key sources of estimation uncertainty’. Changes in gross carrying amounts and loan loss provisions () 1, 2 in EUR million 12-month ECL (Stage 1) Lifetime ECL not credit impaired (Stage 2) Lifetime ECL credit impaired (Stage 3) Total 30 June 2022 Gross carrying amount Provisions Gross carrying amount Provisions Gross carrying amount Provisions Gross carrying amount Provisions Opening balance 890,386 501 49,476 1,016 12,072 3,851 951,934 5,368 Transfer into 12-month ECL (Stage 1) 8,534 13 -8,259 -115 -275 -28 -0 -130 Transfer into lifetime ECL not credit impaired (Stage 2) -17,556 -53 18,174 720 -618 -71 -0 596 Transfer into lifetime ECL credit impaired (Stage 3) -1,451 -9 -851 -53 2,302 611 0 549 Net remeasurement of loan loss provisions -39 301 4 266 New financial assets originated or purchased 119,993 123 119,993 123 Financial assets that have been derecognised -75,384 -34 -5,313 -49 -2,080 -137 -82,777 -220 Net drawdowns and repayments 9,625 761 431 10,818 Changes in models/risk parameters Increase in loan loss provisions 1 804 379 1,184 Write-offs -648 -648 Recoveries of amounts previously written off 28 28 Foreign exchange and other movements -5 65 30 90 Closing balance 934,148 497 53,989 1,885 11,831 3,640 999,968 6,022 1 Stage 3 Lifetime credit impaired provision includes € 5 million on Purchased or Originated Credit Impaired. 2 The addition to the loan provision (in the consolidated statement of profit or loss) amounts to € 1,189 million of which € 1,184 million related to IFRS-9 eligible financial assets, € 4 million related to non-credit replacement guarantees and € 1 million to modification gains and losses on restructured financial assets. Changes in gross carrying amounts and loan loss provisions () 1, 2 in EUR million 12-month ECL (Stage 1) Lifetime ECL not credit impaired (Stage 2) Lifetime ECL credit impaired (Stage 3) Total 31 December 2021 Gross carrying amount Provisions Gross carrying amount Provisions Gross carrying amount Provisions Gross carrying amount Provisions Opening balance 844,231 581 59,313 1,476 13,398 3,797 916,942 5,854 Transfer into 12-month ECL (Stage 1) 15,157 20 -14,322 -279 -835 -54 -0 -313 Transfer into lifetime ECL not credit impaired (Stage 2) -19,737 -32 20,537 206 -800 -75 -0 100 Transfer into lifetime ECL credit impaired (Stage 3) -2,166 -13 -1,589 -96 3,755 820 -0 712 Net remeasurement of loan loss provisions -130 -228 404 46 New financial assets originated or purchased 208,501 149 208,501 149 Financial assets that have been derecognised -125,819 -73 -11,935 -104 -1,898 -237 -139,652 -414 Net drawdowns and repayments -29,781 -2,527 -694 -33,002 Changes in models/risk parameters 12 41 130 184 Increase in loan loss provisions -67 -460 989 462 Write-offs -854 -854 -854 -854 Recoveries of amounts previously written off 45 45 Foreign exchange and other movements -13 1 -125 -138 Closing balance 890,386 501 49,476 1,016 12,072 3,851 951,934 5,368 1 Stage 3 Lifetime credit impaired provision includes € 4 million on Purchased or Originated Credit Impaired. 2 The addition to the loan provision (in the condensed consolidated statement of profit or loss) amounts to € 516 million of which € 462 million related to IFRS-9 eligible financial assets, € 43 million related to non-credit replacement guarantees and € 11 million to modification gains and losses on restructured financial assets. Macroeconomic scenarios and sensitivity analysis of key sources of estimation uncertainty () Methodology () Our methodology in relation to the adoption and generation of macroeconomic scenarios is described in this section. We continue to follow this methodology in generating our probability-weighted ECL, with consideration of alternative scenarios and management adjustments supplementing this ECL where, in management's opinion, the consensus forecast does not fully capture the extent of recent credit or economic events. The macroeconomic scenarios are applicable to the whole ING portfolio in the scope of IFRS 9 ECLs. The IFRS 9 standard, with its inherent complexities and potential impact on the carrying amounts of our assets and liabilities, represents a key source of estimation uncertainty. In particular, ING’s reportable ECL numbers are most sensitive to the forward-looking macroeconomic forecasts used as model inputs, the probability-weights applied to each of the three scenarios, and the criteria for identifying a significant increase in credit risk. As such, these crucial components require consultation and management judgement, and are subject to extensive governance. Baseline scenario () As a baseline for IFRS 9, ING has adopted a market-neutral view combining consensus forecasts for economic variables (GDP, unemployment) with market forwards (for interest rates, exchange rates and oil prices). The Oxford Economics’ Global Economic Model (OEGEM) is used to complement the consensus with consistent projections for variables for which there are no consensus estimates available (most notably house prices and – for some countries - unemployment), to generate alternative scenarios, to convert annual consensus information to a quarterly frequency and to ensure general consistency of the scenarios. The relevance and selection of macroeconomic variables is defined by the ECL models under credit risk model governance. The scenarios are reviewed and challenged by two panels. The first panel consists of economic experts from Global Markets Research and risk and modelling specialists, while the second panel consists of relevant senior managers. Alternative scenarios and probability weights () Two alternative scenarios are taken into account; an upside and a downside scenario. The alternative scenarios have technical characteristics as they are based on the forecast errors of the OEGEM. To understand the baseline level of uncertainty around any forecast, Oxford Economics keeps track of all its forecast errors of the past 20 years. The distribution of forecast errors for GDP, unemployment, house prices and share prices is applied to the baseline forecast creating a broad range of alternative outcomes. In addition, to understand the balance of risks facing the economy in an unbiased way, Oxford Economics runs a survey with respondents from around the world and across a broad range of industries. In this survey the respondents put forward their views of key risks. Following the survey results, the distribution of forecast errors (that is being used for determining the scenarios) may be skewed. For the downside scenario, ING has chosen for the 90th percentile of that distribution because this corresponds with the way risk management earnings-at-risk is defined within the Group. The upside scenario is represented by the 10th percentile of the distribution. The applicable percentiles of the distribution imply a 20% probability for each alternative scenario. Consequently, the baseline scenario has a 60% probability weighting. Please note that, given their technical nature, the downside and upside scenarios are not based on an explicit specific narrative. Macroeconomic scenarios applied () The loan loss provisions are based on the June 2022 consensus forecasts. Baseline assumptions () The general picture that the consensus conveys is that higher inflation will be more persistent but still to be transitory and, in combination with an overall tightening of monetary conditions, fall back towards most central bank’s targets over the course of the forecast horizon. The baseline assumes that the Russia-Ukraine war will not spread beyond Ukraine but that the war drags on with risks to the energy outlook. Against a background of slowing economic (and hence disposable income) growth, increasing unemployment, higher interest rates and, for some markets, high valuations house prices growth is expected to level off to low single digit rates or price declines. The June 2022 consensus expects global output growth (ING definition), after a strong rebound in 2021 of 5.9 %, to slow to 2.7 % in 2022 and to level off further to an at or around 2.5 % growth rate in the years thereafter. When compared to the December 2021 consensus forecast, used for the 2021 Annual Report, the June 2022 forecast assumes a less strong economic environment. Global GDP is expected to increase by 2.7 % in 2022 (compared to 4.1 % assumed before) and 2.5 % in 2023 ( 3.1 % assumed before). This downward adjustment reflects the repercussions from the Russia-Ukraine war and the surge in commodity and oil prices squeezing household incomes and pushing up interest rates. Although to various degrees, these developments all weigh on the economic outlook of the various countries. Tightening of monetary conditions is seen to be swifter in the US than in the eurozone while the European economies are more directly exposed to the Russia-Ukraine war. Alternative scenarios and risks () Because of the possible consequences of the Russia-Ukraine war, uncertainty surrounding the forecasts is assessed as being larger than usual. This reflects uncertainty about European energy supply and worries about more persistent high inflation. To reflect the general increase of uncertainty surrounding the forecasts, the dispersion of the alternative scenarios was used in Q2 2022 at the same widened level as used in Q4 2021 provisioning (half-widened dispersion). The downward skew following on from the outcomes of Oxford Economics’ Global Risk Survey has been maintained and is more negative compared to what has been assumed for Q4 2021. The downside scenario – though technical in nature – sees, for most countries, a fast deceleration of economic growth followed by a recession. Unemployment increases strongly in this scenario and house prices in most countries show outright falls. The downside scenario captures a possible escalation of the Russia-Ukraine war and a more pronounced and prolonged surge in inflation (cut off from Russian gas supplies). The upside scenario – while equally technical in nature – reflects the possibility of a