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Expected credit loss measurement
 12 Months Ended
Dec. 31, 2022
Entity [Table]  
Disclosure Of Financial Assets Explanatory
Additional information
Note 19
 
Expected credit loss measurement
 
 
a) Expected credit losses in the period
Total
 
net credit loss expenses
 
were USD
29
m in 2022, reflecting
 
net credit loss expenses
 
of USD
29
m related to stage 1
and 2 positions and USD
0
m net credit loss expenses related to credit-impaired
 
(stage 3) positions.
Stage 1
 
and
 
2
 
expected
 
credit
 
loss
 
(ECL)
 
expenses
 
of
 
USD
29
m
 
include
 
USD
123
m
 
expenses
 
related
 
to
 
scenario
 
and
parameter updates
 
and USD
13
m related to
 
other book quality and
 
size changes, partly offset
 
by USD
77
m post-model
adjustment (PMA) releases and
 
USD
30
m releases related to model changes. Lending to corporate clients not secured
 
by
mortgages contributed USD
21
m, mainly driven by scenario effects related to the
 
downward revision of GDP and
 
higher
interest rate
 
assumptions
 
in the
 
newly
 
introduced
stagflationary
 
geopolitical
 
crisis
 
scenario
 
(SGC).
 
Lending
 
secured
 
by
mortgages
 
contributed
 
USD
 
16
m
 
in
 
expenses
,
 
mainly
 
driven
 
by
 
scenario
 
effects
 
related
 
to
 
higher
 
interest
 
rate
assumptions,
 
especially from the SGC, and adverse house price assumptions
 
from both applied downside scenarios.
 
This
was partly offset by releases from other lending
 
of USD
9
m.
›
 
Refer to Note 19b
 
for more information
 
regarding changes
 
to ECL models,
 
scenarios, scenario
 
weights and the
 
post-model
adjustment and to
 
Note 19c
 
for more information
 
regarding the development
 
of ECL allowances
 
and provisions
Stage 3 net expenses of USD
0
m were recognized across
 
a number of
 
defaulted positions, with net expenses of
 
USD
12
m
in Personal
 
and Corporate
 
Banking
 
and USD
5
m in
 
Global Wealth
 
Management,
 
offset by
 
releases of
 
USD
18
m in
 
the
Investment Bank, including a USD
28
m release for a single airline-related counterparty, mainly due to improved cashflow
assumptions, and USD
10
m net expenses across a number of defaulted positions.
Credit loss expense
 
/ (release)
USD m
Global
 
Wealth
 
Management
Personal &
 
Corporate
 
Banking
Asset
Management
Investment
 
Bank
Group
 
Functions
Total
For the year ended
 
31.12.22
Stages 1 and 2
(5)
27
0
6
1
29
Stage 3
5
12
0
(18)
2
0
Total credit loss expense /
 
(release)
0
39
0
(12)
3
29
For the year ended
 
31.12.21
Stages 1 and 2
(28)
(62)
0
(34)
0
(123)
Stage 3
(1)
(24)
1
0
0
(25)
Total credit loss expense /
 
(release)
(29)
(86)
1
(34)
0
(148)
For the year ended
 
31.12.20
Stages 1 and 2
48
129
0
88
0
266
Stage 3
40
128
2
217
42
429
Total credit loss expense /
 
(release)
88
257
2
305
42
694
b) Changes to ECL models,
 
scenarios, scenario
 
weights and key inputs
 
Refer
 
to
 
Note 1a for
 
information about
 
the
 
principles governing
 
expected
 
credit
 
loss (ECL)
 
models, scenarios,
 
scenario
weights and key inputs
 
applied.
 
Governance
Comprehensive cross-functional
 
and cross-divisional
 
governance processes
 
are in
 
place and
 
are used to
 
discuss and
 
approve
scenario updates and
 
weights, to
 
assess whether significant increases
 
in credit
 
risk resulted in
 
stage transfers, to
 
review
model outputs and to reach
 
conclusions regarding
 
post-model adjustments.
 
Model changes
During 2022, the model review and enhancement process led to adjustments
 
of the probability of default (PD), loss given
default (LGD), and
 
credit conversion factor
 
(CCF) models, resulting
 
in a USD
30
m decrease in
 
ECL allowances.
 
This includes
a
 
decrease of
 
USD
19
m
 
in Global
 
Wealth Management
 
affecting loans
 
to
 
financial advisors and
 
specialized US
 
lending
portfolios and
 
an USD
11
m decrease
 
in Personal
 
& Corporate
 
Banking
 
related to
 
lending to
large corporate clients
 
and
financial intermediaries
 
& hedge funds
.
 
Scenario and key input
 
updates
During 2022, the scenarios
 
and related macroeconomic factors were updated
 
from those applied
 
at the end of
 
2021 by
considering the
 
prevailing economic
 
and
 
political conditions
 
and
 
uncertainty. The review
 
focused
 
on events
 
that
 
significantly
changed the
 
economic
 
outlook during
 
the year:
 
the Russia–Ukraine
 
war, with the subsequent
 
effect on
 
energy markets,
 
the
inflation outlook and economic growth in Europe, and rising global interest rates due to central banks’ adoption of more
restrictive monetary
 
policies.
Baseline scenario
: the
 
projections
 
of the
 
baseline scenario,
 
which are
 
aligned to
 
the economic
 
and market
 
assumptions
 
used
for UBS’s
 
business
 
planning
 
purposes,
 
are broadly
 
in line
 
with external
 
data, such
 
as that
 
from Bloomberg
 
Consensus,
 
Oxford
Economics and the International
 
Monetary Fund
 
World Economic Outlook.
 
The expectation for 2023 is
 
that global growth
stalls under
 
the weight
 
of monetary
 
policy
 
tightening,
 
and continued
 
pressure
 
on real
 
purchasing
 
power
 
due to
 
high inflation
– further fueled
 
in Europe
 
by the energy
 
crisis and
 
a lack of
 
labor supply
 
– even though
 
unemployment rates
 
are forecast to
be higher than
 
in 2022 and
 
an energy crisis
 
in Europe
 
seems likely to
 
be averted.
 
Interest
 
rates are
 
expected to
 
remain high,
given the persistence of inflationary
 
trends, leading to a less
 
optimistic outlook for global
 
house prices, which is cushioned
in Switzerland by continued
 
strong demand.
 
Global crisis scenario:
The first hypothetical
 
downside scenario, the global crisis
 
scenario, is aligned with the Group’s
 
2022
binding stress scenario and was
 
updated in 2022
 
to reflect expected risks, resulting in
 
minimal changes. It assumes that,
while the
 
global economy
 
has returned to
 
pre-pandemic levels
 
and the immediate
 
risks
 
from COVID-19
 
have decreased,
 
the
associated disruptions
 
and
 
the
 
consequences of
 
the unprecedented
 
monetary and
 
fiscal stimulus
 
measures will
 
remain
critical. Concerns regarding
 
the sustainability
 
of public debt, following the marked deterioration
 
of fiscal positions, lead to
a loss
 
of confidence and
 
market turbulence, while protectionism results in
 
a decrease
 
in global
 
trade. Governments and
central banks have limited scope
 
to support the economies,
 
and interest rate levels remain moderate. As a
 
consequence,
China
 
suffers a
 
hard landing
 
which,
 
combined with
 
political, solvency and
 
liquidity concerns,
 
affects emerging
 
markets
significantly. A
 
spillover
 
effect
 
leads
 
to
 
a
 
contraction of
 
the
 
Eurozone,
 
Swiss
 
and
 
US
 
economies,
 
as
 
global
 
demand
 
is
significantly affected.
 
Given the
 
severity of the
 
macroeconomic
 
impact, unemployment
 
rates rise to
 
historical highs
 
and real
estate sectors contract
 
sharply.
Stagflationary
 
geopolitical
 
crisis
 
scenario:
The
 
second
 
downside
 
scenario
 
was
 
changed
 
during
 
2022.
 
In
 
light
 
of
 
the
developments caused by Russia’s invasion of Ukraine, the
mild global interest rate steepening scenario
 
was replaced by a
severe global
 
interest rate
 
steepening scenario
 
in the
 
first quarter of
 
2022, as
 
the beginning of
 
the Russia–Ukraine war
increased fears of
 
higher inflation and a corresponding
 
reaction by monetary
 
authorities. In
 
the second quarter of the
 
year,
the progression
 
of the war
 
and the enforcement
 
of sanctions
 
regimes led
 
to a redesign
 
of the scenario.
 
The resulting
severe
Russia–Ukraine conflict scenario
 
has similar dynamics as the severe global interest rate
 
steepening scenario, but addressed
specifically the prospect
 
of rising
 
energy costs, especially
 
in Europe, with
 
the consequences
 
of lower
 
growth and higher
inflation rates.
 
In the
 
fourth quarter of
 
2022, UBS
 
developed a new
stagflationary geopolitical
 
crisis scenario
 
(SGC)
 
and
included this new scenario in the ECL
 
calculation for year-end
 
2022 in lieu of
 
the
severe Russia–Ukraine conflict scenario
.
While
 
the SGC scenario addresses similar risks as the
severe Russia–Ukraine conflict
 
scenario
, it also covers additional and
broader risks and
 
therefore assumes
 
more severe
 
shocks. Geopolitical
 
tensions cause
 
an escalation
 
of security concerns
 
and
undermine globalization. The
 
ensuing economic regionalization leads
 
to a
 
surge in
 
global commodity prices
 
and further
disruptions of
 
supply chains
 
and raises
 
the specter
 
of prolonged
 
stagflation.
 
The severe
 
interest
 
rate and
 
adverse
 
house price
assumptions in
 
the SGC scenario
 
had a substantive
 
impact on model-based
 
ECL allowances
 
for loans
 
secured by
 
mortgages
in Switzerland and
 
the US. These
 
effects were
 
partly offset
 
by PMA releases
 
related to loans
 
secured by mortgages.
 
Refer to
the section below
 
on “Scenario weights
 
and post-model adjustments”
 
for more details.
Asset price
 
inflation scenario:
The upside
 
scenario is
 
based on
 
positive developments,
 
such as
 
an easing
 
of
 
geopolitical
tensions across the
 
globe and
 
a rebound
 
in Chinese economic
 
growth. A
 
combination of
 
lower energy and
 
commodity
prices,
 
effective monetary
 
policies
 
and
 
easing
 
supply
 
chain
 
disruptions helps
 
reduce
 
inflation.
 
Improved
 
consumer and
business sentiment lead to an economic rebound with central banks able to normalize interest rates; asset prices increase
significantly.
The table below details the key assumptions
 
for the four scenarios applied
 
as of 31 December 2022.
Scenario weights and post
 
-model adjustments
Due
 
to the
 
less positive
 
outlook
 
compared
 
with the
 
assessment on
 
31 December
 
2021, the
 
scenario weights
 
changed
during 2022. The upside scenario was allocated
 
a
0
% probability, and the previous
5
% weight was added to the
baseline
scenario
, now
 
set at
60
%. Following
 
the introduction
 
of the
 
SGC, which
 
was deemed
 
to have
 
a higher
 
probability of
occurring than
 
the
global crisis
 
scenario
, the weights
 
were rebalanced.
 
The SGC
 
has a
 
weight of
25
% (compared
 
with
10
% for the
mild global
 
interest rate steepening
 
scenario
 
used as
 
of 31 December
 
2021) and
 
the weight
 
of the
global
crisis scenario
 
was reduced to
15
% (from
30
% as of 31 December
 
2021). The weights are also shown in the
 
table below.
The
 
scenarios
 
and
 
weight
 
allocation
 
were
 
established
 
in
 
line
 
with
 
the
 
general
 
market
 
sentiment
 
that
 
the
 
short-term
outlook
 
is subdued
 
and a
 
recession in
 
major markets
 
is a
 
strong
 
probability. The
 
downside
 
risks in
 
relation to
 
inflation
and monetary policy,
 
as well as
 
the availability and
 
price of energy,
 
mainly in Europe,
 
are better reflected
 
in our
 
models
compared with the uncertain developments
 
caused by COVID-19 in recent
 
years.
 
However, unquantifiable risks continue
 
to be relevant, as the
 
pandemic has not
 
been overcome and the world
 
may face
new disruptions.
 
Furthermore, the geopolitical
 
situation worsened
 
during 2022,
 
and the impact on
 
the world
 
economy
from escalations with unforeseeable
 
consequences could be severe. In the near term, this
 
uncertainty relates primarily to
the development
 
of the
 
Russia–Ukraine
 
war. Models,
 
which are
 
based on
 
supportable statistical
 
information
 
from past
experiences regarding interdependencies of
 
macroeconomic factors and their
 
implications for credit
 
risk portfolios, cannot
comprehensively reflect
 
such extraordinary
 
events, such
 
as a
 
pandemic or
 
a fundamental
 
change
 
in the
 
world political
order. Rather than
 
creating multiple additional scenarios
 
to attempt gauging these
 
risks and applying
 
model parameters
that lack supportable information and
 
cannot be robustly validated, management
 
continued to
 
also apply PMAs.
 
These PMA took into account that more of the downside risks were modeled in 2022, particularly for lending
 
secured by
mortgages.
 
The
 
PMA
 
amounted
 
to
 
USD
131
m
 
as
 
of
 
31 December
 
2022
 
(31 December
 
2021:
 
USD
224
m).
 