better economic outturn in case the Russia-Ukraine war would end quickly and a quicker fading of coronavirus and other concerns leading to a consumer-led recovery in advanced economies as consumers spend (some of) their savings accumulated at the height of the corona crisis. Management adjustments applied this year () In times of volatility and uncertainty where portfolio quality and the economic environment are changing rapidly, models alone may not be able to accurately predict losses. In these cases, management adjustments can be applied to appropriately reflect ECL. Management adjustments can also be applied where the impact of the updated macroeconomic scenarios is over- or under-estimated by the IFRS 9 models. ING has internal governance frameworks and controls in place to assess the appropriateness of all management adjustments. Management adjustments to ECL models () in EUR million 30 June 2022 31 December 2021 Economic sector based adjustments 68 341 Second order impact adjustments 268 0 Payment holiday adjustments 0 32 Mortgage portfolio adjustments 131 124 Other Post Model Adjustments 1 25 121 Total management adjustments 492 618 1 Prior period figure has been updated to conform to current year presentation December 2021 management adjustments included an economic sector-based management adjustment of € 341 million because of delays in defaults occurring in the Covid-19 related crisis, mainly as a result of government support programmes. In determining the sector-based management adjustment, a heatmap approach was used to adjust the probability of default for sectors where businesses are significantly impacted by the pandemic. In the first half year of 2022, as it became clearer the Covid-19 had less than expected impact on the number of defaults, the economic sector-based management adjustment has been partly released and partly been converted to second order impact adjustment (see below). The remaining € 68 million relates to business banking clients that have benefitted from government support programmes in the Netherlands such as deferral of tax payments that will end in the second half of 2022. ING performed an assessment for both wholesale banking and retail banking on the impact of the developing situation in Ukraine, the increase in energy prices and other macro-economic developments such as increase of inflation and rising interest rates. As the credit risk models assume that these effects materialize via other risk drivers such as GDP and unemployment rates with an delay, an overlay approach was determined to timely estimate the Expected Credit Losses for private individuals. As at 30 June 2022 the second order impact overlay for Retail countries amounts to € 40 m. In Wholesale banking it was assessed that the economic effects of Covid-19 is not the biggest risk anymore and that other risks have emerged – mainly high energy prices, high interest rates and inflation, supply chain issues and staffing shortages. A heatmap approach was used to adjust the probability of default for clients that are expected to be significantly impacted by these emerged risks. As at 30 June 2022 the second order impact overlay for Wholesale banking amounts to € 228 m. As payment holiday programs generally have expired, this Covid-19 related management adjustment has been fully released. ECL of mortgage portfolios determined by the models continued to decrease rapidly during 2021 and decreased further in the first half of 2022, driven by significant increase of house prices in various countries. Management adjustments of € 131 million in total, mainly in stage 2 and 3, have been recognised in ING Netherlands, Belgium, Germany and Australia to maintain an appropriate level of ECL and reflecting a potential impact of higher inflation and interest rates on clients’ ability to pay and a potential impact of market uncertainty on the recovery value of residential real estate. The management adjustment for the Netherlands mortgage portfolio was determined by developing three alternative macroeconomic forecast scenarios, in addition to the consensus base, up- and down-scenarios, that reflect a correction in the house prices in the next 3 years bringing it back in line with the historical growth rate. For other countries, management adjustments were determined by calculating the impact of lower house prices on LTVs and LGDs. Other Post Model Adjustments mainly relate to the impact of model redevelopment or recalibration and periodic model assessment procedures that have not been incorporated in the ECL models yet. These result from both regular model maintenance and ING’s multiyear program to update ECL models for the new definition of default. These adjustments will be removed once updates to the models have been implemented . Analysis on sensitivity () The table below presents the analysis on the sensitivity of key forward-looking macroeconomic inputs used in the ECL collective-assessment modelling process and the probability-weights applied to each of the three scenarios. The countries included in the analysis are the most significant geographic regions, in terms of both gross contribution to reportable ECL, and sensitivity of ECL to forward -looking macroeconomics. Accordingly, ING considers these portfolios to present the most significant risk of resulting in a material adjustment to the carrying amount of financial assets within the next financial year. ING also observes that, in general, the Wholesale Banking business is more sensitive to the impact of forward-looking macroeconomic scenarios. The purpose of the sensitivity analysis is to enable the reader to understand the extent of the impact from the upside and downside scenario on model-based reportable ECL. The table does not include any management adjustments. In the table below the Real GDP is presented in percentage year-on-year change, the unemployment in percentage of total labour force and the house price index (HPI) in percentage year-on year change. Sensitivity analysis as at June 2022 () 2022 2023 2024 Un-weighted ECL (Eur mln) Probability- weighting Reportable ECL (Eur mln) 1 Netherlands Upside scenario Real GDP 3.6 2.5 3.0 297 20% 361 Unemployment 3.7 3.7 3.5 HPI 17.6 15.7 4.1 Baseline Scenario Real GDP 2.8 1.3 1.8 337 60% Unemployment 4.1 4.5 4.7 HPI 14.8 2.7 1.9 Downside scenario Real GDP 0.3 -1.4 0.8 494 20% Unemployment 5.8 6.9 8.0 HPI 11.1 -13.4 -0.9 Germany Upside scenario Real GDP 2.8 3.6 2.3 642 20% 787 Unemployment 2.7 2.6 2.2 HPI 11.7 6.3 4.8 Baseline Scenario Real GDP 1.8 2.1 1.8 772 60% Unemployment 3.1 3.2 3.3 HPI 10.8 3.3 1.4 Downside scenario Real GDP -0.3 -1.2 0.6 977 20% Unemployment 4.6 5.3 5.8 HPI 9.0 -2.1 -2.3 Belgium Upside scenario Real GDP 3.1 3.0 2.2 546 20% 608 Unemployment 5.2 5.1 5.2 HPI 4.8 3.0 2.5 Baseline Scenario Real GDP 2.4 1.8 1.8 596 60% Unemployment 5.7 5.7 5.8 HPI 4.4 2.3 2.0 Downside scenario Real GDP 0.8 -0.3 1.3 705 20% Unemployment 6.9 7.7 8.2 HPI 3.2 0.3 0.7 United States Upside scenario Real GDP 3.9 2.5 2.4 68 20% 156 Unemployment 3.6 3.3 2.8 HPI 10.1 4.4 8.1 Baseline Scenario Real GDP 2.4 1.5 1.7 124 60% Unemployment 3.9 4.2 4.2 HPI 9.8 1.2 2.3 Downside scenario Real GDP 0.2 -1.6 0.1 342 20% Unemployment 6.0 7.2 8.3 HPI 8.7 -4.3 -4.1 1 Excluding management adjustments. Sensitivity analysis as at December 2021 () 2022 2023 2024 Un-weighted ECL (Eur mln) Probability- weighting Reportable ECL (Eur mln) 1 Netherlands Upside scenario Real GDP 5.1 2.9 2.7 259 20% 307 Unemployment 3.2 2.9 2.9 HPI 23.3 10.9 0.9 Baseline Scenario Real GDP 3.4 2.0 1.7 289 60% Unemployment 3.7 4.1 4.3 HPI 13.1 2.8 0.8 Downside scenario Real GDP -1.5 1.2 0.7 411 20% Unemployment 5.6 6.8 7.8 HPI 0.3 -7.7 0.6 Germany Upside scenario Real GDP 6.2 3.1 1.6 457 20% 483 Unemployment 2.9 2.2 1.9 HPI 12.9 7.9 5.3 Baseline Scenario Real GDP 4.0 2.3 1.4 475 60% Unemployment 3.4 3.1 3.1 HPI 10.4 4.6 1.9 Downside scenario Real GDP -0.6 0.9 0.8 535 20% Unemployment 5.0 5.4 5.7 HPI 5.3 0.4 -2.1 Belgium Upside scenario Real GDP 4.6 2.5 2.0 364 20% 393 Unemployment 5.6 5.6 5.9 HPI 3.9 2.7 2.9 Baseline Scenario Real GDP 3.1 2.0 1.8 383 60% Unemployment 6.1 6.3 6.3 HPI 3.0 2.3 2.3 Downside scenario Real GDP -0.4 1.4 1.4 451 20% Unemployment 7.6 8.6 9.0 HPI 0.4 1.0 1.0 United States Upside scenario Real GDP 6.7 2.4 3.1 28 20% 75 Unemployment 3.5 2.5 2.4 HPI 10.4 8.1 8.7 Baseline Scenario Real GDP 4.0 2.5 2.1 55 60% Unemployment 4.0 3.7 3.7 HPI 9.1 3.0 3.3 Downside scenario Real GDP -0.7 1.1 0.3 183 20% Unemployment 6.5 7.4 8.0 HPI 5.3 -3.2 -3.0 1 Excluding management adjustments. When compared to the sensitivity analysis of 2021, the macroeconomic inputs for 2022 and 2023 are less favourable, driven by worsened macro-economic outlook as a result of the war in Ukraine as well as its indirect effects such as inflation and increasing interest rates. Both 2021 and 2022 contain half widened dispersion around upside and downside scenarios, for 2021 reflecting continuing but decreased short term uncertainty related to the impact of Covid-19 and for 2022 reflecting short term uncertainty around the war in Ukraine and its indirect effects. The increase in reportable ECL compared to 2021 is mainly caused by higher model ECL amounts as per June 2022 as a result of increased provisions for Russia related exposures in Stage 2. While the table above does give a high-level indication of the sensitivity of the outputs to the different scenarios, it does not provide insight into the interdependencies and correlations between different macroeconomic variable inputs. On total ING level, the unweighted ECL for all collective provisioned clients in the upside scenario was € 2,754 million, in the baseline scenario € 3,181 million and in the downside scenario € 4,305 million compared to € 3,337 million reportable collective provisions as per 30 June 2022 (excluding all management adjustments). This reconciles as follows to the reported ECL’s: Reconciliation of model (reportable) ECL to total ECL () in EUR million 30 June 2022 31 December 2021 Total model ECL 1 3,337 2,408 ECL from individually assessed impairments 2,193 2,342 ECL from management adjustments 1 492 618 Total ECL 6,022 5,368 1 Prior period figure has been updated to conform to current year presentation Criteria for identifying a significant increase in credit risk (SICR) () For the methodology and our approaches on absolute lifetime PD threshold and relative lifetime PD threshold, please refer to the “Risk management” section in the Annual Report ING Group for the year ended December 31, 2021. In the table below the average increase in PD at origination needed to be classified in Stage 2 is reported, taking into account the PD at origination of the facilities included in each combination of asset class and rating quality. In terms of rating quality, assets are divided into “Investment grade” and “Non-investment grade” facilities. Rating 18 and 19 are not included in the table since facilities are not originated in these ratings and they constitute a staging trigger of their own (i.e. if a facility is ever to reach rating 18 or 19 at reporting date, it is classified in Stage 2). In the table below values are weighted by IFRS 9 exposure and shown for both year-end 2021 and June 2022. In order to represent the thresholds as a ratio (i.e. how much should the PD at origination increase in relative terms to trigger Stage 2 classification) the absolute threshold is recalculated as a relative threshold for disclosure purposes. Since breaching only relative or absolute threshold triggers Stage 2 classification, the minimum between the relative and recalculated absolute threshold is taken as value of reference for each facility. Quantitative SICR thresholds () 30 June 2022 31 December 2021 Average threshold ratio Investment grade (rating grade 1-10) Non- investment grade (rating grade 11-17) Investment grade (rating grade 1-10) Non- investment grade (rating grade 11-17) Asset class category Mortgages 2.7 2.3 2.7 2.2 Consumer Lending 3.4 1.8 2.8 1.7 Business Lending 3.4 2.2 4.0 2.2 Governments and Fin. Institutions 7.7 2.2 7.9 2.2 Other Wholesale Banking 4.3 1.9 4.5 2.0 As it is apparent from the disclosures above, as per ING’s methodology, the threshold is tighter the higher the riskiness at origination of the assets, and confirmed by the noticeable difference between the average threshold applied to investment grade facilities and non-investment grade facilities. In addition to the above, asset classes having usually more favourable ratings at origination (i.e. Governments and Financial Institutions) show an average threshold higher than the rest in investment grade assets. Changes in the threshold averages between the two reporting dates are caused by model updates (the staging parameters have been recalibrated) and/ or by changes in portfolio composition. Sensitivity of ECL to PD lifetime PD thresholds The setting of PD threshold bandings requires management judgement and is a key source of estimation uncertainty. On Group level, the total ECL collective-assessment for performing assets is € 1,849 million (2021: € 1,003 million) (without taking management adjustments into account). To demonstrate the sensitivity of the ECL to these PD thresholds bandings, analysis was run on all collectively-assessed assets, which assumed all assets (Stage 1 and 2) were below the threshold and apportioned a 12-month ECL. On the same asset base, analysis was run which assumed all performing assets were above the threshold and apportioned a lifetime ECL. This gave rise to hypothetical collective-assessment ECLs of € 1,321 million (2021: € 634 million) and € 3,258 million (2021: € 2,232 million) respectively. Please note that in this analysis all other ECL risk parameters (except for the stage) were kept equal. Market risk IBOR transition () In line with the recommendations from the Financial Stability Board, a fundamental review of important interest rates benchmarks has been undertaken. While some interest benchmarks have been reformed, others have or will be replaced by risk-free rates (RFR) and discontinued. The reform of EURIBOR was completed in 2019 and allows for continued use. EONIA ceased to be published on 3 January 2022 and was succeeded by €STR, GBP, CHF, JPY, and EUR LIBOR rates ceased on 31 December 2021. The most used USD LIBOR tenors will continue to be published until the end of June 2023 to support legacy products. During 2021, ING and the industry focused on the transition of EONIA and non-USD LIBOR contracts. In 2022, the focus has shifted to USD LIBOR, with new USD lending already using alternative rates based on SOFR. This is consistent with guidance issued to limit the use of USD LIBOR from 1 January 2022 onward. A permitted exception are risk reduction trades to help manage the run-off of existing USD LIBOR contracts and positions. To enable these changes, the financial sector has issued several guidance papers and other initiatives to help phase in key components of this transition. For example ISDA issued an IBOR fallback supplement to help ensure clear fallback rates apply on the discontinuation of key IBORs. For loans, various recommendations have been made to help drive the inclusion of consistent robust fallback pro visions. Public authorities have also recognised that certain contracts do not contain provisions for any alternatives, contain inappropriate alternatives, or cannot be renegotiated prior to the expected cessation date (‘tough legacy’ contracts). In response, the European Commission has implemented legislation that gives the Commission the power to replace critical benchmarks if their termination would significantly disrupt or otherwise affect the functioning of the financial markets in the EU. For USD LIBOR specific actions have yet to be announced. In addition, the Financial Conduct Authority (FCA) has the remit to temporary publish a ‘’synthetic’’ LIBOR beyond the cessation date using a different methodology. The FCA has not yet decided whether it will require the administrator to publish synthetic USD LIBOR rates after June 2023, however such an action was taken for GBP and JPY LIBOR. At the end of 2021, ING Group had significant exposures to USD LIBOR. Due to the discontinuation of this important rate, ING Group, its customers, and the financial services industry face a number of risks. These risks include legal, financial, operational, and conduct risk. Legal risks are related to any required changes to existing transactions. Financial risks may arise due to declining liquidity and may impact a contract directly or the ability to hedge the risks in that contract. Operational risks due to the requirement to adapt IT systems, trade reporting infrastructure and operational processes to the new benchmark rates. Conduct risk also plays a role, given that the renegotiation of loan contracts requires active engagement from all parties to a contract, and may lead to negotiations concentrated in a period close to actual cessation. ING continues to reach out to impacted clients in order to manage the relevant timelines. The ING IBOR programme has governance in place with progress being tracked by business line steering committees reporting into a central IBOR steering committee. The programme assesses and coordinates the actions necessary to manage the required changes to internal processes and systems, including pricing, risk management, legal documentation, hedge arrangements, as well as the impact on our customers. ING continues to monitor market developments and any reform plans for other rates, to anticipate the impact on the program, our customers and any related risks. As at 30 June 2022 approximately EUR 40,485 million (31 December 2021: EUR 41,805 million) of non-derivative financial assets and approximately EUR 1,501 million (31 December 2021: EUR 1,542 million) of non-derivative liabilities linked to USD LIBOR have yet to transition to alternative benchmark rates. In addition, ING had as at 30 June 2022 approximately EUR 9,979 million (31 December 2021: EUR 16,435 million) of fully undrawn committed credit facilities linked to USD LIBOR that have yet to transition. The tables below summarize these approximate exposures for USD LIBOR and excludes exposures that will expire before transition date 30 June 2023. Non derivative Financial instruments to transition to alternative benchmarks () in EUR million at 30 June 2022 Financial Assets non-derivative Financial Liabilities non-derivative Off balance sheet commitments Carrying value Carrying value Nominal value By benchmark rate GBP LIBOR USD LIBOR 40,485 1,501 9,979 CHF LIBOR EONIA Total 40,485 1,501 9,979 Non derivative Financial instruments to transition to alternative benchmarks () in EUR million at 31 December 2021 Financial Assets non-derivative Financial Liabilities non-derivative Off balance sheet commitments Carrying value Carrying value Nominal value By benchmark rate GBP LIBOR 764 350 USD LIBOR 41,805 1,542 16,435 CHF LIBOR 1 EONIA 23 184 Total 42,570 1,565 16,969 As at 30 June 2022 approximately EUR 508,877 million (31 December 2021: EUR 488,499 million) derivatives notional exposures linked to USD LIBOR have yet to transition. The conduct risk is limited as the majority of derivatives are transacted with clearing houses which will transition through a standardized exercise in the second quarter of 2023 and for not centrally cleared derivatives the main transition will occur via ISDA IBOR fallback protocol at the USD LIBOR cessation date. The GBP LIBOR contracts included as at 31 December 2021 have transitioned. Derivative Financial instruments to transition to alternative benchmarks (*) 30 June 2022 31 December 2021 in EUR million Nominal value Nominal value By benchmark rate 1 GBP LIBOR 822 USD LIBOR 508,877 488,499 2 Total 508,877 489,321 1 For cross currency swaps all legs of the swap are included that are linked to a main IBOR that is significant to ING Group. 2 The prior period has been updated to improve consistency and comparability.