These
remaining PMA
 
for uncertainties
 
on potentially
 
unmodeled risk
 
almost entirely
 
relate
 
to corporate
 
lending portfolios
 
in
Personal & Corporate Banking
 
and the Investment Bank.
Economic scenarios and weights applied
Assigned weights in %
ECL scenario
31.12.22
31.12.21
Asset price inflation
0.0
5.0
Baseline
60.0
55.0
Mild global interest rate steepening
 
0.0
10.0
Stagflationary geopolitical crisis
25.0
0.0
Global crisis
 
15.0
30.0
Scenario assumptions
One year
 
Three years cumulative
 
31.12.22
Asset price
inflation
Baseline
Stagflationary
geopolitical
crisis
 
Global
crisis
 
Asset price
inflation
Baseline
Stagflationary
geopolitical
crisis
 
Global
crisis
 
Real GDP growth (% change)
United States
4.0
(0.3)
(4.8)
(6.4)
9.1
3.2
(4.4)
(1.8)
Eurozone
3.0
0.6
(5.6)
(8.5)
6.2
2.5
(5.7)
(8.3)
Switzerland
3.0
0.7
(4.8)
(6.7)
6.6
3.5
(4.9)
(3.7)
Consumer price index (% change)
 
United States
2.5
2.6
10.0
(0.5)
8.1
6.5
15.8
1.2
Eurozone
2.3
5.0
9.6
(0.7)
7.4
9.6
14.8
(0.7)
Switzerland
2.1
1.6
5.8
(1.8)
6.2
3.9
10.7
(1.6)
Unemployment rate (end-of
 
-period level, %)
United States
3.0
3.9
9.2
10.0
3.0
5.3
11.8
9.4
Eurozone
6.0
7.0
10.9
11.9
6.0
7.1
12.2
13.0
Switzerland
1.7
2.3
4.3
4.4
1.5
2.6
5.1
4.9
Fixed income: 10-year government
 
bonds (change in yields, basis points)
USD
25.0
(5.6)
235.0
(326.0)
70.0
(13.2)
205.0
(291.1)
EUR
20.0
47.8
250.0
(270.6)
57.5
44.7
220.0
(246.5)
CHF
25.0
45.7
220.0
(209.7)
62.5
57.0
205.0
(159.6)
Equity indices (% change)
S&P 500
20.0
7.4
(51.5)
(50.0)
51.7
22.8
(45.6)
(27.9)
EuroStoxx 50
17.0
17.2
(51.6)
(50.0)
42.9
29.2
(47.2)
(39.3)
SPI
14.0
5.6
(51.6)
(46.0)
37.9
19.3
(47.2)
(32.9)
Swiss real estate (% change)
Single-Family Homes
 
6.6
1.1
(16.7)
(19.9)
14.0
2.3
(32.9)
(23.9)
Other real estate (% change)
United States (S&P / Case–Shiller)
7.8
(4.5)
(12.8)
(19.3)
19.1
(0.6)
(35.8)
(32.7)
Eurozone (House Price Index)
7.0
(2.7)
(8.4)
(8.9)
15.4
2.0
(14.7)
(17.5)
Scenario assumptions
One year
 
Three years cumulative
 
31.12.21
Asset price
inflation
Baseline
Mild global
interest rate
steepening
 
Global crisis
 
Asset price
inflation
Baseline
Mild global
interest rate
steepening
 
Global crisis
 
Real GDP growth (% change)
United States
9.1
4.4
(0.1)
(5.9)
17.8
10.1
1.8
(3.8)
Eurozone
9.4
3.9
(0.1)
(8.7)
17.3
7.5
0.9
(10.3)
Switzerland
5.5
2.4
(0.9)
(6.6)
13.1
5.8
(0.1)
(5.7)
Consumer price index (% change)
United States
3.1
2.2
5.7
(1.2)
9.5
6.3
13.0
0.4
Eurozone
2.3
1.4
4.2
(1.3)
8.0
4.8
10.4
(1.7)
Switzerland
1.8
0.3
3.5
(1.8)
6.1
1.7
9.0
(1.6)
Unemployment rate (end-of
 
-period level, %)
United States
3.0
3.9
6.1
10.9
3.0
3.5
7.2
10.8
Eurozone
6.2
7.4
8.7
12.9
6.0
7.2
9.1
15.1
Switzerland
2.3
2.5
3.4
5.2
1.6
2.3
4.2
5.9
Fixed income: 10-year government
 
bonds (change in yields, basis points)
USD
50.0
16.5
259.2
(50.0)
170.0
41.2
329.2
(15.0)
EUR
40.0
11.1
283.8
(35.0)
140.0
34.9
349.3
(25.0)
CHF
50.0
12.1
245.5
(70.0)
150.0
34.4
307.3
(35.0)
Equity indices (% change)
S&P 500
12.0
14.1
(27.0)
(50.2)
35.5
24.7
(21.8)
(40.1)
EuroStoxx 50
16.0
12.3
(23.4)
(57.6)
41.6
20.7
(19.9)
(50.4)
SPI
14.0
12.1
(22.9)
(53.6)
37.9
19.1
(19.6)
(44.2)
Swiss real estate (% change)
Single-Family Homes
 
5.1
4.4
(4.3)
(17.0)
15.5
7.4
(8.8)
(30.0)
Other real estate (% change)
United States (S&P / Case–Shiller)
10.0
3.5
(2.3)
(9.5)
21.7
7.1
(8.7)
(26.3)
Eurozone (House Price Index)
8.4
5.1
(4.0)
(5.4)
17.8
9.6
(7.6)
(10.8)
c) Development of ECL allowances
 
and provisions
 
The ECL allowances and provisions
 
recognized in the period
 
are impacted by a variety of factors,
 
such as:
–
 
the effect of selecting and
 
updating forward-looking scenarios
 
and the respective weights;
–
 
origination of new instruments during
 
the period;
 
–
 
the effect
 
of passage of
 
time (lower residual
 
lifetime PD and the
 
effect of discount
 
unwind) as the
 
ECL on an
 
instrument
for the remaining lifetime decreases (all other
 
factors remaining the same);
–
 
derecognition of instruments in the
 
period;
–
 
change in individual asset quality of instruments;
–
 
movements from
 
a
 
maximum
 
12-month
 
ECL
 
to
 
the
 
recognition
 
of
 
lifetime ECL
 
(and
 
vice versa)
 
following
 
transfers
between stages 1 and 2;
 
–
 
movements from stages 1 and 2 to stage 3 (credit-impaired status) when default has become certain and PD increases
to 100% (or vice versa);
–
 
changes in models or updates
 
to model parameters;
–
 
write-off; and
–
 
foreign exchange translations for assets denominated
 
in foreign currencies.
The
 
table
 
below
 
explains
 
the
 
changes
 
in
 
the
 
ECL
 
allowances
 
and
 
provisions
 
for
 
on-
 
and
 
off-balance
 
sheet
 
financial
instruments and credit
 
lines in scope of ECL
 
requirements
 
between the beginning
 
and the end of the
 
period due
 
to the
factors listed above.
Development of ECL allowances
 
and provisions
USD m
Total
Stage 1
Stage 2
Stage 3
Balance as of 31 December 2021
(1,165)
(282)
(220)
(662)
Net movement from new and derecognized
 
transactions
1
(7)
(21)
16
(2)
of which: Private clients with mortgages
(6)
(6)
0
0
of which: Real estate financing
(3)
(5)
2
0
of which: Large corporate clients
8
(1)
11
(2)
of which: SME clients
(1)
(1)
0
0
of which: Other
(6)
(8)
3
0
 
of which: Financial intermediaries and hedge
 
funds
0
(2)
2
0
 
of which: Loans to financial advisors
0
0
0
0
Remeasurements with stage transfers
2
(65)
20
(39)
(46)
of which: Private clients with mortgages
(10)
3
(12)
0
of which: Real estate financing
7
(1)
8
0
of which: Large corporate clients
(33)
16
(28)
(21)
of which: SME clients
(23)
2
(2)
(22)
of which: Other
(6)
1
(4)
(3)
 
of which: Financial intermediaries and hedge
 
funds
0
0
0
0
 
of which: Loans to financial advisors
1
2
(1)
0
Remeasurements without
 
stage transfers
3
13
(8)
(27)
48
of which: Private clients with mortgages
(12)
5
(18)
1
of which: Real estate financing
13
3
10
0
of which: Large corporate clients
32
(11)
2
41
of which: SME clients
(6)
(10)
(9)
14
of which: Other
(15)
5
(12)
(8)
 
of which: Sovereigns
(8)
0
(8)
0
 
of which: Loans to financial advisors
(3)
3
(1)
(6)
Model changes
4
30
29
1
0
Movements with profit or loss impact
5
(29)
20
(49)
0
Movements without profit or loss impact
 
(write-off,
 
FX and other)
6
104
3
1
99
Balance as of 31 December 2022
(1,091)
(259)
(267)
(564)
1 Represents
 
the increase
 
and decrease
 
in allowances
 
and provisions
 
resulting from
 
financial instruments
 
(including guarantee
 
s
 
and facilities)
 
that were
 
newly originated,
 
purchased or
 
renewed and
 
from the
 
final
derecognition of loans or facilities on their maturity date or earlier.
 
2 Represents the remeasurement between 12
 
-month and lifetime ECL due to stage transfers.
 
3 Represents the change in allowances and provisions
related to
 
changes
 
in model
 
inputs
 
or assumptions,
 
including
 
changes
 
in forward
 
-looking
 
macroeconomic
 
conditions,
 
changes
 
in the
 
exposure
 
profile,
 
PD and
 
LGD
 
changes,
 
and
 
unwinding
 
of the
 
time
 
value.
 
4 Represents the change in the allowances
 
and provisions related to changes
 
in models and methodologies.
 
5 Includes ECL movements
 
from new and derecognized transactions,
 
remeasurement changes,
 
model and
methodology changes.
 
6 Represents
 
the decrease
 
in allowances
 
and provisions
 
resulting from
 
write-offs of
 
the ECL
 
allowance
 
against the
 
gross carrying
 
amount when
 
all or
 
part of
 
a financial
 
asset is
 
deemed
uncollectible or forgiven and
 
movements in foreign exchange
 
rates.
Movements with profit
 
or loss
 
impact:
Stages 1
 
and 2 ECL
 
allowances and provisions increased
 
on a net
 
basis by
 
USD
29
m:
 
–
 
Net movement
 
from new
 
and derecognized
 
transactions
 
includes USD
21
m stage 1
 
expenses and
 
USD
16
m stage 2
releases: Stage 1 expenses are primarily driven by new loans secured by real estate. The residual
 
effect is spread across
lending segments. Stage 2
 
releases are largely driven by redemption of
 
corporate loans in the
 
Investment Bank.
–
 
Remeasurements with
 
stage transfers
 
include USD
20
m releases
 
in stage
 
1 and
 
USD
39
m expenses
 
in stage
 
2.
 
This
mainly includes
 
the transfer of
 
a few
 
large corporate
 
lending
 
transactions in
 
the Investment
 
Bank
 
from stage
 
1 to
 
2
(i.e., releases in
 
stage 1
 
and related but
 
generally higher
 
expenses in stage
 
2), driven by
 
rating downgrades and scenario
effects.
–
 
Remeasurements
 
without
 
stage
 
transfers
 
include
 
stage
 
1
 
expenses
 
of
 
USD
8
m
 
and stage
 
2 expenses
 
of
 
USD
27
m.
These expenses of
 
USD
35
m relate
 
to large and
 
SME corporate lending
 
(USD
28
m), substantially
 
due to scenario
 
effects,
and to a single sovereign
 
counterparty (USD
8
m).
 
–
 
Model changes: refer to Note
 
19b for more information.
Movements without profit or loss impact:
Stage 3 allowances decreased by USD
99
m almost entirely due to write-offs of
USD
95
m.
Development of ECL allowances
 
and provisions
USD m
Total
Stage 1
Stage 2
Stage 3
Balance as of 31 December 2020
(1,468)
(306)
(333)
(829)
Net movement from new and derecognized
 
transactions
1
(59)
(72)
13
0
of which: Private clients with mortgages
(7)
(10)
3
0
of which: Real estate financing
(7)
(11)
4
0
of which: Large corporate clients
(13)
(21)
7
0
of which: SME clients
(8)
(8)
0
0
of which: Other
(24)
(23)
(2)
0
 
of which: Financial intermediaries and hedge
 
funds
(21)
(18)
(4)
0
 
of which: Loans to financial advisors
0
(1)
1
0
Remeasurements with stage transfers
2
(40)
8
0
(49)
of which: Private clients with mortgages
(9)
4
(13)
0
of which: Real estate financing
(3)
1
(4)
0
of which: Large corporate clients
2
(2)
12
(8)
of which: SME clients
(27)
5
4
(36)
of which: Other
(3)
0
2
(4)
 
of which: Financial intermediaries and hedge
 
funds
2
(1)
3
0
 
of which: Loans to financial advisors
0
1
(1)
0
Remeasurements without
 
stage transfers
3
203
55
74
74
of which: Private clients with mortgages
33
8
26
(1)
of which: Real estate financing
30
13
13
3
of which: Large corporate clients
44
5
21
17
of which: SME clients
53
(1)
1
53
of which: Other
44
29
14
2
 
of which: Financial intermediaries and hedge
 
funds
27
15
12
0
 
of which: Loans to financial advisors
6
8
1
(3)
Model changes
4
45
29
16
0
Movements with profit or loss impact
5
148
19
104
25
Movements without profit or loss impact
 
(write-off, FX
 
and other)
6
154
5
9
141
Balance as of 31 December 2021
(1,165)
(282)
(220)
(662)
1 Represents
 
the increase
 
and decrease
 
in allowances
 
and provisions
 
resulting from
 
financial instruments
 
(including guarantee
 
s
 
and facilities)
 
that were
 
newly originated,
 
purchased or
 
renewed and
 
from the
 
final
derecognition of loans or facilities on their maturity date or earlier.
 
2 Represents the remeasurement between 12
 
-month and lifetime ECL due to stage transfers.
 
3 Represents the change in allowances and provisions
related to
 
changes
 
in model
 
inputs
 
or assumptions,
 
including
 
changes
 
in forward
 
-looking
 
macroeconomic
 
conditions,
 
changes
 
in the
 
exposure
 
profile,
 
PD and
 
LGD
 
changes,
 
and
 
unwinding
 
of the
 
time
 
value.
 
4 Represents the change in the allowances
 
and provisions related to changes
 
in models and methodologies.
 
5 Includes ECL movements
 
from new and derecognized
 
transactions, remeasurement
 
changes, model and
methodology changes.
 