Credit risk

Portfolio quality and concentration

Our lending portfolio is diversified over various sectors and countries.

The total gross carrying amounts is

composed of approximately

% business lending and

% consumer lending. For a detailed breakdown of ING’s

credit risk portfolio by Sector and Geographical area, refer

to the section “Credit Risk portfolio” reported in the

‘Risk management’ section of the 2021 Annual Report.

ING’s total gross carrying amounts

increased compared to year-end 2021 due to higher customer lending and

cash and balances with central banks.

Loan loss provisioning (*)

ING recognises

loss allowances based on the expected credit loss (ECL) model of IFRS 9, which is designed to be

forward-looking. The IFRS 9 impairment requirements are

applicable to on-balance sheet financial assets

measured at amortised cost or fair value through other comprehensive

income (FVOCI), such as loans, debt

securities and lease receivables, as well as off-balance sheet items such as undrawn loan commitments,

certain

financial guarantees issued, and undrawn committed re

volving credit facilities.

The table below describes the portfolio composition over the different IFRS

9 stages and rating classes. The Stage

1 portfolio represents

93.4

% (2021:

93.5

%) of the total gross carrying amounts, mainly composed of investment

grade, while Stage 2 makes up

5.4

% (2021:

5.2

%) and Stage 3 makes up

1.2

% (2021:

1.3

%) total gross carrying

amounts, respectively.

Gross carrying amount per IFRS 9 stage and rating class (*)

in EUR million

12-month ECL (Stage 1)

Lifetime ECL not credit

impaired (Stage 2)

Lifetime ECL credit impaired

(Stage 3)

Total

30 June 2022

Rating class

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Investment grade

1 (AAA)

116,616

2-4 (AA)

112,044

259

112,303

5-7 (A)

170,785

1,402

172,187

8-10 (BBB)

336,871

9,745

346,616

Non-Investment grade

11-13 (BB)

164,326

231

13,745

178,071

314

14-16 (B)

27,239

180

16,083

367

43,322

548

17 (CCC)

6,267

4,391

213

10,658

220

Substandard grade

18 (CC)

5,654

780

5,654

780

19 (C)

2,710

420

2,710

420

Non-performing loans

20-22 (D)

11,831

3,640

11,831

3,640

Total

934,148

497

53,989

1,885

11,831

3,640

999,968

6,022

1 IAS 37 provisions are established for non-credit replacement guarantees not in the scope of IFRS 9. Total

IAS 37 provisions (€

117

million) are excluded.

Gross carrying amount per IFRS 9 stage and rating class (*)

in EUR million

12-month ECL (Stage 1)

Lifetime ECL not credit

impaired (Stage 2)

Lifetime ECL credit impaired

(Stage 3)

Total

31 December 2021

Rating class

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Gross

Carrying

Amount

Provisions

Investment grade

1 (AAA)

107,788

2-4 (AA)

106,673

197

106,870

5-7 (A)

152,167

1,000

153,167

8-10 (BBB)

328,302

7,232

335,533

Non-Investment grade

11-13 (BB)

163,228

208

14,679

177,908

294

14-16 (B)

26,852

185

17,931

404

44,783

589

17 (CCC)

5,377

4,354

198

9,730

207

Substandard grade

18 (CC)

2,314

173

2,314

173

19 (C)

1,769

142

1,769

142

Non-performing loans

20-22 (D)

12,072

3,851

12,072

3,851

Total

890,387

501

49,476

1,016

12,072

3,851

951,934

5,368

1 IAS 37 provisions are established for non-credit replacement guarantees not in the scope of IFRS 9. Total

IAS 37 provisions (€

114.4

million) are excluded.

The table below provides a reconciliation by stage of the gross carrying amount

and allowances for loans and

advances to banks and customers, including loan commitments and financial guarantees.

The transfers of

financial instruments represent the impact of stage transfers

upon the gross carrying/nominal amount and

associated allowance for ECL. This includes the net-remeasurement

of ECL arising from stage transfers,

for

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

(Stage 2) ECL measurement basis. The net-

remeasurement line represents the changes in provisions for

facilities that remain in the same stage.

Please note the following comments with respect to the movements observed in the table below:

◾

Stage 3 gross carrying amount decreased by €

0.2

billion from €

12.1

billion as per 31 December 2021

mainly as a result of write-offs and generally low inflow into NPL in the first

half of 2022;

◾

Stage 2 gross carrying amount increased by €

4.5

billion from €

49.5

billion as per 31 December 2021. This

is mainly caused by the Significant Lifetime PD trigger (€

6.4

billion) driven by downgrades of the Russian

portfolio and to a lesser extent the 30 Days past due trigger (€

1.9

bn), offset by decreases in other

triggers mainly the Forbearance (-/-€

4.0

billion) trigger.

For the latter,

a 2-year probation period is

required before a client can move back to Stage

1 and the decrease relates to the fact that the start

the COVID pandemic is now more than 2 years ago;

◾

In the first half year of 2022, the largest increases in Stage 2 were

in Natural Resources, Non-Bank

Financial Institutions and Telecom

of €

3.9

billion, €

0.9

billion and €

0.6

billion respectively, materially

impacted by the Russian portfolio. Largest decreases were in Automotive

and Utilities with €

0.7

release each. The largest Stage 2 outstandings per economic sector as per 30 June 2022 are Natural

Resources, Transportation

& Logistics, Real Estate and Services representing

% and

% of the

total Stage 2 gross carrying amounts respectively.

Additional information on macroeconomic scenarios is included in the section ‘Macro-economic scenarios and

sensitivity analysis of key sources of estimation uncertainty’.

Changes in gross carrying amounts and loan loss provisions (*)

1, 2

in EUR million

12-month ECL (Stage 1)

Lifetime ECL not credit

impaired (Stage 2)

Lifetime ECL credit

impaired (Stage 3)

Total

30 June 2022

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Opening balance

890,386

501

49,476

1,016

12,072

3,851

951,934

5,368

Transfer

into 12-month ECL (Stage 1)

8,534

-8,259

-115

-275

-28

-0

-130

Transfer

into lifetime ECL not credit impaired (Stage 2)

-17,556

-53

18,174

720

-618

-71

-0

596

Transfer

into lifetime ECL credit impaired (Stage 3)

-1,451

-9

-851

-53

2,302

611

549

Net remeasurement of loan loss provisions

-39

301

266

New financial assets originated or purchased

119,993

123

119,993

123

Financial assets that have been derecognised

-75,384

-34

-5,313

-49

-2,080

-137

-82,777

-220

Net drawdowns and repayments

9,625

761

431

10,818

Changes in models/risk parameters

Increase in loan loss provisions

804

379

1,184

Write-offs

-648

Recoveries of amounts previously written off

Foreign exchange and other movements

-5

Closing balance

934,148

497

53,989

1,885

11,831

3,640

999,968

6,022

Stage 3 Lifetime credit impaired provision includes €

million on Purchased or Originated Credit Impaired.

The addition to the loan provision (in the consolidated statement of profit or loss) amounts to €

1,189

million of which €

1,184

million related to IFRS-9 eligible financial assets, €

million related to non-credit replacement guarantees and €

million to modification gains and losses on

restructured financial assets.

Changes in gross carrying amounts and loan loss provisions (*)

1, 2

in EUR million

12-month ECL (Stage 1)

Lifetime ECL not credit

impaired (Stage 2)

Lifetime ECL credit impaired

(Stage 3)

Total

31 December 2021

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Gross

carrying

amount

Provisions

Opening balance

844,231

581

59,313

1,476

13,398

3,797

916,942

5,854

Transfer

into 12-month ECL (Stage 1)

15,157

-14,322

-279

-835

-54

-0

-313

Transfer

into lifetime ECL not credit impaired (Stage 2)

-19,737

-32

20,537

206

-800

-75

-0

100

Transfer

into lifetime ECL credit impaired (Stage 3)

-2,166

-13

-1,589

-96

3,755

820

-0

712

Net remeasurement of loan loss provisions

-130

-228

404

New financial assets originated or purchased

208,501

149

208,501

149

Financial assets that have been derecognised

-125,819

-73

-11,935

-104

-1,898

-237

-139,652

-414

Net drawdowns and repayments

-29,781

-2,527

-694

-33,002

Changes in models/risk parameters

130

184

Increase in loan loss provisions

-67

-460

989

462

Write-offs

-854

Recoveries of amounts previously written off

Foreign exchange and other movements

-13

-125

-138

Closing balance

890,386

501

49,476

1,016

12,072

3,851

951,934

5,368

Stage 3 Lifetime credit impaired provision includes €

million on Purchased or Originated Credit Impaired.

The addition to the loan provision (in the condensed consolidated statement of profit or loss) amounts to €

516

million of which €

462

million related to IFRS-9 eligible financial assets, €

million related to non-credit replacement guarantees and €

million to modification gains and

losses on restructured financial assets.

Our methodology in relation to the adoption and generation of macroeconomic scenarios is described in this

section. We continue to follow this methodology in generating

our probability-weighted ECL, with consideration

of alternative scenarios and management adjustments supplementing this ECL where, in management's

opinion,

the consensus forecast does not fully capture the extent

of recent credit or economic events. The

macroeconomic scenarios are applicable to the whole ING portfolio in the scope of IFRS 9 ECLs.