6 Represents
 
the decrease
 
in allowa
 
nces and
 
provisions resulting
 
from write
 
-offs of
 
the ECL
 
allowance
 
against the
 
gross carrying
 
amount when
 
all or
 
part of
 
a financial
 
asset is
 
deemed
uncollectible or forgiven and
 
movements in foreign exchange
 
rates.
As explained
 
in Note 1a,
 
the assessment
 
of a significant
 
increase
 
in credit
 
risk (SICR)
 
considers a
 
number
 
of qualitative
and
 
quantitative factors
 
to determine
 
whether a
 
stage transfer
 
between
 
stage 1
 
and stage 2
 
is required,
 
although the
primary assessment considers changes in PD based
 
on rating analyses and economic
 
outlook. Additionally,
 
UBS takes into
consideration counterparties
 
that have
 
moved to
 
a credit
 
watch list
 
and those
 
with payments
 
that are
 
at least
 
30 days
past due.
ECL stage 2 (“significant deterioration
 
in credit risk”) allowances / provisions
 
as of 31 December 2022 – classification by trigger
USD m
Stage 2
of which:
PD layer
of which:
watch list
of which:
≥30 days
 
past due
On-
 
and off-balance sheet
 
(267)
(196)
(21)
(50)
of which: Private clients with mortgages
(107)
(83)
0
(25)
of which: Real estate financing
(23)
(18)
0
(5)
of which: Large corporate clients
(65)
(51)
(13)
0
of which: SME clients
(37)
(22)
(7)
(7)
of which: Financial intermediaries and hedge funds
(17)
(17)
0
0
of which: Loans to financial advisors
(2)
0
0
(2)
of which: Credit cards
(12)
0
0
(12)
of which: Other
(5)
(5)
0
0
d) Maximum exposure to credit risk
The
 
tables
 
below
 
provide
 
the
 
Group’s
 
maximum
 
exposure
 
to
 
credit
 
risk
 
for
 
financial
 
instruments
 
subject
 
to
 
ECL
requirements
 
and
 
the
 
respective
 
collateral
 
and
 
other
 
credit
 
enhancements
 
mitigating
 
credit
 
risk
 
for
 
these
 
classes
 
of
financial instruments.
 
The maximum exposure
 
to credit risk
 
includes the
 
carrying amounts
 
of financial instruments
 
recognized on
 
the balance
sheet subject to credit risk
 
and the notional amounts for off-balance sheet arrangements. Where information is available,
collateral is presented
 
at fair value. For other collateral,
 
such as real estate,
 
a reasonable alternative
 
value is used. Credit
enhancements,
 
such
 
as
 
credit
 
derivative
 
contracts
 
and
 
guarantees,
 
are
 
included
 
at
 
their
 
notional
 
amounts.
 
Both
 
are
capped
 
at the
 
maximum exposure
 
to credit
 
risk for
 
which they
 
serve as
 
security. The
 
“Risk
 
management and
 
control”
section of this
 
report describes
 
management’s view
 
of credit
 
risk and
 
the related exposures,
 
which can differ
 
in certain
respects from the requirements of International
 
Financial Reporting Standards
 
(IFRS).
Maximum exposure to credit
 
risk
 
31.12.22
Collateral
1,2
Credit enhancements
1
Exposure to
credit risk
after collateral
and credit
enhancements
USD bn
Maximum
exposure to
credit risk
Cash
collateral
received
Collateralized
by equity
 
and debt
instruments
 
Secured by
real estate
Other
collateral
3
Netting
Credit
derivative
contracts
Guarantees
 
Financial assets measured at
 
amortized cost on the balance sheet
Cash and balances at central banks
169.4
169.4
Loans and advances to banks
4
14.8
0.0
0.1
14.7
Receivables from securities financing transactions
measured at amortized cost
67.8
0.0
64.5
2.4
0.9
Cash collateral receivables on derivative
 
instruments
5,6
35.0
22.9
12.1
Loans and advances to customers
387.2
33.6
115.9
197.8
19.6
3.0
17.3
Other financial assets measured at amortized cost
53.3
0.1
0.5
0.0
1.3
51.3
Total financial assets
 
measured at amortized cost
727.6
33.7
181.0
197.9
23.4
22.9
0.0
3.0
265.8
Financial assets measured at
 
fair value
 
through other comprehensive income – debt
2.2
2.2
Total maximum exposure to
 
credit risk
 
reflected on the balance sheet within
 
the scope of ECL
729.8
33.7
181.0
197.9
23.4
22.9
0.0
3.0
268.0
Guarantees
7
22.1
1.2
9.3
0.1
2.0
1.8
7.7
Loan commitments
7
39.9
0.2
3.1
1.3
6.5
0.1
1.0
27.8
Forward starting transactions,
 
reverse repurchase
and securities borrowing agreements
3.8
3.8
0.0
Committed unconditionally revocable credit lines
41.4
0.2
8.2
6.0
6.2
0.5
20.2
Total maximum exposure to
 
credit risk not
 
reflected on the balance sheet within
 
the scope of ECL
107.2
1.6
24.4
7.5
14.7
0.0
0.1
3.3
55.7
31.12.21
Collateral
1,2
Credit enhancements
1
Exposure to
credit risk
after collateral
and credit
enhancements
USD bn
Maximum
exposure to
credit risk
Cash
collateral
received
Collateralized
by equity
 
and debt
instruments
 
Secured by
real estate
Other
collateral
3
Netting
Credit
derivative
contracts
Guarantees
 
Financial assets measured at
 
amortized cost on the balance sheet
Cash and balances at central banks
192.8
192.8
Loans and advances to banks
4
15.5
0.1
0.1
15.3
Receivables from securities financing transactions
measured at amortized cost
75.0
0.0
68.0
6.9
0.0
Cash collateral receivables on derivative
 
instruments
5,6
30.5
18.4
12.1
Loans and advances to customers
397.8
37.5
128.7
191.3
20.2
4.0
16.2
Other financial assets measured at amortized cost
26.2
0.2
0.1
0.0
1.3
24.6
Total financial assets
 
measured at amortized cost
737.8
37.7
196.9
191.3
28.4
18.4
0.0
4.0
261.0
Financial assets measured at
 
fair value
 
through other comprehensive income – debt
8.8
8.8
Total maximum exposure to
 
credit risk
 
reflected on the balance sheet within
 
the scope of ECL
746.6
37.7
196.9
191.3
28.4
18.4
0.0
4.0
269.8
Guarantees
7
20.9
1.3
6.5
0.2
2.5
2.3
8.1
Loan commitments
7
39.4
0.5
4.0
2.4
7.3
0.3
1.7
23.1
Forward starting transactions,
 
reverse repurchase
and securities borrowing agreements
1.4
1.4
0.0
Committed unconditionally revocable credit lines
40.7
0.3
9.0
6.2
3.9
0.5
20.9
Total maximum exposure to
 
credit risk not
 
reflected on the balance sheet within
 
the scope of ECL
102.5
2.2
20.9
8.7
13.7
0.0
0.3
4.5
52.1
1 Of which: USD
1,372
m for 31 December 2022 (31 December 2021: USD
1,443
m) relates to total credit-impaired financial assets measured
 
at amortized cost and USD
113
m for 31 December 2022 (31 December
 
2021:
USD
130
m) to total off-balance sheet financial instruments and credit lines for credit-impaired positions.
 
2 Collateral arrangements generally incorporate
 
a range of collateral, including cash, equity and debt instruments,
real estate and other collateral. UBS
 
applies a risk-based approach
 
that generally
 
prioritizes collateral according
 
to its liquidity profile.
 
3 Includes but is not limited to
 
life insurance contracts,
 
inventory,
 
mortgage loans,
gold and other commodities.
 
4 Loans and advances
 
to banks include amounts held with
 
third-party banks on
 
behalf of clients. The
 
credit risk associated with these
 
balances may be borne by those clients.
 
5 Included
within Cash collateral
 
receivables on derivative
 
instruments are
 
margin balances
 
due from exchanges
 
or clearing houses.
 
Some
 
of these margin
 
balances reflect
 
amounts transferred on
 
behalf of clients
 
who retain the
associated credit
 
risk.
 
6 The
 
amount shown
 
in the
 
“Netting” column
 
represents the
 
netting potential
 
not recognized
 
on the
 
balance sheet.
 
Refer to
 
Note 21
 
for more
 
information.
 
7 The
 
amount
 
shown in
 
the
“Guarantees” column includes
 
sub-participations.
e) Financial assets subject to credit risk
 
by rating category
The table below
 
shows the
 
credit quality and
 
the maximum exposure
 
to credit risk
 
based
 
on the Group’s
 
internal credit
rating system and year-end stage classification. Under IFRS 9, the credit risk rating reflects the Group’s assessment of the
probability of default of individual counterparties,
 
prior to substitutions. The amounts presented are gross
 
of impairment
allowances.
›
 
Refer to the “Risk
 
management and
 
control” section of
 
this report for more
 
details regarding the
 
Group’s internal grading system
Financial assets subject to credit risk by
 
rating category
USD m
31.12.22
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total gross
carrying
amount
ECL
allowances
Net carrying
amount
(maximum
exposure to
credit risk)
Financial assets measured at amortized
 
cost
Cash and balances at central banks
168,525
877
0
0
56
0
169,457
(12)
169,445
of which: stage 1
168,525
877
0
0
0
0
169,402
0
169,402
of which: stage 2
0
0
0
0
56
0
56
(12)
44
Loans and advances to banks
862
12,257
860
440
379
0
14,798
(6)
14,792
of which: stage 1
862
12,257
860
440
378
0
14,797
(5)
14,792
of which: stage 2
0
0
0
0
1
0
1
(1)
1
of which: stage 3
0
0
0
0
0
0
0
0
0
Receivables from securities
 
financing transactions measured at
amortized cost
27,158
15,860
8,870
15,207
721
0
67,816
(2)
67,814
of which: stage 1
27,158
15,860
8,870
15,207
721
0
67,816
(2)
67,814
Cash collateral receivables on
 
derivative instruments
10,613
12,977
7,138
4,157
147
0
35,033
0
35,032
of which: stage 1
10,613
12,977
7,138
4,157
147
0
35,033
0
35,032
Loans and advances to customers
6,491
214,473
68,356
74,732
21,939
2,012
388,003
(783)
387,220
of which: stage 1
6,491
212,980
66,114
68,034
16,605
0
370,224
(129)
370,095
of which: stage 2
0
1,493
2,242
6,698
5,334
0
15,767
(180)
15,587
of which: stage 3
0
0
0
0
0
2,012
2,012
(474)
1,538
Other financial assets measured at
 
amortized cost
29,011
16,632
447
6,600
450
210
53,350
(86)
53,264
of which: stage 1
29,011
16,630
427
6,317
336
0
52,721
(17)
52,704
of which: stage 2
0
2
20
283
114
0
419
(6)
413
of which: stage 3
0
0
0
0
0
210
210
(63)
147
Total financial assets
 
measured at amortized cost
242,660
273,076
85,671
101,136
23,693
2,222
728,457
(889)
727,568
On-balance sheet financial instruments
Financial assets measured at FVOCI
 
– debt instruments
1,307
840
0
92
0
0
2,239
0
2,239
Total on-balance
 
sheet financial instruments
243,966
273,916
85,671
101,228
23,693
2,222
730,696
(889)
729,807
Off-balance sheet positions subject to expected
 
credit loss by rating category
USD m
31.12.22
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total off-
balance sheet
exposure
(maximum
exposure to
credit risk)
ECL provisions
Off-balance sheet financial instruments
Guarantees
 
7,252
5,961
4,772
3,049
1,025
108
22,167
(48)
of which: stage 1
7,252
5,917
3,812
2,229
596
0
19,805
(13)
of which: stage 2
0
44
960
821
429
0
2,254
(9)
of which: stage 3
0
0
0
0
0
108
108
(26)
Irrevocable loan commitments
1,770
14,912
6,986
10,097
6,107
124
39,996
(111)
of which: stage 1
1,770
14,789
6,818
9,625
4,529
0
37,531
(59)
of which: stage 2
0
123
168
472
1,578
0
2,341
(52)
of which: stage 3
0
0
0
0
0
124
124
0
Forward starting reverse repurchase
 
and securities borrowing agreements
2,781
2
11
1,007
0
0
3,801
0
Total off-balance sheet
 
financial instruments
11,803
20,874
11,769
14,153
7,132
233
65,964
(159)
Credit lines
Committed unconditionally revocable
 
credit lines
2,288
15,918
9,247
10,162
3,739
36
41,390
(40)
of which: stage 1
2,288
15,213
8,960
9,631
3,429
0
39,521
(32)
of which: stage 2
0
705
287
531
310
0
1,833
(8)
of which: stage 3
0
0
0
0
0
36
36
0
Irrevocable committed prolongation
 
of existing loans
7
1,939
1,489
868
392
2
4,696
(2)
of which: stage 1
7
1,938
1,411
864
380
0
4,600
(2)
of which: stage 2
0
1
78
4
11
0
94
0
of which: stage 3
0
0
0
0
0
2
2
0
Total credit lines
2,295
17,857
10,736
11,030
4,131
37
46,086
(42)
1 Refer to the “Internal UBS rating
 
scale and mapping of external
 
ratings” table in the “Risk
 
management and control”
 
section of this report for
 
more information on rating
 
categories.
Financial assets subject to credit risk by
 
rating category
USD m
31.12.21
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total gross
carrying
amount
ECL
allowances
Net carrying
amount
(maximum
exposure to
credit risk)
Financial assets measured at amortized
 
cost
Cash and balances at central banks
191,015
1,802
0
0
0
0
192,817
0
192,817
of which: stage 1
191,015
1,802
0
0
0
0
192,817
0
192,817
Loans and advances to banks
407
12,623
1,171
795
490
1
15,488
(8)
15,480
of which: stage 1
407
12,623
1,146
795
488
0
15,460
(7)
15,453
of which: stage 2
0
0
24
0
2
0
27
(1)
26
of which: stage 3
0
0
0
0
0
1
1
0
1
Receivables from securities
 
financing transactions
measured at amortized cost
34,386
11,267
10,483
17,440
1,439
0
75,014
(2)
75,012
of which: stage 1
34,386
11,267
10,483
17,440
1,439
0
75,014
(2)
75,012
Cash collateral receivables on
 
derivative instruments
7,466
13,476
5,878
3,647
47
0
30,514
0
30,514
of which: stage 1
7,466
13,476
5,878
3,647
47
0
30,514
0
30,514
Loans and advances to customers
5,295
232,233
67,620
69,892
21,423
2,148
398,611
(850)
397,761
of which: stage 1
5,295
231,153
65,084
62,796
16,362
0
380,690
(126)
380,564
of which: stage 2
0
1,080
2,536
7,096
5,061
0
15,773
(152)
15,620
of which: stage 3
0
0
0
0
0
2,148
2,148
(572)
1,577
Other financial assets measured at
 
amortized cost
12,564
6,702
321
6,072
394
264
26,318
(109)
26,209
of which: stage 1
12,564
6,693
307
5,863
317
0
25,745
(27)
25,718
of which: stage 2
0
10
13
209
77
0
309
(7)
302
of which: stage 3
0
0
0
0
0
264
264
(76)
189
Total financial assets
 
measured at amortized cost
251,133
278,103
85,472
97,846
23,793
2,414
738,762
(969)
737,794
On-balance sheet financial instruments
Financial assets measured at FVOCI
 