The IFRS 9 standard, with its inherent complexities and potential

impact on the carrying amounts of our assets

and liabilities, represents a key source of estimation uncertainty.

In particular, ING’s

reportable ECL numbers are

most sensitive to the forward-looking macroeconomic forecasts

used as model inputs, the probability-weights

applied to each of the three scenarios, and the criteria for identifying a significant increase in credit risk. As such,

these crucial components require consultation and management judgement, and are

subject to extensive

governance.

Baseline scenario (*)

As a baseline for IFRS 9, ING has adopted a market-neutral view combining consensus

forecasts for economic

variables (GDP,

unemployment) with market forwards (for interest

rates, exchange rates

and oil prices). The

Oxford Economics’ Global Economic Model (OEGEM) is used to complement

the consensus with consistent

projections for variables for which there are no consensus estimates

available (most notably house prices and –

for some countries - unemployment), to generate

alternative scenarios, to convert annual consensus information

to a quarterly frequency and to ensure general consistency

of the scenarios.

The relevance and selection of macroeconomic variables is defined by the ECL models under credit risk model

governance. The scenarios are reviewed and challenged by two panels. The first panel consists

of economic

experts from Global Markets Research and risk and modelling specialists, while the second

panel consists of

relevant senior managers.

Alternative scenarios and probability weights (*)

Two alternative scenarios are taken

into account; an upside and a downside scenario. The alternative scenarios

have technical characteristics as they are

based on the forecast errors of the OEGEM.

To understand

the baseline level of uncertainty around any forecast,

Oxford Economics keeps

track of all its

forecast errors of the past 20 years.

The distribution of forecast errors for

GDP,

unemployment, house prices and

share prices is applied to the baseline forecast creating a broad range

of alternative outcomes. In addition, to

understand the balance of risks facing the economy in an unbiased way,

Oxford Economics runs a survey with

respondents from around the world and across a broad range

of industries. In this survey the respondents put

forward their views of key risks. Following

the survey results, the distribution of forecast errors

(that is being

used for determining the scenarios) may be skewed.

For the downside scenario, ING has chosen for the 90th percentile of that distribution because this corresponds

with the way risk management earnings-at-risk is defined within the Group. The upside scenario is represented

by the 10th percentile of the distribution. The applicable percentiles of the distribution imply a 20% probability

for each alternative scenario. Consequently,

the baseline scenario has a 60% probability weighting. Please note

that, given their technical nature, the downside and upside scenarios are not based on an explicit specific

narrative.

Macroeconomic scenarios applied (*)

The loan loss provisions are based on the June 2022 consensus forecasts.

Baseline assumptions (*)

The general picture that the consensus conveys

is that higher inflation will be more persistent but still to be

transitory and, in combination with an overall tightening of monetary conditions,

fall back towards most central

bank’s targets

over the course of the forecast horizon. The baseline assumes that

the Russia-Ukraine war will not

spread beyond Ukraine but that the war drags on with risks to

the energy outlook. Against a background of

slowing economic (and hence disposable income) growth, increasing unemployment, higher interest rates

and,

for some markets, high valuations house prices growth is expected

to level off to low single digit rates or price

declines.

The June 2022 consensus expects global output growth (ING definition), after a strong rebound in 2021 of

5.9

to slow to

2.7

% in 2022 and to level off further to an at or around

2.5

% growth rate in the years thereafter.

When compared to the December 2021 consensus forecast, used for the

2021 Annual Report, the June 2022

forecast assumes a less strong economic environment.

Global GDP is expected to increase by

2.7

% in 2022

(compared to

4.1

% assumed before) and

2.5

% in 2023 (

3.1

% assumed before). This downward adjustment

reflects the repercussions from the Russia-Ukraine war and the surge

in commodity and oil prices squeezing

household incomes and pushing up interest rates. Although to various

degrees, these developments all weigh on

the economic outlook of the various countries. Tightening of monetary conditions is seen to be swifter in the US

than in the eurozone while the European economies are more directly exposed

to the Russia-Ukraine war.

Alternative scenarios and risks (*)

Because of the possible consequences of the Russia-Ukraine war,

uncertainty surrounding the forecasts is

assessed as being larger than usual. This reflects uncertainty about European energy supply and worries about

more persistent high inflation. To

reflect the general increase of uncertainty surrounding the forecasts,

the

dispersion of the alternative scenarios was used in Q2 2022 at the same widened level as used in Q4 2021

provisioning (half-widened dispersion). The downward skew

following on from the outcomes of Oxford

Economics’ Global Risk Survey has been maintained and is more negative compared

to what has been assumed

for Q4 2021.

The downside scenario – though technical in nature – sees, for most countries, a fast deceleration

of economic

growth followed by a recession. Unemployment increases strongly

in this scenario and house prices in most

countries show outright falls. The downside scenario captures a possible escalation of the Russia-Ukraine war

and

a more pronounced and prolonged surge

in inflation (cut off from Russian gas supplies).

The upside scenario – while equally technical in nature – reflects the possibility of a better economic outturn in

case the Russia-Ukraine war would end quickly and a quicker fading of coronavirus

and other concerns leading to

a consumer-led recovery in advanced economies as consumers

spend (some of) their savings accumulated at the

height of the corona crisis.

Management adjustments applied this year (*)

In times of volatility and uncertainty where portfolio quality and the economic environment are

changing rapidly,

models alone may not be able to accurately predict losses. In these cases, management adjustments can

applied to appropriately reflect ECL. Management adjustments

can also be applied where the impact of the

updated macroeconomic scenarios is over-

or under-estimated by the IFRS 9 models.

ING has internal governance frameworks and controls

in place to assess the appropriateness of all management

adjustments.

December 2021 management adjustments included an economic sector-based management adjustment

of €

341

million because of delays in defaults occurring in the Covid-19 related crisis, mainly as a result of government

support programmes. In determining the sector-based management

adjustment, a heatmap approach was used

to adjust the probability of default for sectors

where businesses are significantly impacted by the pandemic. In

the first half year of 2022, as it became clearer the Covid-19 had less than expected impact on the number of

defaults, the economic sector-based management adjustment

has been partly released and partly been

converted to second order impact adjustment (see below). The remaining €

million relates to business banking

clients that have benefitted from government

support programmes in the Netherlands such as deferral of tax

payments that will end in the second half of 2022.

ING performed an assessment for both wholesale banking and retail banking on the impact of the developing

situation in Ukraine, the increase in energy prices and other macro-economic developments such as increase of

inflation and rising interest rates. As the credit risk models assume that these effects

materialize via other risk

drivers such as GDP and unemployment rates with an delay,

an overlay approach was determined to timely

estimate the Expected Credit Losses for private

individuals. As at 30 June 2022 the second order impact overlay

for Retail countries amounts to €

In Wholesale banking it was assessed that the economic effects of Covid-19 is not the biggest risk anymore and

that other risks have emerged – mainly high energy prices, high interest

rates and inflation, supply chain issues

and staffing shortages. A heatmap approach was used to

adjust the probability of default for clients that are

expected to be significantly impacted by these emerged risks. As at

30 June 2022 the second order impact

overlay for Wholesale banking amounts to €

228

As payment holiday programs generally

have expired, this Covid-19 related

management adjustment has been

fully released.