– debt instruments
3,996
4,771
0
77
0
0
8,844
0
8,844
Total on-balance
 
sheet financial instruments
255,130
282,874
85,472
97,923
23,793
2,414
747,606
(969)
746,638
Off-balance sheet positions subject to expected
 
credit loss by rating category
USD m
31.12.21
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total off-
balance sheet
exposure
(maximum
exposure to
credit risk)
ECL provisions
Off-balance sheet financial instruments
Guarantees
 
4,457
7,064
4,535
3,757
1,009
150
20,972
(41)
of which: stage 1
4,457
7,037
4,375
3,075
752
0
19,695
(18)
of which: stage 2
0
27
160
682
258
0
1,127
(8)
of which: stage 3
0
0
0
0
0
150
150
(15)
Irrevocable loan commitments
2,797
14,183
7,651
8,298
6,502
46
39,478
(114)
of which: stage 1
2,797
13,917
7,416
7,127
5,840
0
37,097
(72)
of which: stage 2
0
266
235
1,171
663
0
2,335
(42)
of which: stage 3
0
0
0
0
0
46
46
0
Forward starting reverse repurchase
 
and securities borrowing agreements
0
0
55
1,389
0
0
1,444
0
Total off-balance sheet
 
financial instruments
7,254
21,247
12,241
13,444
7,512
196
61,894
(155)
Credit lines
Committed unconditionally revocable
 
credit lines
2,636
15,594
8,627
9,752
4,107
63
40,778
(38)
of which: stage 1
2,636
15,250
8,304
8,346
3,671
0
38,207
(28)
of which: stage 2
0
344
323
1,406
436
0
2,508
(10)
of which: stage 3
0
0
0
0
0
63
63
0
Irrevocable committed prolongation
 
of existing loans
17
2,438
1,422
1,084
602
48
5,611
(3)
of which: stage 1
17
2,438
1,422
1,082
568
0
5,527
(3)
of which: stage 2
0
0
0
1
34
0
36
0
of which: stage 3
0
0
0
0
0
48
48
0
Total credit lines
2,653
18,032
10,049
10,836
4,709
111
46,390
(41)
1 Refer to the “Internal UBS rating
 
scale and mapping of external
 
ratings” table in the “Risk
 
management and control”
 
section of this report for more
 
information on rating categories.
f) Sensitivity information
As outlined in Note
 
1a, ECL estimates involve significant uncertainties at the
 
time they are made.
ECL models
The models
 
applied
 
to determine
 
point
 
-in-time
 
PD and LGD
 
rely on
 
market and statistical
 
data, which
 
has been
 
found
to
 
correlate
 
well
 
with
 
historically
 
observed
 
defaults
 
in
 
sufficiently
 
homogeneous
 
segments.
 
The
 
risk
 
sensitivities
 
for
each of the
 
ECL reporting
 
segments
 
to such
 
factors are
 
summarized
 
in Note 9.
Sustainability and climate risk
 
Sustainability and climate risk (SCR) may negatively affect clients
 
or portfolios due to direct or indirect transition costs, or
exposure to physical risks in locations
 
likely to be impacted by climate change.
 
Such effects could lead to
 
a deterioration
in credit worthiness, which in turn would
 
have an impact on ECLs.
 
While some indicators
 
that are more
 
influenced by
 
climate change (e.g.,
 
energy prices) are
 
factored into the
 
current PD
models where they have demonstrated statistical
 
relevance, UBS currently does not use a
 
specific SCR scenario in
 
addition
to the four
 
general economic
 
scenarios
 
applied to
 
derive the
 
weighted-average
 
ECL. The
 
rationale for
 
the approach
 
at
this point in time is the significance of model risks and
 
challenges in calibration and
 
probability weight assessment given
the paucity of data.
Instead,
 
UBS
 
focuses
 
on
 
the
 
process
 
of
 
vetting
 
clients
 
and
 
business
 
transactions
 
and
 
takes
 
individual
 
actions,
 
where
transition risk is deemed
 
to be a significant
 
driver of a
 
counterparty’s credit worthiness.
 
This review process may
 
lead to
a downward revision
 
of the counterparty’s credit rating,
 
or the adoption of risk mitigating
 
actions, and hence affect the
individual contribution to ECLs.
At the portfolio
 
level, UBS
 
has started
 
to use
 
stress loss
 
assumptions to
 
assess the
 
extent to
 
which SCR
 
may affect
 
the
quality of the
 
loans extended
 
to small and
 
medium-sized entities and
 
large corporate clients.
 
Initial tests were
 
based on
a set of assumptions presented
 
by external parties (such as the Bank of
 
England). Such analysis undertaken
 
during 2022
concluded that the counterparties
 
are not expected to be
 
significantly impacted
 
by physical or transition
 
risks, mainly as
there are no material risk concentrations in high-risk sectors. The
 
analysis of the corporate loan book has also shown that
any potential significant impacts from transition costs or
 
physical risks would materialize over a
 
time horizon that exceeds
in most cases the
 
contractual lifetime of the
 
underlying assets. Based on current information
 
on regulatory developments,
this would
 
also apply
 
to the portfolio
 
of private
 
clients’ mortgages
 
and real
 
estate financing,
 
given the long
 
lead times
for investments in upgrading
 
the housing stock.
As a
 
result of
 
the aforementioned
 
factors, it
 
was assessed
 
that the
 
magnitude of
 
any impact
 
of SCR
 
on the
 
weighted-
average ECL would not be material as of 31 December 2022. Therefore, no specific post-model adjustment
 
was made in
this regard.
›
 
Refer to “Sustainability
 
and climate risk”
 
in the “Risk management
 
and control” section
 
of this report
 
›
 
Refer to “Our focus
 
on sustainability
 
and climate”
 
in the “Our strategy, business
 
model and environment”
 
section of this
 
report
›
 
Refer to “UBS AG consolidated
 
supplemental disclosures
 
required under SEC regulations”
 
for the maturity
 
profile of UBS core loan
book
 
Forward-looking scenarios
Depending
 
on
 
the scenario
 
selection and
 
related macroeconomic
 
assumptions
 
for the
 
risk factors,
 
the components
 
of
the
 
relevant
 
weighted-average
 
ECL
 
change.
 
This
 
is
 
particularly
 
relevant
 
for
 
interest
 
rates,
 
which
 
can
 
move
 
in
 
both
directions under
 
a given growth
 
assumption,
 
e.g., low
 
growth with
 
high interest
 
rates in
 
a stagflation
 
scenario, versus
low growth
 
and falling interest
 
rates in a
 
recession. Management
 
generally looks
 
for scenario narratives that reflect
 
the
key risk drivers of a given credit
 
portfolio.
As forecasting
 
models are complex,
 
due to the
 
combination of
 
multiple factors, simple what-if
 
analyses involving a
 
change
of individual
 
parameters do not
 
necessarily provide realistic information
 
on the
 
exposure of segments
 
to changes
 
in the
macroeconomy.
 
Portfolio-specific
 
analyses
 
based
 
on
 
their key
 
risk
 
factors
 
would
 
also
 
not
 
be
 
meaningful,
 
as
 
potential
compensatory effects in other segments
 
would be ignored.
 
The table below indicates some sensitivities
 
to ECLs, if a key
macroeconomic
 
variable
 
for
 
the
 
forecasting
 
period
 
is
 
amended
 
across
 
all
 
scenarios
 
with
 
all
 
other
 
factors
 
remaining
unchanged.
Potential effect on stage
 
1 and stage 2 positions from changing key
 
parameters as of 31 December 2022
USD m
100% Baseline
100%
Stagflationary
geopolitical crisis
 
100% Global crisis
 
Weighted average
 
Change in key parameters
Fixed income: Government bonds
 
(absolute change)
–0.50%
(3)
(106)
(2)
(14)
+0.50%
4
124
2
17
+1.00%
8
264
10
37
Unemployment rate (absolute change)
–1.00%
(4)
(138)
(24)
(23)
–0.50%
(2)
(78)
(13)
(12)
+0.50%
3
84
16
15
+1.00%
5
179
32
31
Real GDP growth (relative change)
–2.00%
7
13
18
11
–1.00%
3
7
9
5
+1.00%
(3)
(7)
(9)
(5)
+2.00%
(5)
(13)
(18)
(10)
House Price Index (relative change)
–5.00%
15
196
88
56
–2.50%
7
92
40
25
+2.50%
(4)
(83)
(35)
(19)
+5.00%
(7)
(157)
(65)
(36)
Equity (S&P500, EuroStoxx, SMI)
 
(relative change)
–10.00%
4
7
6
5
–5.00%
2
3
3
2
+5.00%
(2)
(4)
(3)
(2)
+10.00%
(4)
(8)
(7)
(5)
Sensitivities
 
can
 
be
 
more
 
meaningfully
 
assessed
 
in
 
the
 
context
 
of
 
coherent
 
scenarios
 
with
 
consistently
 
developed
macroeconomic
 
factors.
 
The
 
table
 
above
 
outlines
 
favorable
 
and
 
unfavorable
 
effects,
 
based
 
on
 
reasonably
 
possible
alternative changes to
 
the economic conditions
 
for stage 1 and
 
stage 2 positions. The
 
ECL impact
 
is calculated for
 
material
portfolios and disclosed for each
 
scenario.
 
The forecasting horizon is limited to three years, with a model
 
-based mean reversion of PD and LGD assumed thereafter.
Changes to these timelines may have
 
an effect on ECLs: depending
 
on the cycle, a longer or shorter forecasting horizon
will lead to different annualized lifetime PD and average LGD estimations. This is currently not deemed to be material for
UBS,
 
as a large proportion
 
of loans,
 
including mortgages
 
in Switzerland, have
 
maturities that are
 
within the
 
forecasting
horizon.
Scenario weights and stage allocation
 
Potential effect
 
on stage 1 and stage
 
2 positions from
 
changing scenario
 
weights or moving to
 
an ECL lifetime
 
calculation
 
as of 31 December
 
2022
Actual ECL
allowances and
provisions,
including staging
(as per Note 9)
 
Pro forma ECL allowances and provisions,
 
including staging
 
and assuming application of 100% scenario weighting
 
Pro forma ECL
allowances and
provisions,
assuming all
positions being
subject to lifetime
ECL
 
Scenarios
Weighted average
100% Baseline
100% Asset price
inflation
100%
Stagflationary
geopolitical crisis
 
100% Global crisis
 
Weighted average
USD m, except where indicated
Segmentation
Private clients with mortgages
(136)
(25)
(13)
(523)
(184)
(473)
Real estate financing
(43)
(26)
(22)
(176)
(30)
(126)
Large corporate clients
(136)
(97)
(84)
(199)
(174)
(235)
SME clients
(86)
(67)
(66)
(162)
(97)
(153)
Other segments
(125)
(114)
(111)
(145)
(153)
(281)
Total
(526)
(329)
(295)
(1,204)
(638)
(1,267)
Scenario weights
ECL is sensitive to changing scenario weights,
 
in particular if narratives and parameters are
 
selected that are not close to
the baseline scenario, highlighting
 
the non-linearity of credit losses.
As
 
shown
 
in the
 
table
 
above,
 
the
 
ECLs
 
for stage 1
 
and
 
stage 2
 
positions
 
would
 
have been
 
USD
329
m (31
 
December
2021:
 
USD
387
m)
 
instead of
 
USD
526
m
 
(31 December
 
2021:
 
USD
503
m)
 
if ECLs
 
had
 
been
 
determined
 
solely
 
on
 
the
baseline scenario
. The weighted-average ECL
 
therefore amounted
 
to
160
% (31 December 2021:
130
%) of the baseline
value. The effects of weighting
 
each of the four scenarios 100%
 
are shown in the table above.
Stage allocation and SICR
The determination
 
of what
 
constitutes an
 
SICR is
 
based on
 
management judgment,
 
as explained
 
in Note 1a.
 
Changing
the SICR trigger will have a direct effect on ECLs, as more or fewer positions would be subject to lifetime ECLs under any
scenario.
 
The
 
relevance of
 
the
 
SICR trigger
 
on
 
overall ECL
 
is
 
demonstrated
 
in
 
the table
 
above with
 
the
 
indication that
 
the
 
ECL
allowances and provisions
 
for stage 1 and stage 2 positions
 
would have been USD
1,267
m, if all non-impaired positions
across the
 
portfolio had been
 
measured for
 
lifetime ECLs irrespective of
 
their actual SICR
 
status. This
 
amount compares
with actual stage 1 and 2
 
allowances and provisions of USD
526
m as of 31 December 2022.
Maturity profile
The maturity
 
profile is
 
an important
 
driver in
 
ECLs, in
 
particular for
 
transactions
 
in stage
 
2.
 
A transfer
 
of a
 
transaction
into stage
 
2 may
 
therefore have a
 
significant effect on ECLs.
 
The current maturity
 
profile of most
 
lending books is relatively
short.
 
Lending
 
to large
 
corporate clients
 
is generally
 
between
 
one
 
and two
 
years, with
 
related loan
 
commitments up
 
to four
years. Real estate lending is generally between
 
two and three years in Switzerland, with long
 
dated maturities in the US.
Lombard-lending
 
contracts
 
typically
 
have
 
average
 
contractual
 
maturities
 
of
 
12
 
months
 
or
 
less,
 
and
 
include
 
callable
features.
A
 
significant
 
portion
 
of
 
our
 
lending
 
to
 
SMEs
 
and
 
Real
 
estate
 
financings
 
is
 
documented
 
under
 
multi-purpose
 
credit
agreements,
 
which allow
 
for various
 
forms of
 
utilization
 
but are
 
unconditionally cancelable
 
by UBS
 
at any
 
time: a)
 
for
drawings under such agreements with a fixed maturity, the respective term is
 
applied for ECL calculations, or a maximum
of 12 months in stage
 
1; b) for unused
 
credit lines and all drawings
 
that have no fixed
 
maturity (e.g., current
 
accounts),
UBS generally applies a 12-month maturity from the reporting
 
date, given the credit review policies, which require either
continuous monitoring of key indicators and behavioral patterns
 
for smaller positions or an annual formal review for any
other limit. The ECLs for these products
 
are sensitive to shortening
 
or extending the maturity assumption.
UBS AG  
Entity [Table]  
Disclosure Of Financial Assets Explanatory
Additional information
Note 19
 
Expected credit loss measurement
 
 
a) Expected credit losses in the period
Total
 
net credit loss expenses
 
were USD
29
m in 2022, reflecting
 
net credit loss expenses
 
of USD
29
m related to stage 1
and 2 positions and USD
0
m net credit loss expenses related to credit-impaired
 
(stage 3) positions.
Stage 1
 
and
 
2
 
expected
 
credit
 
loss
 
(ECL)
 
expenses
 
of
 
USD
29
m
 
include
 
USD
123
m
 
expenses
 
related
 
to
 
scenario
 
and
parameter updates
 
and USD
13
m related to
 
other book quality and
 
size changes, partly offset
 
by USD
77
m post-model
adjustment (PMA) releases and
 
USD
30
m releases related to model changes. Lending to corporate clients not secured
 
by
mortgages contributed USD
21
m, mainly driven by scenario effects related to the
 
downward revision of GDP and
 
higher
interest rate
 
assumptions
 
in the
 
newly
 
introduced
stagflationary
 
geopolitical
 
crisis
 
scenario
 
(SGC).
 
Lending
 
secured
 
by
mortgages
 
contributed
 
USD
 
16
m
 
in
 
expenses
,
 
mainly
 
driven
 
by
 
scenario
 
ef
fects
 
related
 
to
 
higher
 
interest
 
rate
assumptions,
 
especially from the SGC, and adverse house price assumptions
 
from both applied downside scenarios.
 
This
was partly offset by releases from other lending
 
of USD
9
m.
›
 
Refer to Note 19b
 
for more information
 
regarding changes
 
to ECL models,
 
scenarios, scenario
 
weights and the
 
post-model
adjustment and to
 
Note 19c
 
for more information
 
regarding the development
 
of ECL allowances
 
and provisions
Stage 3 net expenses of USD
0
m were recognized across
 
a number of
 
defaulted positions, with net expenses of
 
USD
12
m
in Personal
 
and Corporate
 
Banking
 
and USD
5
m in
 
Global Wealth
 
Management,
 
offset by
 
releases of
 
USD
18
m in
 
the
Investment Bank, including a USD
28
m release for a single airline-related counterparty, mainly due to improved cashflow
assumptions, and USD
10
m net expenses across a number of defaulted positions.
Credit loss expense
 
/ (release)
USD m
Global
 
Wealth
 
Management
Personal &
 
Corporate
 
Banking
Asset
Management
Investment
 
Bank
Group
 
Functions
Total
For the year ended
 
31.12.22
Stages 1 and 2
(5)
27
0
6
1
29
Stage 3
5
12
0
(18)
2
0
Total credit loss expense /
 
(release)
0
39
0
(12)
3
29
For the year ended
 
31.12.21
Stages 1 and 2
(28)
(62)
0
(34)
0
(123)
Stage 3
(1)
(24)
1
0
0
(25)
Total credit loss expense /
 
(release)
(29)
(86)
1
(34)
0
(148)
For the year ended
 
31.12.20
Stages 1 and 2
48
129
0
88
0
266
Stage 3
40
128
2
217
42
429
Total credit loss expense /
 
(release)
88
257
2
305
42
695
b) Changes to ECL models,
 
scenarios, scenario
 
weights and key inputs
 
Refer
 
to
 
Note 1a for
 
information about
 
the
 
principles governing
 
expected
 
credit
 
loss (ECL)
 
models, scenarios,
 
scenario
weights and key inputs
 
applied.
 
Governance
Comprehensive cross-functional
 
and cross-divisional
 
governance processes
 
are in
 
place and
 
are used to
 
discuss and
 
approve
scenario updates and
 
weights, to
 
assess whether significant increases
 
in credit
 
risk resulted in
 
stage transfers, to
 
review
model outputs and to reach
 
conclusions regarding
 
post-model adjustments.
 
Model changes
During 2022, the model review and enhancement process led to adjustments
 
of the probability of default (PD), loss given
default (LGD), and
 
credit conversion factor
 
(CCF) models, resulting
 
in a USD
30
m decrease in
 
ECL allowances.
 
This includes
a
 
decrease of
 
USD
19
m
 
in Global
 
Wealth Management
 
affecting loans
 
to
 
financial advisors and
 
specialized US
 
lending
portfolios and
 
an USD
11
m decrease
 
in Personal
 
& Corporate
 
Banking
 
related to
 
lending to
large corporate clients
 
and
financial intermediaries
 
& hedge funds
.
 
Scenario and key input
 
updates
During 2022, the scenarios
 
and related macroeconomic factors were updated
 
from those applied
 
at the end of
 
2021 by
considering the
 
prevailing economic
 
and
 
political conditions
 
and
 
uncertainty. The review
 
focused
 
on events
 
that
 
significantly
changed the
 
economic
 
outlook during
 
the
 
year: the
 
Russia–Ukraine
 
war, with the subsequent
 
effect on
 
energy markets,
 
the
inflation outlook and economic growth in Europe, and rising global interest rates due to central banks’ adoption of more
restrictive monetary
 
policies.
Baseline scenario
: the
 
projections
 
of the
 
baseline scenario,
 
which are
 
aligned to
 
the economic
 
and market
 
assumptions
 
used
for UBS AG’s business planning purposes, are broadly
 
in line with external data, such as that from Bloomberg Consensus,
Oxford Economics and the International
 
Monetary Fund World Economic
 
Outlook. The expectation for
 
2023 is that global
growth stalls
 
under the
 
weight of
 
monetary
 
policy tightening,
 
and continued
 
pressure on
 
real purchasing
 
power due
 
to high
inflation – further fueled in Europe by the energy crisis and a lack of labor supply – even though unemployment rates are
forecast to be higher than in 2022 and an energy crisis in
 
Europe seems likely to be averted. Interest rates
 
are expected to
remain high,
 
given the persistence
 
of inflationary trends,
 
leading to a less
 
optimistic outlook for
 
global house prices,
 
which
is cushioned in Switzerland
 
by continued strong
 
demand.
 
Global crisis
 
scenario:
The first
 
hypothetical
 
downside scenario,
 
the global crisis
 
scenario, is
 
aligned with
 
the UBS AG’s
 
2022
binding stress scenario and was
 
updated in 2022
 
to reflect expected risks, resulting in
 
minimal changes. It assumes that,
while the
 
global economy
 
has returned to
 
pre-pandemic levels
 
and the immediate
 
risks
 
from COVID-19
 
have decreased,
 
the
associated disruptions
 
and
 
the
 
consequences of
 
the unprecedented
 
monetary and
 
fiscal stimulus
 
measures will
 
remain
critical. Concerns regarding
 
the sustainability
 
of public debt, following the marked deterioration
 
of fiscal positions, lead to
a loss
 
of confidence and
 
market turbulence, while protectionism results in
 
a decrease
 
in global
 
trade. Governments and
central banks have limited scope
 
to support the economies,
 
and interest rate levels remain moderate. As a
 
consequence,
China
 
suffers a
 
hard landing
 
which,
 
combined with
 
political, solvency and
 
liquidity concerns,
 
affects emerging
 
markets
significantly. A
 
spillover
 
effect
 
leads
 
to
 
a
 
contraction of
 
the
 
Eurozone,
 
Swiss
 
and
 
US
 
economies,
 
as
 
global
 
demand
 
is
significantly affected.
 
Given the
 
severity of the
 
macroeconomic
 
impact, unemployment
 
rates rise to
 
historical highs
 
and real
estate sectors contract
 
sharply.
Stagflationary
 
geopolitical
 
crisis
 
scenario:
The
 
second
 
downside
 
scenario
 
was
 
changed
 
during
 
2022.
 
In
 
light
 
of
 
the
developments caused by Russia’s invasion of Ukraine, the
mild global interest rate steepening scenario
 
was replaced by a
severe global
 
interest rate
 
steepening scenario
 
in the
 
first quarter of
 
2022, as
 
the beginning of
 
the Russia–Ukraine war
increased fears of
 
higher inflation and a corresponding
 
reaction by monetary
 
authorities. In
 
the second quarter of the
 
year,
the progression
 
of the war
 
and the enforcement
 
of sanctions
 
regimes led
 
to a redesign
 
of the scenario.
 
The resulting
severe
Russia–Ukraine conflict scenario
 
has similar dynamics as the severe global interest rate
 
steepening scenario, but addressed
specifically the prospect of
 
rising energy costs,
 
especially in Europe, with
 
the consequences
 
of lower
 
growth and higher
inflation rates.
 
In the
 
fourth quarter of
 
2022, UBS
 
developed a new
stagflationary geopolitical
 
crisis scenario
 
(SGC)
 
and
included this new
 
scenario in the ECL calculation for year-end 2022 in lieu of the
severe Russia–Ukraine conflict scenario
.
While
 
the SGC scenario addresses similar risks as the
severe Russia–Ukraine conflict
 
scenario
, it also covers additional and
broader risks and
 
therefore assumes
 
more severe
 
shocks. Geopolitical
 
tensions cause
 
an escalation
 
of security concerns
 
and
undermine globalization. The
 
ensuing economic regionalization leads
 
to a
 
surge in
 
global commodity prices
 
and further
disruptions of
 
supply chains
 
and raises
 
the specter
 
of prolonged
 
stagflation.
 
The severe
 
interest
 
rate and
 
adverse
 
house price
assumptions in
 
the SGC scenario
 
had a substantive
 
impact on model-based
 
ECL allowances
 
for loans
 
secured by
 
mortgages
in Switzerland and
 
the US. These
 
effects were
 
partly offset
 
by PMA releases
 
related to loans
 
secured by mortgages.
 
Refer to
the section below
 
on “Scenario weights
 
and post-model adjustments”
 
for more details.
Asset price
 
inflation scenario:
The upside
 
scenario is
 
based on
 
positive developments,
 
such as
 
an easing
 
of
 
geopolitical
tensions across the
 
globe and
 
a rebound
 
in Chinese economic
 
growth. A
 
combination of
 
lower energy and
 
commodity
prices,
 
effective monetary
 
policies
 
and
 
easing
 
supply
 
chain
 
disruptions helps
 
reduce
 
inflation.
 
Improved
 
consumer and
business sentiment lead to an economic rebound with central banks able to normalize interest rates; asset prices increase
significantly.
The table below details the key assumptions
 
for the four scenarios applied
 
as of 31 December 2022.
Scenario weights and post
 
-model adjustments
Due
 
to the
 
less positive
 
outlook
 
compared
 
with the
 
assessment on
 
31 December
 
2021, the
 
scenario weights
 
changed
during 2022. The upside scenario was allocated
 
a
0
% probability, and the previous
5
% weight was added to the
baseline
scenario
, now
 
set at
60
%. Following
 
the introduction
 
of the
 
SGC, which
 
was deemed
 
to have
 
a higher
 
probability of
occurring than
 
the
global crisis
 
scenario
, the weights
 
were rebalanced.
 
The SGC
 
has a
 
weight of
25
% (compared
 
with
10
% for the
mild global
 
interest rate steepening
 
scenario
 
used as
 
of 31 December
 
2021) and
 
the weight
 
of the
global
crisis scenario
 
was reduced to
15
% (from
30
% as of 31 December
 
2021). The weights are also shown in the
 
table below.
The
 
scenarios
 
and
 
weight
 
allocation
 
were
 
established
 
in
 
line
 
with
 
the
 
general
 
market
 
sentiment
 
that
 
the
 
short-term
outlook
 
is subdued
 
and a
 
recession in
 
major markets
 
is a
 
strong
 
probability. The
 
downside
 
risks in
 
relation to
 
inflation
and monetary policy,
 
as well as
 
the availability and
 
price of energy,
 
mainly in Europe,
 
are better reflected
 
in our
 
models
compared with the uncertain developments
 
caused by COVID-19 in recent
 
years.
 
However, unquantifiable risks continue
 
to be relevant, as the pandemic
 
has not been overcome and
 
the world may face
new disruptions.
 
Furthermore, the geopolitical
 
situation worsened
 
during 2022,
 
and the impact on
 
the world
 
economy
from escalations with unforeseeable
 
consequences could be severe. In the near term, this
 
uncertainty relates primarily to
the development
 
of the
 
Russia–Ukraine
 
war. Models,
 
which are
 
based on
 
supportable statistical
 
information
 
from past
experiences regarding interdependencies of
 
macroeconomic factors and their
 
implications for credit
 
risk portfolios, cannot
comprehensively reflect
 
such extraordinary
 
events, such
 
as a
 
pandemic or
 
a fundamental
 
change
 
in the
 
world political
order. Rather than
 
creating multiple additional scenarios
 
to attempt gauging these
 
risks and applying
 
model parameters
that lack supportable information and
 
cannot be robustly validated, management
 
continued to
 
also apply PMAs.
 
These PMA took into account that more of the downside risks were modeled in 2022, particularly for lending
 
secured by
mortgages.
 
The
 
PMA
 
amounted
 
to
 
USD
131
m
 
as
 
of
 
31 December
 
2022
 
(31 December
 
2021:
 
USD
224
m).
 