ECL of mortgage portfolios determined by the models continued to decrease

rapidly during 2021 and decreased

further in the first half of 2022, driven by significant increase of house prices in various countries. Management

adjustments of €

131

million in total, mainly in stage 2 and 3, have been recognised in ING Netherlands, Belgium,

Germany and Australia to maintain an appropriate

level of ECL and reflecting a potential impact of higher

inflation and interest rates on clients’

ability to pay and a potential impact of market uncertainty on the recovery

value of residential real estate. The management adjustment

for the Netherlands mortgage portfolio was

determined by developing three alternative macroeconomic forecast

scenarios, in addition to the consensus

base, up- and down-scenarios, that reflect a correction in the house prices in the next 3 years bringing it back in

line with the historical growth rate. For other countries,

management adjustments were determined by

calculating the impact of lower house prices on LTVs

and LGDs.

Other Post Model Adjustments mainly relate to the impact of model redevelopment

or recalibration and periodic

model assessment procedures that have not been incorporated

in the ECL models yet. These result from both

regular model maintenance and ING’s multiyear

program to update ECL models for the new definition of default.

These adjustments will be removed once updates to the models have been implemented

Analysis on sensitivity (*)

The table below presents the analysis on the sensitivity of key forward-looking macroeconomic

inputs used in the

ECL collective-assessment modelling process and the probability-weights applied to each of the three scenarios.

The countries included in the analysis are the most significant geographic regions, in terms of both gross

contribution to reportable ECL, and sensitivity of ECL to forward

-looking macroeconomics. Accordingly,

ING

considers these portfolios to present the most significant

risk of resulting in a material adjustment to the carrying

amount of financial assets within the next financial year.

ING also observes that, in general, the Wholesale

Banking business is more sensitive to the impact of forward-looking macroeconomic scenarios.

The purpose of the sensitivity analysis is to enable the reader to understand the extent of the impact from the

upside and downside scenario on model-based reportable ECL. The table does not include any management

adjustments.

In the table below the Real GDP is presented in percentage

year-on-year change, the unemployment in

percentage of total labour force and the house price index

(HPI) in percentage year-on year change.

Sensitivity analysis as at June 2022

(*)

2022

2023

2024

Un-weighted

ECL (Eur mln)

Probability-

weighting

Reportable ECL

(Eur mln)

Netherlands

Upside scenario

Real GDP

3.6

2.5

3.0

297

20%

361

Unemployment

3.7

3.5

HPI

17.6

15.7

4.1

Baseline Scenario

Real GDP

2.8

1.3

1.8

337

60%

Unemployment

4.1

4.5

4.7

HPI

14.8

2.7

1.9

Downside scenario

Real GDP

0.3

-1.4

0.8

494

20%

Unemployment

5.8

6.9

8.0

HPI

11.1

-13.4

-0.9

Germany

Upside scenario

Real GDP

2.8

3.6

2.3

642

20%

787

Unemployment

2.7

2.6

2.2

HPI

11.7

6.3

4.8

Baseline Scenario

Real GDP

1.8

2.1

1.8

772

60%

Unemployment

3.1

3.2

3.3

HPI

10.8

3.3

1.4

Downside scenario

Real GDP

-0.3

-1.2

0.6

977

20%

Unemployment

4.6

5.3

5.8

HPI

9.0

-2.1

-2.3

Belgium

Upside scenario

Real GDP

3.1

3.0

2.2

546

20%

608

Unemployment

5.2

5.1

5.2

HPI

4.8

3.0

2.5

Baseline Scenario

Real GDP

2.4

1.8

596

60%

Unemployment

5.7

5.8

HPI

4.4

2.3

2.0

Downside scenario

Real GDP

0.8

-0.3

1.3

705

20%

Unemployment

6.9

7.7

8.2

HPI

3.2

0.3

0.7

United States

Upside scenario

Real GDP

3.9

2.5

2.4

20%

156

Unemployment

3.6

3.3

2.8

HPI

10.1

4.4

8.1

Baseline Scenario

Real GDP

2.4

1.5

1.7

124

60%

Unemployment

3.9

4.2

HPI

9.8

1.2

2.3

Downside scenario

Real GDP

0.2

-1.6

0.1

342

20%

Unemployment

6.0

7.2

8.3

HPI

8.7

-4.3

-4.1

1 Excluding management adjustments.

Sensitivity analysis as at December 2021 (*)

2022

2023

2024

Un-weighted

ECL (Eur mln)

Probability-

weighting

Reportable ECL

(Eur mln)

Netherlands

Upside scenario

Real GDP

5.1

2.9

2.7

259

20%

307

Unemployment

3.2

2.9

HPI

23.3

10.9

0.9

Baseline Scenario

Real GDP

3.4

2.0

1.7

289

60%

Unemployment

3.7

4.1

4.3

HPI

13.1

2.8

0.8

Downside scenario

Real GDP

-1.5

1.2

0.7

411

20%

Unemployment

5.6

6.8

7.8

HPI

0.3

-7.7

0.6

Germany

Upside scenario

Real GDP

6.2

3.1

1.6

457

20%

483

Unemployment

2.9

2.2

1.9

HPI

12.9

7.9

5.3

Baseline Scenario

Real GDP

4.0

2.3

1.4

475

60%

Unemployment

3.4

3.1

HPI

10.4

4.6

1.9

Downside scenario

Real GDP

-0.6

0.9

0.8

535

20%

Unemployment

5.0

5.4

5.7

HPI

5.3

0.4

-2.1

Belgium

Upside scenario

Real GDP

4.6

2.5

2.0

364

20%

393

Unemployment

5.6

5.9

HPI

3.9

2.7

2.9

Baseline Scenario

Real GDP

3.1

2.0

1.8

383

60%

Unemployment

6.1

6.3

HPI

3.0

2.3

Downside scenario

Real GDP

-0.4

1.4

451

20%

Unemployment

7.6

8.6

9.0

HPI

0.4

1.0

United States

Upside scenario

Real GDP

6.7

2.4

3.1

20%

Unemployment

3.5

2.5

2.4

HPI

10.4

8.1

8.7

Baseline Scenario

Real GDP

4.0

2.5

2.1

60%

Unemployment

4.0

3.7

HPI

9.1

3.0

3.3

Downside scenario

Real GDP

-0.7

1.1

0.3

183

20%

Unemployment

6.5

7.4

8.0

HPI

5.3

-3.2

-3.0

1 Excluding management adjustments.

When compared to the sensitivity analysis of 2021, the macroeconomic inputs for 2022 and 2023 are less

favourable, driven by worsened

macro-economic outlook as a result of the war in Ukraine as well as its indirect

effects such as inflation and increasing interest

rates. Both 2021 and 2022 contain half widened dispersion

around upside and downside scenarios, for 2021 reflecting continuing but decreased short term uncertainty

related to the impact of Covid-19 and for 2022 reflecting short term

uncertainty around the war in Ukraine and

its indirect effects. The increase in reportable ECL compared

to 2021 is mainly caused by higher model ECL

amounts as per June 2022 as a result of increased provisions for Russia related exposures

in Stage 2.