These
remaining PMA
 
for uncertainties
 
on potentially
 
unmodeled risk
 
almost entirely
 
relate
 
to corporate
 
lending portfolios
 
in
Personal & Corporate Banking
 
and the Investment Bank.
Economic scenarios and weights applied
Assigned weights in %
ECL scenario
31.12.22
31.12.21
Asset price inflation
0.0
5.0
Baseline
60.0
55.0
Mild global interest rate steepening
 
0.0
10.0
Stagflationary geopolitical crisis
25.0
0.0
Global crisis
 
15.0
30.0
Scenario assumptions
One year
 
Three years cumulative
 
31.12.22
Asset price
inflation
Baseline
Stagflationary
geopolitical
crisis
 
Global
crisis
 
Asset price
inflation
Baseline
Stagflationary
geopolitical
crisis
 
Global
crisis
 
Real GDP growth (% change)
United States
4.0
(0.3)
(4.8)
(6.4)
9.1
3.2
(4.4)
(1.8)
Eurozone
3.0
0.6
(5.6)
(8.5)
6.2
2.5
(5.7)
(8.3)
Switzerland
3.0
0.7
(4.8)
(6.7)
6.6
3.5
(4.9)
(3.7)
Consumer price index (% change)
 
United States
2.5
2.6
10.0
(0.5)
8.1
6.5
15.8
1.2
Eurozone
2.3
5.0
9.6
(0.7)
7.4
9.6
14.8
(0.7)
Switzerland
2.1
1.6
5.8
(1.8)
6.2
3.9
10.7
(1.6)
Unemployment rate (end-of
 
-period level, %)
United States
3.0
3.9
9.2
10.0
3.0
5.3
11.8
9.4
Eurozone
6.0
7.0
10.9
11.9
6.0
7.1
12.2
13.0
Switzerland
1.7
2.3
4.3
4.4
1.5
2.6
5.1
4.9
Fixed income: 10-year government
 
bonds (change in yields, basis points)
USD
25.0
(5.6)
235.0
(326.0)
70.0
(13.2)
205.0
(291.1)
EUR
20.0
47.8
250.0
(270.6)
57.5
44.7
220.0
(246.5)
CHF
25.0
45.7
220.0
(209.7)
62.5
57.0
205.0
(159.6)
Equity indices (% change)
S&P 500
20.0
7.4
(51.5)
(50.0)
51.7
22.8
(45.6)
(27.9)
EuroStoxx 50
17.0
17.2
(51.6)
(50.0)
42.9
29.2
(47.2)
(39.3)
SPI
14.0
5.6
(51.6)
(46.0)
37.9
19.3
(47.2)
(32.9)
Swiss real estate (% change)
Single-Family Homes
 
6.6
1.1
(16.7)
(19.9)
14.0
2.3
(32.9)
(23.9)
Other real estate (% change)
United States (S&P / Case–Shiller)
7.8
(4.5)
(12.8)
(19.3)
19.1
(0.6)
(35.8)
(32.7)
Eurozone (House Price Index)
7.0
(2.7)
(8.4)
(8.9)
15.4
2.0
(14.7)
(17.5)
Scenario assumptions
One year
 
Three years cumulative
 
31.12.21
Asset price
inflation
Baseline
Mild global
interest rate
steepening
 
Global crisis
 
Asset price
inflation
Baseline
Mild global
interest rate
steepening
 
Global crisis
 
Real GDP growth (% change)
United States
9.1
4.4
(0.1)
(5.9)
17.8
10.1
1.8
(3.8)
Eurozone
9.4
3.9
(0.1)
(8.7)
17.3
7.5
0.9
(10.3)
Switzerland
5.5
2.4
(0.9)
(6.6)
13.1
5.8
(0.1)
(5.7)
Consumer price index (% change)
United States
3.1
2.2
5.7
(1.2)
9.5
6.3
13.0
0.4
Eurozone
2.3
1.4
4.2
(1.3)
8.0
4.8
10.4
(1.7)
Switzerland
1.8
0.3
3.5
(1.8)
6.1
1.7
9.0
(1.6)
Unemployment rate (end-of
 
-period level, %)
United States
3.0
3.9
6.1
10.9
3.0
3.5
7.2
10.8
Eurozone
6.2
7.4
8.7
12.9
6.0
7.2
9.1
15.1
Switzerland
2.3
2.5
3.4
5.2
1.6
2.3
4.2
5.9
Fixed income: 10-year government
 
bonds (change in yields, basis points)
USD
50.0
16.5
259.2
(50.0)
170.0
41.2
329.2
(15.0)
EUR
40.0
11.1
283.8
(35.0)
140.0
34.9
349.3
(25.0)
CHF
50.0
12.1
245.5
(70.0)
150.0
34.4
307.3
(35.0)
Equity indices (% change)
S&P 500
12.0
14.1
(27.0)
(50.2)
35.5
24.7
(21.8)
(40.1)
EuroStoxx 50
16.0
12.3
(23.4)
(57.6)
41.6
20.7
(19.9)
(50.4)
SPI
14.0
12.1
(22.9)
(53.6)
37.9
19.1
(19.6)
(44.2)
Swiss real estate (% change)
Single-Family Homes
 
5.1
4.4
(4.3)
(17.0)
15.5
7.4
(8.8)
(30.0)
Other real estate (% change)
United States (S&P / Case–Shiller)
10.0
3.5
(2.3)
(9.5)
21.7
7.1
(8.7)
(26.3)
Eurozone (House Price Index)
8.4
5.1
(4.0)
(5.4)
17.8
9.6
(7.6)
(10.8)
c) Development of ECL allowances
 
and provisions
 
The ECL allowances and provisions
 
recognized in the period
 
are impacted by a variety of factors,
 
such as:
–
 
the effect of selecting and
 
updating forward-looking scenarios
 
and the respective weights;
–
 
origination of new instruments during
 
the period;
 
–
 
the effect
 
of passage of
 
time (lower residual
 
lifetime PD and the
 
effect of discount
 
unwind) as the
 
ECL on an
 
instrument
for the remaining lifetime decreases (all other
 
factors remaining the same);
–
 
derecognition of instruments in the
 
period;
–
 
change in individual asset quality of instruments;
–
 
movements from
 
a
 
maximum
 
12-month
 
ECL
 
to
 
the
 
recognition
 
of
 
lifetime ECL
 
(and
 
vice versa)
 
following
 
transfers
between stages 1 and 2;
 
–
 
movements from stages 1 and 2 to stage 3 (credit-impaired status) when default has become certain and PD increases
to 100% (or vice versa);
–
 
changes in models or updates
 
to model parameters;
–
 
write-off; and
–
 
foreign exchange translations for assets denominated
 
in foreign currencies.
The
 
table
 
below
 
explains
 
the
 
changes
 
in
 
the
 
ECL
 
allowances
 
and
 
provisions
 
for
 
on-
 
and
 
off-balance
 
sheet
 
financial
instruments and credit
 
lines in scope of ECL
 
requirements
 
between the beginning
 
and the end of the
 
period due
 
to the
factors listed above.
Development of ECL allowances
 
and provisions
USD m
Total
Stage 1
Stage 2
Stage 3
Balance as of 31 December 2021
(1,165)
(282)
(220)
(662)
Net movement from new and derecognized
 
transactions
1
(7)
(21)
16
(2)
of which: Private clients with mortgages
(6)
(6)
0
0
of which: Real estate financing
(3)
(5)
2
0
of which: Large corporate clients
8
(1)
11
(2)
of which: SME clients
(1)
(1)
0
0
of which: Other
(6)
(8)
3
0
 
of which: Financial intermediaries and hedge
 
funds
0
(2)
2
0
 
of which: Loans to financial advisors
0
0
0
0
Remeasurements with stage transfers
2
(65)
20
(39)
(46)
of which: Private clients with mortgages
(10)
3
(12)
0
of which: Real estate financing
7
(1)
8
0
of which: Large corporate clients
(33)
16
(28)
(21)
of which: SME clients
(23)
2
(2)
(22)
of which: Other
(6)
1
(4)
(3)
 
of which: Financial intermediaries and hedge
 
funds
0
0
0
0
 
of which: Loans to financial advisors
1
2
(1)
0
Remeasurements without
 
stage transfers
3
13
(8)
(27)
48
of which: Private clients with mortgages
(12)
5
(18)
1
of which: Real estate financing
13
3
10
0
of which: Large corporate clients
32
(11)
2
41
of which: SME clients
(6)
(10)
(9)
14
of which: Other
(15)
5
(12)
(8)
 
of which: Sovereigns
(8)
0
(8)
0
 
of which: Loans to financial advisors
(3)
3
(1)
(6)
Model changes
4
30
29
1
0
Movements with profit or loss impact
5
(29)
20
(49)
0
Movements without profit or loss impact
 
(write-off,
 
FX and other)
6
104
3
1
99
Balance as of 31 December 2022
(1,091)
(260)
(267)
(564)
1 Represents
 
the increase
 
and decrease
 
in allowances
 
and provisions
 
resulting from
 
financial instruments
 
(including guarantee
 
s
 
and facilities)
 
that were
 
newly originated,
 
purchased or
 
renewed and
 
from the
 
final
derecognition of loans or facilities on their maturity date or earlier.
 
2 Represents the remeasurement between 12
 
-month and lifetime ECL due to stage transfers.
 
3 Represents the change in allowances and provisions
related to
 
changes
 
in model
 
inputs
 
or assumptions,
 
including
 
changes
 
in forward
 
-looking
 
macroeconomic
 
conditions,
 
changes
 
in the
 
exposure
 
profile,
 
PD and
 
LGD
 
changes,
 
and
 
unwinding
 
of the
 
time
 
value.
 
4 Represents the change in the allowances
 
and provisions related to changes
 
in models and methodologies.
 
5 Includes ECL movements
 
from new and derecognized transactions,
 
remeasurement changes,
 
model and
methodology changes.
 
6 Represents
 
the decrease
 
in allowances
 
and provisions
 
resulting from
 
write-offs of
 
the ECL
 
allowance
 
against the
 
gross carrying
 
amount when
 
all or
 
part of
 
a financial
 
asset is
 
deemed
uncollectible or forgiven and
 
movements in foreign exchange
 
rates.
Movements with profit
 
or loss
 
impact:
Stages 1
 
and 2 ECL
 
allowances and provisions
 
increased on a
 
net basis
 
by USD
29
m:
 
–
 
Net movement
 
from new
 
and derecognized
 
transactions
 
includes USD
21
m stage 1
 
expenses and
 
USD
16
m stage 2
releases: Stage 1 expenses are primarily driven by new loans secured by real estate. The residual
 
effect is spread across
lending segments. Stage 2
 
releases are largely driven by redemption of
 
corporate loans in the I
 
nvestment Bank.
–
 
Remeasurements with
 
stage transfers
 
include USD
20
m releases
 
in stage
 
1 and
 
USD
39
m expenses
 
in stage
 
2.
 
This
mainly includes
 
the transfer of
 
a few
 
large corporate
 
lending
 
transactions in
 
the Investment
 
Bank
 
from stage
 
1 to
 
2
(i.e., releases in
 
stage 1
 
and related but
 
generally higher
 
expenses in stage
 
2), driven by
 
rating downgrades and scenario
effects.
–
 
Remeasurements
 
without
 
stage
 
transfers
 
include
 
stage
 
1
 
expenses
 
of
 
USD
8
m
 
and stage
 
2 expenses
 
of
 
USD
27
m.
These expenses of
 
USD
35
m relate
 
to large and
 
SME corporate lending
 
(USD
28
m), substantially
 
due to scenario
 
effects,
and to a single sovereign
 
counterparty (USD
8
m).
 
–
 
Model changes: refer to Note
 
19b for more information.
Movements without profit or loss impact:
Stage 3 allowances decreased by USD
99
m almost entirely due to write-offs of
USD
95
m.
Development of ECL allowances
 
and provisions
USD m
Total
Stage 1
Stage 2
Stage 3
Balance as of 31 December 2020
(1,468)
(306)
(333)
(829)
Net movement from new and derecognized
 
transactions
1
(59)
(72)
13
0
of which: Private clients with mortgages
(7)
(10)
3
0
of which: Real estate financing
(7)
(11)
4
0
of which: Large corporate clients
(13)
(21)
7
0
of which: SME clients
(8)
(8)
0
0
of which: Other
(24)
(23)
(2)
0
 
of which: Financial intermediaries and hedge
 
funds
(21)
(18)
(4)
0
 
of which: Loans to financial advisors
0
(1)
1
0
Remeasurements with stage transfers
2
(40)
8
0
(49)
of which: Private clients with mortgages
(9)
4
(13)
0
of which: Real estate financing
(3)
1
(4)
0
of which: Large corporate clients
2
(2)
12
(8)
of which: SME clients
(27)
5
4
(36)
of which: Other
(3)
0
2
(4)
 
of which: Financial intermediaries and hedge
 
funds
2
(1)
3
0
 
of which: Loans to financial advisors
0
1
(1)
0
Remeasurements without
 
stage transfers
3
203
55
74
74
of which: Private clients with mortgages
33
8
26
(1)
of which: Real estate financing
30
13
13
3
of which: Large corporate clients
44
5
21
17
of which: SME clients
53
(1)
1
53
of which: Other
44
29
14
2
 
of which: Financial intermediaries and hedge
 
funds
27
15
12
0
 
of which: Loans to financial advisors
6
8
1
(3)
Model changes
4
45
29
16
0
Movements with profit or loss impact
5
148
19
104
25
Movements without profit or loss impact
 
(write-off, FX
 
and other)
6
154
5
9
141
Balance as of 31 December 2021
(1,165)
(282)
(220)
(662)
1 Represents
 
the increase
 
and decrease
 
in allowances
 
and provisions
 
resulting from
 
financial instruments
 
(including guarantee
 
s
 
and facilities)
 
that were
 
newly originated,
 
purchased or
 
renewed and
 
from the
 
final
derecognition of loans or facilities on their maturity date or earlier.
 
2 Represents the remeasurement between 12
 
-month and lifetime ECL due to stage transfers.
 
3 Represents the change in allowances and provisions
related to
 
changes
 
in model
 
inputs
 
or assumptions,
 
including
 
changes
 
in forward
 
-looking
 
macroeconomic
 
conditions,
 
changes
 
in the
 
exposure
 
profile,
 
PD and
 
LGD
 
changes,
 
and
 
unwinding
 
of the
 
time
 
value.
 
4 Represents the change in the allowances
 
and provisions related to changes
 
in models and methodologies.
 
5 Includes ECL movements
 
from new and derecognized
 
transactions, remeasurement
 
changes, model and
methodology changes.
 
6 Represents
 
the decrease
 
in allowa
 
nces and
 
provisions resulting
 
from write
 
-offs of
 
the ECL
 
allowance
 
against the
 
gross carrying
 
amount when
 
all or
 
part of
 
a financial
 
asset is
 
deemed
uncollectible or forgiven and
 
movements in foreign exchange
 
rates.
As explained
 
in Note 1a,
 
the assessment
 
of a significant
 
increase
 
in credit
 
risk (SICR)
 
considers a
 
number
 
of qualitative
and
 
quantitative factors
 
to determine
 
whether a
 
stage transfer
 
between
 
stage 1
 
and stage 2
 
is required,
 
although the
primary assessment considers changes in PD based on rating analyses and economic outlook. Additionally, UBS AG takes
into consideration
 
counterparties that
 
have moved
 
to a
 
credit watch
 
list and
 
those with
 
payments that
 
are at
 
least 30
days past due.
ECL stage 2 (“significant deterioration
 
in credit risk”) allowances / provisions
 
as of 31 December 2022 – classification by trigger
USD m
Stage 2
of which:
PD layer
of which:
watch list
of which:
≥30 days
 
past due
On-
 
and off-balance sheet
 
(267)
(196)
(21)
(50)
of which: Private clients with mortgages
(107)
(83)
0
(25)
of which: Real estate financing
(23)
(18)
0
(5)
of which: Large corporate clients
(65)
(51)
(13)
0
of which: SME clients
(37)
(22)
(7)
(7)
of which: Financial intermediaries and hedge
 
funds
(17)
(17)
0
0
of which: Loans to financial advisors
(2)
0
0
(2)
of which: Credit cards
(12)
0
0
(12)
of which: Other
(5)
(5)
0
0
d) Maximum exposure to credit risk
The tables
 
below provide UBS
 
AG’s maximum exposure to credit
 
risk for financial
 
instruments subject to
 
ECL requirements
and
 
the
 
respective
 
collateral
 
and
 
other
 
credit
 
enhancements
 
mitigating
 
credit
 
risk
 
for
 
these
 
classes
 
of
 
financial
instruments.
 
The maximum exposure
 
to credit risk
 
includes the
 
carrying amounts
 
of financial instruments
 
recognized on
 
the balance
sheet subject to credit risk
 
and the notional amounts for off-balance sheet arrangements. Where information is available,
collateral is presented at fair
 
value. For other collateral, such
 
as real estate, a
 
reasonable alternative
 
value is used. Credit
enhancements,
 
such
 
as
 
credit
 
derivative
 
contracts
 
and
 
guarantees,
 
are
 
included
 
at
 
their
 
notional
 
amounts.
 
Both
 
are
capped
 
at the
 
maximum exposure
 
to credit
 
risk for
 
which they
 
serve as
 
security. The
 
“Risk
 
management and
 
control”
section of this
 
report describes
 
management’s view
 
of credit
 
risk and
 
the related exposures,
 
which can differ
 
in certain
respects from the requirements of International
 
Financial Reporting Standards
 
(IFRS).
Maximum exposure to credit
 
risk
 
31.12.22
Collateral
1,2
Credit enhancements
1
Exposure to
credit risk
after collateral
and credit
enhancements
USD bn
Maximum
exposure to
credit risk
Cash
collateral
received
Collateralized
by equity and
debt
instruments
Secured by
real estate
Other
collateral
3
Netting
Credit
derivative
contracts
Guarantees
 
Financial assets measured at
 
amortized cost on the balance sheet
Cash and balances at central banks
169.4
169.4
Loans and advances to banks
4
14.7
0.0
0.1
14.6
Receivables from securities financing transactions
measured at amortized cost
67.8
0.0
64.5
2.4
0.9
Cash collateral receivables on derivative
 
instruments
5,6
35.0
22.9
12.1
Loans and advances to customers
390.0
36.1
115.9
197.8
19.6
3.0
17.6
Other financial assets measured at amortized cost
53.4
0.1
0.5
0.0
1.3
51.4
Total financial assets
 
measured at amortized cost
730.4
36.2
181.0
197.9
23.4
22.9
0.0
3.0
266.1
Financial assets measured at
 
fair value
 
through other comprehensive income – debt
2.2
2.2
Total maximum exposure to
 
credit risk
 
reflected on the balance sheet within
 
the scope of ECL
732.6
36.2
181.0
197.9
23.4
22.9
0.0
3.0
268.3
Guarantees
7
22.1
1.2
9.3
0.1
2.0
1.8
7.7
Loan commitments
7
39.9
0.2
3.1
1.3
6.5
0.1
1.0
27.8
Forward starting transactions,
 
reverse repurchase
and securities borrowing agreements
3.8
3.8
0.0
Committed unconditionally revocable credit lines
43.6
0.2
8.2
6.0
6.2
0.5
22.5
Total maximum exposure to
 
credit risk not
 
reflected on the balance sheet within
 
the scope of ECL
109.4
1.6
24.4
7.5
14.7
0.0
0.1
3.3
58.0
31.12.21
Collateral
1,2
Credit enhancements
1
Exposure to
credit risk
after collateral
and credit
enhancements
USD bn
Maximum
exposure to
credit risk
Cash
collateral
received
Collateralized
by equity and
debt
instruments
Secured by
real estate
Other
collateral
3
Netting
Credit
derivative
contracts
Guarantees
 
Financial assets measured at
 
amortized cost on the balance sheet
Cash and balances at central banks
192.8
192.8
Loans and advances to banks
4
15.4
0.1
0.1
15.1
Receivables from securities financing transactions
measured at amortized cost
75.0
0.0
68.0
6.9
0.0
Cash collateral receivables on derivative
 
instruments
5,6
30.5
18.4
12.1
Loans and advances to customers
398.7
38.2
128.7
191.3
20.2
4.0
16.4
Other financial assets measured at amortized cost
26.2
0.2
0.1
0.0
1.3
24.7
Total financial assets
 
measured at amortized cost
738.6
38.4
196.9
191.3
28.4
18.4
0.0
4.0
261.1
Financial assets measured at
 
fair value
 
through other comprehensive income – debt
8.8
8.8
Total maximum exposure to
 
credit risk
 
reflected on the balance sheet within
 
the scope of ECL
747.5
38.4
196.9
191.3
28.4
18.4
0.0
4.0
270.0
Guarantees
7
20.9
1.3
6.5
0.2
2.5
2.3
8.1
Loan commitments
7
39.4
0.5
4.0
2.4
7.3
0.3
1.7
23.1
Forward starting transactions,
 
reverse repurchase
and securities borrowing agreements
1.4
1.4
0.0
Committed unconditionally revocable credit lines
42.3
0.3
9.0
6.2
3.9
0.5
22.5
Total maximum exposure to
 
credit risk not
 
reflected on the balance sheet within
 
the scope of ECL
104.1
2.2
20.9
8.7
13.7
0.0
0.3
4.5
53.7
1 Of which: USD
1,372
m for 31 December 2022 (31 December
 
2021: USD
1,443
m) relates to total credit-impaired financial
 
assets measured at amortized cost and USD
113
m for 31 December 2022 (31 December
 
2021:
USD
130
m) to total off-balance sheet financial instruments and credit
 
lines for credit-impaired positions.
 
2 Collateral arrangements
 
generally incorporate a range of collateral, including
 
cash, equity and debt instruments,
real estate and
 
other collateral.
 
UBS AG applies
 
a risk-based
 
approach that
 
generally
 
prioritizes collateral
 
according to its
 
liquidity profile.
 
3 Includes but is
 
not limited to life
 
insurance contracts,
 
inventory,
 
mortgage
loans, gold
 
and other
 
commodities.
 
4 Loans
 
and advances
 
to banks
 
include amounts
 
held with third
 
-party banks
 
on behalf
 
of clients.
 
The credit
 
risk associated
 
with these
 
balances may
 
be borne
 
by those clients.
 
5 Included within Cash
 
collateral receivables
 
on derivative
 
instruments are
 
margin balances
 
due from exchanges
 
or clearing houses.
 
Some of these
 
margin balances
 
reflect amounts
 
transferred on
 
behalf of clients
 
who
retain the associated
 
credit risk.
 
6 The amount
 
shown in the
 
“Netting” column represents
 
the netting
 
potential not recognized
 
on the balance sheet.
 
Refer to Note 21
 
for more information.
 
7 The amount
 
shown in
the “Guarantees” column includes
 
sub-participations.
e) Financial assets subject to credit risk
 
by rating category
The table below shows the credit quality and the maximum exposure
 
to credit risk based on the UBS AG’s internal credit
rating system and
 
year-end stage
 
classification. Under
 
IFRS 9,
 
the credit risk
 
rating reflects
 
the UBS
 
AG’s assessment
 
of
the
 
probability
 
of
 
default
 
of
 
individual
 
counterparties,
 
prior
 
to
 
substitutions.
 
The
 
amounts
 
presented
 
are
 
gross
 
of
impairment allowances.
›
 
Refer to the “Risk
 
management and
 
control” section of
 
this report for more
 
details
 
regarding the UBS AG’s internal
 
grading
system
Financial assets subject to credit risk by
 
rating category
USD m
31.12.22
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total gross
carrying
amount
ECL
allowances
Net carrying
amount
(maximum
exposure to
credit risk)
Financial assets measured at amortized
 
cost
Cash and balances at central banks
168,525
877
0
0
56
0
169,457
(12)
169,445
of which: stage 1
168,525
877
0
0
0
0
169,402
0
169,402
of which: stage 2
0
0
0
0
56
0
56
(12)
44
Loans and advances to banks
862
11,150
832
996
837
0
14,676
(6)
14,671
of which: stage 1
862
11,150
832
996
836
0
14,675
(5)
14,670
of which: stage 2
0
0
0
0
1
0
1
(1)
1
of which: stage 3
0
0
0
0
0
0
0
0
0
Receivables from securities
 
financing transactions measured at
amortized cost
27,158
15,860
8,870
15,207
721
0
67,816
(2)
67,814
of which: stage 1
27,158
15,860
8,870
15,207
721
0
67,816
(2)
67,814
Cash collateral receivables on
 
derivative instruments
10,613
12,978
7,138
4,157
147
0
35,034
0
35,033
of which: stage 1
10,613
12,978
7,138
4,157
147
0
35,034
0
35,033
Loans and advances to customers
6,491
216,824
68,444
76,147
20,891
2,012
390,810
(783)
390,027
of which: stage 1
6,491
215,332
66,202
69,450
15,557
0
373,032
(129)
372,903
of which: stage 2
0
1,493
2,242
6,698
5,334
0
15,767
(180)
15,587
of which: stage 3
0
0
0
0
0
2,012
2,012
(474)
1,538
Other financial assets measured at
 
amortized cost
29,011
16,649
447
6,708
450
210
53,475
(86)
53,389
of which: stage 1
29,011
16,646
427
6,426
336
0
52,846
(17)
52,829
of which: stage 2
0
2
20
283
114
0
419
(6)
413
of which: stage 3
0
0
0
0
0
210
210
(63)
147
Total financial assets
 
measured at amortized cost
242,660
274,337
85,731
103,216
23,102
2,222
731,269
(890)
730,379
On-balance sheet financial instruments
Financial assets measured at FVOCI
 
– debt instruments
1,307
840
0
92
0
0
2,239
0
2,239
Total on-balance
 
sheet financial instruments
243,966
275,178
85,731
103,308
23,102
2,222
733,508
(890)
732,618
Off-balance sheet positions subject to expected
 
credit loss by rating category
USD m
31.12.22
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total off-
balance sheet
exposure
(maximum
exposure to
credit risk)
ECL provisions
Off-balance sheet financial instruments
Guarantees
 
7,252
5,961
4,772
3,049
1,025
108
22,167
(48)
of which: stage 1
7,252
5,917
3,812
2,229
596
0
19,805
(13)
of which: stage 2
0
44
960
821
429
0
2,254
(9)
of which: stage 3
0
0
0
0
0
108
108
(26)
Irrevocable loan commitments
1,770
14,912
6,986
10,097
6,107
124
39,996
(111)
of which: stage 1
1,770
14,789
6,818
9,625
4,529
0
37,531
(59)
of which: stage 2
0
123
168
472
1,578
0
2,341
(52)
of which: stage 3
0
0
0
0
0
124
124
0
Forward starting reverse repurchase
 
and securities borrowing agreements
2,781
2
11
1,007
0
0
3,801
0
Total off-balance sheet
 
financial instruments
11,803
20,874
11,769
14,153
7,132
233
65,964
(159)
Credit lines
Committed unconditionally revocable
 
credit lines
2,288
16,483
9,247
11,885
3,739
36
43,677
(40)
of which: stage 1
2,288
15,777
8,960
11,355
3,429
0
41,809
(32)
of which: stage 2
0
705
287
531
310
0
1,833
(8)
of which: stage 3
0
0
0
0
0
36
36
0
Irrevocable committed prolongation
 
of existing loans
7
1,939
1,489
868
392
2
4,696
(2)
of which: stage 1
7
1,938
1,411
864
380
0
4,600
(2)
of which: stage 2
0
1
78
4
11
0
94
0
of which: stage 3
0
0
0
0
0
2
2
0
Total credit lines
2,295
18,421
10,736
12,753
4,131
37
48,373
(42)
1 Refer to the “Internal UBS rating
 
scale and mapping of external
 
ratings” table in the “Risk
 
management and control”
 
section of this report for more
 
information on rating categories.
Financial assets subject to credit risk by
 
rating category
USD m
31.12.21
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total gross
carrying
amount
ECL
allowances
Net carrying
amount
(maximum
exposure to
credit risk)
Financial assets measured at amortized
 
cost
Cash and balances at central banks
191,015
1,802
0
0
0
0
192,817
0
192,817
of which: stage 1
191,015
1,802
0
0
0
0
192,817
0
192,817
Loans and advances to banks
407
12,552
1,123
795
490
1
15,368
(8)
15,360
of which: stage 1
407
12,552
1,098
795
488
0
15,340
(7)
15,333
of which: stage 2
0
0
24
0
2
0
27
(1)
26
of which: stage 3
0
0
0
0
0
1
1
0
1
Receivables from securities
 
financing transactions
measured at amortized cost
34,386
11,267
10,483
17,440
1,439
0
75,014
(2)
75,012
of which: stage 1
34,386
11,267
10,483
17,440
1,439
0
75,014
(2)
75,012
Cash collateral receivables on
 
derivative instruments
7,466
13,476
5,878
3,647
47
0
30,514
0
30,514
of which: stage 1
7,466
13,476
5,878
3,647
47
0
30,514
0
30,514
Loans and advances to customers
5,295
232,663
67,620
70,394
21,423
2,148
399,543
(850)
398,693
of which: stage 1
5,295
231,583
65,083
63,298
16,362
0
381,622
(126)
381,496
of which: stage 2
0
1,080
2,536
7,096
5,061
0
15,773
(152)
15,620
of which: stage 3
0
0
0
0
0
2,148
2,148
(572)
1,577
Other financial assets measured at
 
amortized cost
12,564
6,705
321
6,097
394
264
26,346
(109)
26,236
of which: stage 1
12,564
6,696
307
5,887
317
0
25,772
(27)
25,746
of which: stage 2
0
10
13
209
77
0
309
(7)
302
of which: stage 3
0
0
0
0
0
264
264
(76)
189
Total financial assets
 
measured at amortized cost
251,133
278,465
85,424
98,372
23,793
2,414
739,601
(969)
738,632
On-balance sheet financial instruments
Financial assets measured at FVOCI
 