While the table above does give a high-level indication of the sensitivity of the outputs to the different

scenarios,

it does not provide insight into the interdependencies and correlations between

different macroeconomic

variable inputs. On total ING level, the unweighted ECL for

all collective provisioned clients in the upside scenario

was €

2,754

million, in the baseline scenario €

3,181

million and in the downside scenario €

4,305

million compared

to €

3,337

million reportable collective provisions as per 30 June 2022 (excluding all management

adjustments).

This reconciles as follows to the reported ECL’s:

Criteria for identifying a significant increase in credit risk (SICR) (*)

For the methodology and our approaches on absolute lifetime PD threshold and relative

lifetime PD threshold,

please refer to the “Risk management” section in the Annual Report ING Group for the year ended December 31,

2021.

In the table below the average increase in PD at origination needed to be classified in Stage

2 is reported, taking

into account the PD at origination of the facilities included in each combination of asset class and rating quality.

In terms of rating quality,

assets are divided into “Investment grade” and “Non-investment

grade” facilities.

Rating 18 and 19 are not included in the table since facilities are not originated in these ratings and they

constitute a staging trigger of their own (i.e. if a facility is ever to reach rating

18 or 19 at reporting date, it is

classified in Stage 2). In the table below values are weighted by IFRS 9 exposure

and shown for both year-end

2021 and June 2022.

In order to represent the thresholds as a ratio (i.e. how much should the PD at origination increase

in relative

terms to trigger Stage 2 classification) the absolute threshold is recalculated

as a relative threshold for disclosure

purposes. Since breaching only relative or absolute threshold triggers Stage 2 classification,

the minimum

between the relative and recalculated absolute threshold

is taken as value of reference

for each facility.

As it is apparent from the disclosures above, as per ING’s methodology,

the threshold is tighter the higher the

riskiness at origination of the assets, and confirmed by the noticeable difference between the average

threshold

applied to investment grade facilities and non-investment

grade facilities. In addition to the above, asset classes

having usually more favourable ratings

at origination (i.e. Governments and Financial Institutions) show an

average threshold higher than the rest in investment

grade assets. Changes in the threshold averages between

the two reporting dates are caused by model updates (the staging

parameters have been recalibrated)

and/ or by

changes in portfolio composition.

Sensitivity of ECL to PD lifetime PD thresholds

The setting of PD threshold bandings requires management judgement and is a key

source of estimation

uncertainty. On Group

level, the total ECL collective-assessment for performing

assets is €

1,849

million (2021:

€

1,003

million) (without taking management adjustments into account). To

demonstrate the sensitivity of the

ECL to these PD thresholds bandings, analysis was run on all collectively-assessed assets, which assumed all

assets (Stage 1 and 2) were below the threshold and apportioned a 12-month ECL. On the same asset base,

analysis was run which assumed all performing assets were above the threshold and apportioned a lifetime ECL.

This gave rise to hypothetical collective-assessment ECLs

of €

1,321

million (2021: €

634

million) and €

3,258

million (2021: €

2,232

million) respectively. Please note that

in this analysis all other ECL risk parameters (except

for the stage) were kept

equal.

Market risk

IBOR transition (*)

In line with the recommendations from the Financial Stability Board, a fundamental review of important

interest

rates benchmarks has been undertaken. While some interest

benchmarks have been reformed, others have

will be replaced by risk-free rates

(RFR) and discontinued. The reform of EURIBOR was completed in 2019 and

allows for continued use. EONIA ceased to be published on 3 January 2022 and was succeeded by €STR, GBP,

CHF,

JPY,

and EUR LIBOR rates ceased on 31 December 2021. The most used USD LIBOR tenors will continue to be

published until the end of June 2023 to support legacy products.

During 2021, ING and the industry focused on the transition of EONIA and non-USD LIBOR contracts. In 2022, the

focus has shifted to USD LIBOR, with new USD lending already using alternative rates

based on SOFR.

This is

consistent with guidance issued to limit the use of USD LIBOR from 1 January 2022 onward. A permitted

exception are risk reduction trades to

help manage the run-off of existing USD LIBOR contracts and positions.

To enable these changes, the financial sector has issued several

guidance papers and other initiatives to help

phase in key components of this transition. For example

ISDA issued an IBOR fallback supplement to help ensure

clear fallback rates apply on the discontinuation of key

IBORs. For loans, various recommendations have been

made to help drive the inclusion of consistent robust fallback pro

visions.

Public authorities have also recognised that certain contracts do not contain

provisions for any alternatives,

contain inappropriate alternatives, or cannot be renegotiated

prior to the expected cessation date (‘tough legacy’

contracts). In response, the European Commission has implemented legislation that

gives the Commission the

power to replace critical benchmarks if their termination would significantly disrupt or otherwise affect

the

functioning of the financial markets in the EU. For USD LIBOR specific actions have yet to

be announced. In

addition, the Financial Conduct Authority (FCA) has the remit to temporary publish a ‘’synthetic’’

LIBOR beyond

the cessation date using a different methodology.

The FCA has not yet decided whether it will require the

administrator to publish synthetic USD LIBOR rates

after June 2023, however such an action was taken for

GBP

and JPY LIBOR.

At the end of 2021, ING Group had significant exposures to USD LIBOR. Due to the discontinuation

of this

important rate, ING Group, its customers,

and the financial services industry face a number of risks. These risks

include legal, financial, operational, and conduct risk. Legal risks are related

to any required changes to existing

transactions. Financial risks may arise due to declining liquidity and may impact a contract directly

or the ability

to hedge the risks in that contract. Operational risks due to

the requirement to adapt IT systems, trade

reporting

infrastructure and operational processes to the new

benchmark rates. Conduct risk also plays a role, given that

the renegotiation of loan contracts requires active engagement

from all parties to a contract, and may lead to

negotiations concentrated in a period close to actual cessation. ING continues to reach

out to impacted clients in

order to manage the relevant timelines.

The ING IBOR programme has governance in place with progress being tracked

by business line steering

committees reporting into a central IBOR steering

committee. The programme assesses and coordinates

the

actions necessary to manage the required changes to internal processes and systems,

including pricing, risk

management, legal documentation, hedge arrangements,

as well as the impact on our customers. ING continues

to monitor market developments and any reform

plans for other rates, to anticipate the impact on the program,

our customers and any related risks.

As at 30 June 2022 approximately EUR

40,485

million (31 December 2021: EUR

41,805

million) of non-derivative

financial assets and approximately EUR

1,501

million (31 December 2021: EUR

1,542

million) of non-derivative

liabilities linked to USD LIBOR have yet to transition

to alternative benchmark rates. In addition, ING had as at 30

June 2022 approximately EUR

9,979

million (31 December 2021: EUR

16,435

million) of fully undrawn committed

credit facilities linked to USD LIBOR that have

yet to transition.

The tables below summarize these approximate exposures

for USD LIBOR and excludes exposures that will expire

before transition date 30 June 2023.

As at 30 June 2022 approximately EUR

508,877

million (31 December 2021: EUR

488,499

million) derivatives

notional exposures linked to USD LIBOR have yet

to transition. The conduct risk is limited as the majority of

derivatives are transacted with clearing houses which will transition through

a standardized exercise

in the

second quarter of 2023 and for not centrally cleared derivatives

the main transition will occur via ISDA IBOR

fallback protocol at the USD LIBOR cessation date. The GBP LIBOR contracts

included as at 31 December 2021

have transitioned.