– debt instruments
3,996
4,771
0
77
0
0
8,844
0
8,844
Total on-balance
 
sheet financial instruments
255,130
283,236
85,424
98,449
23,793
2,414
748,445
(969)
747,477
Off-balance sheet positions subject to expected
 
credit loss by rating category
USD m
31.12.21
Rating category
1
0–1
2–3
4–5
6–8
9–13
Credit-
impaired
(defaulted)
Total off-
balance sheet
exposure
(maximum
exposure to
credit risk)
ECL provisions
Off-balance sheet financial instruments
Guarantees
 
4,457
7,064
4,535
3,757
1,009
150
20,972
(41)
of which: stage 1
4,457
7,037
4,375
3,075
752
0
19,695
(18)
of which: stage 2
0
27
160
682
258
0
1,127
(8)
of which: stage 3
0
0
0
0
0
150
150
(15)
Irrevocable loan commitments
2,797
14,183
7,651
8,298
6,502
46
39,478
(114)
of which: stage 1
2,797
13,917
7,416
7,127
5,840
0
37,097
(72)
of which: stage 2
0
266
235
1,171
663
0
2,335
(42)
of which: stage 3
0
0
0
0
0
46
46
0
Forward starting reverse repurchase
 
and securities borrowing agreements
0
0
55
1,389
0
0
1,444
0
Total off balance
 
sheet financial instruments
7,254
21,247
12,241
13,444
7,512
196
61,894
(155)
Credit lines
Committed unconditionally revocable
 
credit lines
2,636
16,811
8,627
10,130
4,107
63
42,373
(38)
of which: stage 1
2,636
16,467
8,304
8,724
3,671
0
39,802
(28)
of which: stage 2
0
344
323
1,406
436
0
2,508
(10)
of which: stage 3
0
0
0
0
0
63
63
0
Irrevocable committed prolongation
 
of existing loans
17
2,438
1,422
1,084
602
48
5,611
(3)
of which: stage 1
17
2,438
1,422
1,082
568
0
5,527
(3)
of which: stage 2
0
0
0
1
34
0
36
0
of which: stage 3
0
0
0
0
0
48
48
0
Total credit lines
2,653
19,249
10,049
11,214
4,709
111
47,984
(41)
1 Refer to the “Internal UBS rating
 
scale and mapping of external
 
ratings” table in the “Risk
 
management and control”
 
section of this report for more
 
information on rating
 
categories.
f) Sensitivity information
As outlined in Note
 
1a, ECL estimates involve significant uncertainties at the
 
time they are made.
ECL models
The models
 
applied
 
to determine
 
point
 
-in-time
 
PD and LGD
 
rely on
 
market and statistical
 
data, which
 
has been
 
found
to
 
correlate
 
well
 
with
 
historically
 
observed
 
defaults
 
in
 
sufficiently
 
homogeneous
 
segments.
 
The
 
risk
 
sensitivities
 
for
each of the
 
ECL reporting
 
segments
 
to such
 
factors are
 
summarized
 
in Note 9.
Sustainability and climate risk
 
Sustainability and climate risk (SCR) may negatively affect clients
 
or portfolios due to direct or indirect transition costs, or
exposure to physical risks in locations
 
likely to be impacted by climate change.
 
Such effects could lead to
 
a deterioration
in credit worthiness, which in turn would
 
have an impact on ECLs.
 
While some indicators
 
that are more
 
influenced by
 
climate change (e.g.,
 
energy prices) are
 
factored into the
 
current PD
models where
 
they have
 
demonstrated
 
statistical
 
relevance,
 
UBS
 
AG currently
 
does
 
not use
 
a specific
 
SCR
 
scenario in
addition
 
to
 
the
 
four
 
general
 
economic
 
scenarios
 
applied
 
to
 
derive
 
the
 
weighted-average
 
ECL.
 
The
 
rationale
 
for
 
the
approach
 
at
 
this
 
point
 
in
 
time
 
is
 
the
 
significance
 
of
 
model
 
risks
 
and
 
challenges
 
in
 
calibration
 
and
 
probability
 
weight
assessment given the paucity of data.
Instead, UBS
 
AG focuses on
 
the process of
 
vetting clients and
 
business transactions and
 
takes individual actions,
 
where
transition risk is deemed
 
to be a significant
 
driver of a
 
counterparty’s credit worthiness.
 
This review process may
 
lead to
a downward revision
 
of the counterparty’s credit rating,
 
or the adoption of risk mitigating
 
actions, and hence affect the
individual contribution to ECLs.
At the portfolio level, UBS AG
 
has started to use stress loss assumptions to assess the extent to which SCR may affect the
quality of the
 
loans extended to
 
small and medium-sized entities
 
and large
 
corporate clients. Initial tests
 
were based
 
on
a set of assumptions presented
 
by external parties (such as the Bank of
 
England). Such analysis undertaken
 
during 2022
concluded that the counterparties
 
are not expected to be
 
significantly impacted
 
by physical or transition
 
risks,
 
mainly as
there are no material risk concentrations in high-risk sectors. The
 
analysis of the corporate loan book has also shown that
any potential significant impacts from transition costs or
 
physical risks would materialize over a
 
time horizon that exceeds
in most cases the
 
contractual lifetime of the
 
underlying assets. Based on current information
 
on regulatory developments,
this would
 
also apply
 
to the
 
portfolio of
 
private clients’
 
mortgages and
 
real estate
 
financing,
 
given the long
 
lead times
for investments in upgrading
 
the housing stock.
As a
 
result of
 
the aforementioned
 
factors, it
 
was assessed
 
that the
 
magnitude of
 
any impact
 
of SCR
 
on the
 
weighted-
average ECL would not be material as of 31 December 2022.
 
Therefore, no specific post-model adjustment was made in
this regard.
›
 
Refer to “Sustainability
 
and climate risk”
 
in the “Risk management
 
and control” section
 
of this report
 
›
 
Refer to “Our focus
 
on sustainability
 
and climate”
 
in the “Our strategy, business
 
model and environment”
 
section of this
 
report
›
 
Refer to “UBS AG consolidated
 
supplemental disclosures
 
required under SEC regulations”
 
for the maturity
 
profile of UBS core loan
book
 
Forward-looking scenarios
Depending
 
on
 
the scenario
 
selection and
 
related macroeconomic
 
assumptions
 
for the
 
risk factors,
 
the components
 
of
the
 
relevant
 
weighted-average
 
ECL
 
change.
 
This
 
is
 
particularly
 
relevant
 
for
 
interest
 
rates,
 
which
 
can
 
move
 
in
 
both
directions under
 
a given growth
 
assumption,
 
e.g., low
 
growth with
 
high interest
 
rates in
 
a stagflation
 
scenario, versus
low growth
 
and falling interest
 
rates in a
 
recession. Management
 
generally looks
 
for scenario narratives that reflect
 
the
key risk drivers of a given credit
 
portfolio.
As forecasting
 
models are complex,
 
due to the
 
combination of
 
multiple factors, simple what-if
 
analyses involving a
 
change
of individual
 
parameters do not
 
necessarily provide realistic information
 
on the
 
exposure of segments
 
to changes in
 
the
macroeconomy.
 
Portfolio-specific
 
analyses
 
based
 
on
 
their key
 
risk
 
factors
 
would
 
also
 
not
 
be
 
meaningful,
 
as
 
potential
compensatory effects in other segments
 
would be ignored
 
.
 
The table below indicates some sensitivities
 
to ECLs, if a key
macroeconomic
 
variable
 
for
 
the
 
forecasting
 
period
 
is
 
amended
 
across
 
all
 
scenarios
 
with
 
all
 
other
 
factors
 
remaining
unchanged.
Potential effect on stage
 
1 and stage 2 positions from changing key
 
parameters as of 31 December 2022
USD m
100% Baseline
100%
Stagflationary
geopolitical crisis
 
100% Global crisis
 
Weighted average
 
Change in key parameters
Fixed income: Government bonds
 
(absolute change)
–0.50%
(3)
(106)
(2)
(14)
+0.50%
4
124
2
17
+1.00%
8
264
10
37
Unemployment rate (absolute change)
–1.00%
(4)
(138)
(24)
(23)
–0.50%
(2)
(78)
(13)
(12)
+0.50%
3
84
16
15
+1.00%
5
179
32
31
Real GDP growth (relative change)
–2.00%
7
13
18
11
–1.00%
3
7
9
5
+1.00%
(3)
(7)
(9)
(5)
+2.00%
(5)
(13)
(18)
(10)
House Price Index (relative change)
–5.00%
15
196
88
56
–2.50%
7
92
40
25
+2.50%
(4)
(83)
(35)
(19)
+5.00%
(7)
(157)
(65)
(36)
Equity (S&P500, EuroStoxx, SMI)
 
(relative change)
–10.00%
4
7
6
5
–5.00%
2
3
3
2
+5.00%
(2)
(4)
(3)
(2)
+10.00%
(4)
(8)
(7)
(5)
Sensitivities
 
can
 
be
 
more
 
meaningfully
 
assessed
 
in
 
the
 
context
 
of
 
coherent
 
scenarios
 
with
 
consistently
 
developed
macroeconomic
 
factors.
 
The
 
table
 
above
 
outlines
 
favorable
 
and
 
unfavorable
 
effects,
 
based
 
on
 
reasonably
 
possible
alternative changes to
 
the economic conditions
 
for stage 1 and
 
stage 2 positions. The
 
ECL impact
 
is calculated for
 
material
portfolios and disclosed for each
 
scenario.
 
The forecasting horizon is limited to three years, with a model
 
-based mean reversion of PD and LGD assumed thereafter.
Changes to these timelines may have an
 
effect on ECLs: depending
 
on the cycle, a longer or shorter forecasting horizon
will lead to different annualized lifetime PD and average LGD estimations. This is currently not deemed to be material for
UBS,
 
as a large proportion
 
of loans,
 
including mortgages
 
in Switzerland, have
 
maturities that are
 
within the
 
forecasting
horizon.
Scenario weights and stage allocation
Potential effect
 
on stage 1 and stage
 
2 positions from
 
changing scenario
 
weights or moving to
 
an ECL lifetime
 
calculation
 
as of 31 December
 
2022
Actual ECL
allowances and
provisions,
including staging
(as per Note 9)
 
Pro forma ECL allowances and provisions,
 
including staging
 
and assuming application of 100% scenario weighting
 
Pro forma ECL
allowances and
provisions,
assuming all
positions being
subject to lifetime
ECL
 
Scenarios
Weighted average
100% Baseline
100% Asset price
inflation
100%
Stagflationary
geopolitical crisis
 
100% Global crisis
 
Weighted average
USD m, except where indicated
Segmentation
Private clients with mortgages
(136)
(25)
(13)
(523)
(184)
(473)
Real estate financing
(43)
(26)
(22)
(176)
(30)
(126)
Large corporate clients
(136)
(97)
(84)
(199)
(174)
(235)
SME clients
(86)
(67)
(66)
(162)
(97)
(153)
Other segments
(125)
(114)
(111)
(145)
(153)
(281)
Total
(526)
(329)
(295)
(1,204)
(638)
(1,267)
Scenario weights
ECL is sensitive to changing scenario weights,
 
in particular if narratives and parameters are
 
selected that are not close to
the baseline scenario, highlighting
 
the non-linearity of credit losses.
As
 
shown
 
in the
 
table
 
above,
 
the
 
ECLs
 
for stage 1
 
and
 
stage 2
 
positions
 
would
 
have been
 
USD
329
m (31
 
December
2021:
 
USD
387
m)
 
instead of
 
USD
526
m
 
(31 December
 
2021:
 
USD
503
m)
 
if ECLs
 
had
 
been
 
determined
 
solely
 
on
 
the
baseline scenario
. The weighted-average
 
ECL therefore amounted
 
to
160
% (31 December 2021:
130
%) of the baseline
value. The effects of weighting
 
each of the four scenarios 100%
 
are shown in the table above.
Stage allocation and SICR
The determination
 
of what
 
constitutes an
 
SICR is
 
based on
 
management judgment,
 
as explained
 
in Note 1a.
 
Changing
the SICR trigger will have a direct effect on ECLs, as more or fewer positions would be subject to lifetime ECLs under any
scenario.
 
The
 
relevance
 
of
 
the
 
SICR trigger
 
on
 
overall ECL
 
is
 
demonstrated
 
in
 
the table
 
above with
 
the
 
indication that
 
the
 
ECL
allowances and provisions
 
for stage 1 and stage 2 positions
 
would have been USD
1,267
m, if all non-impaired positions
across the
 
portfolio had been
 
measured for
 
lifetime ECLs irrespective of
 
their actual SICR
 
status. This
 
amount compares
with actual stage 1 and 2
 
allowances and provisions of USD
526
m as of 31 December 2022.
Maturity profile
The maturity
 
profile is
 
an important
 
driver in
 
ECLs,
 
in particular
 
for transactions
 
in stage
 
2.
 
A transfer
 
of a
 
transaction
into stage
 
2 may
 
therefore have a
 
significant effect on ECLs.
 
The current maturity
 
profile of most
 
lending books is relatively
short.
 
Lending
 
to large
 
corporate clients
 
is generally
 
between
 
one
 
and two
 
years, with
 
related loan
 
commitments up
 
to four
years. Real estate lending is generally between
 
two and three years in Switzerland, with long
 
dated maturities in the US.
Lombard-lending
 
contracts
 
typically
 
have
 
average
 
contractual
 
maturities
 
of
 
12
 
months
 
or
 
less,
 
and
 
include
 
callable
features.
 
A
 
significant
 
portion
 
of
 
our
 
lending
 
to
 
SMEs
 
and
 
Real
 
estate
 
financings
 
is
 
documented
 
under
 
multi-purpose
 
credit
agreements,
 
which allow
 
for various
 
forms of
 
utilization
 
but are
 
unconditionally cancelable
 
by UBS
 
at any
 
time: a)
 
for
drawings under such agreements with a fixed maturity, the respective term is
 
applied for ECL calculations, or a maximum
of 12 months in stage
 
1; b) for unused
 
credit lines and all drawings
 
that have no fixed
 
maturity (e.g., current
 
accounts),
UBS generally applies a 12-month maturity from the reporting
 
date, given the credit review policies, which require either
continuous monitoring of key indicators and behavioral patterns
 
for smaller positions or an annual formal review for any
other limit. The ECLs for these products
 
are sensitive to shortening
 
or extending the maturity assumption.