The Group recognises an allowance for expected credit losses (ECLs) for loans and advances to customers and banks, other financial assets held at amortised cost, financial assets (other than equity investments) measured at fair value through other comprehensive income and certain loan commitment and financial guarantee contracts. At 31 December 2023, the Group’s expected credit loss allowance was £4,084 million (2022: £4,903 million), of which £3,762 million (2022: £4,580 million) was in respect of drawn balances.


	Allowance for expected credit losses
At 31 December 2023	Stage 1 £m	Stage 2 £m	Stage 3 £m	POCI £m	Total £m
In respect of:
Loans and advances to banks	8	–	–	–	8
UK mortgages	161	374	357	213	1,105
Credit cards	168	401	130	–	699
Other	339	320	228	–	887
Retail	668	1,095	715	213	2,691
Commercial Banking	232	372	418	–	1,022
Other	–	–	4	–	4

Loans and advances to customers	900	1,467	1,137	213	3,717
Debt securities	7	2	2	–	11
Financial assets at amortised cost	915	1,469	1,139	213	3,736
Other assets	16	–	10	–	26
Provisions in relation to loan commitments and financial guarantees	160	160	2	–	322
Total	1,091	1,629	1,151	213	4,084
Expected credit loss in respect of financial assets at fair value through other comprehensive income (memorandum item)	7	–	–	–	7


	Allowance for expected credit losses
At 31 December 2022	Stage 1 £m	Stage 2 £m	Stage 3 £m	POCI £m	Total £m
In respect of:
Loans and advances to banks	13	2	–	–	15
UK mortgages	91	552	311	253	1,207
Credit cards	120	433	113	–	666
Other	275	409	259	–	943
Retail	486	1,394	683	253	2,816
Commercial Banking	214	414	1,070	–	1,698
Other	–	–	4	–	4

Loans and advances to customers	700	1,808	1,757	253	4,518
Debt securities	8	–	1	–	9
Financial assets at amortised cost	721	1,810	1,758	253	4,542
Other assets	–	–	38	–	38
Provisions in relation to loan commitments and financial guarantees	134	185	4	–	323
Total	855	1,995	1,800	253	4,903
Expected credit loss in respect of financial assets at fair value through other comprehensive income (memorandum item)	9	–	–	–	9


Critical judgements:			Determining an appropriate definition of default against which a probability of default, exposure at default and loss given default parameter can be evaluated
			Establishing the criteria for a significant increase in credit risk (SICR)
			The individual assessment of material cases and the use of judgemental adjustments made to impairment modelling processes that adjust inputs, parameters and outputs to reflect risks not captured by models
Key source of estimation uncertainty:			Base case and multiple economic scenarios (MES) assumptions, including the rate of unemployment and the rate of change of house prices, required for creation of MES scenarios and forward-looking credit parameters

The probability of default (PD) of an exposure, both over a 12-month period and over its lifetime, is a key input to the measurement of the ECL allowance. Default has occurred when there is evidence that the customer is experiencing significant financial difficulty which is likely to affect the ability to repay amounts due. The definition of default adopted by the Group is described in note 2(H) Impairment of financial assets. IFRS 9 contains a rebuttable presumption that default occurs no later than when a payment is 90 days past due which the Group now uses for all its products following changes to the definition of default for UK mortgages on 1 January 2022. In addition, other indicators of mortgage default include end-of-term payments on past due interest-only accounts and loans considered in probation due to recent arrears or forbearance, aligning the definition of Stage 3 credit-impaired for IFRS 9 to the CRD IV prudential regulatory definition of default.

An ECL allowance equivalent to 12 months’ expected losses is established against assets in Stage 1; assets classified as Stage 2 carry an ECL allowance equivalent to lifetime expected losses. Assets are transferred from Stage 1 to Stage 2 when there has been a significant increase in credit risk (SICR) since initial recognition. Credit-impaired assets are transferred to Stage 3 with a lifetime expected losses allowance. The Group uses both quantitative and qualitative indicators to determine whether there has been a SICR for an asset. For Retail, the following tables set out the retail master scale (RMS) grade triggers which result in a SICR for financial assets and the PD boundaries for each RMS grade.

The Group uses the internal credit risk classification and watchlist as qualitative indicators to identify a SICR. The Group does not use the low credit risk exemption in its staging assessments. The use of a payment holiday in and of itself has not been judged to indicate a significant increase in credit risk, nor forbearance, with the underlying long-term credit risk deemed to be driven by economic conditions and captured through the use of forward-looking models. These portfolio level models are capturing the anticipated volume of increased defaults and therefore an appropriate assessment of staging and expected credit loss.

A Stage 3 asset that is no longer credit-impaired is transferred back to Stage 2 as no general probation period is applied to assets in Stage 3. UK mortgages is an exception to this rule where a probation period is enforced for non-performing, forborne and defaulted exposures in accordance with prudential regulation. If an exposure that is classified as Stage 2 no longer meets the SICR criteria, which in some cases capture customer behaviour in previous periods, it is moved back to Stage 1.

A range of approaches, segmented by product type, has been adopted by the Group to estimate a product’s expected life. These include using the full contractual life and taking into account behavioural factors such as early repayments, extensions and refinancing. For non-revolving retail assets, the Group has assumed the expected life for each product to be the time taken for all significant losses to be observed. For revolving retail products, the Group has considered the losses beyond the contractual term over which the Group is exposed to credit risk. For commercial overdraft facilities, the average behavioural life has been used. Changes to the assumed expected lives of the Group’s assets could impact the ECL allowance recognised by the Group. The assessment of SICR and corresponding lifetime loss, and the PD, of a financial asset designated as Stage 2, or Stage 3, is dependent on its expected life.


	Modelled ECL £m	Individually assessed £m		Judgements due to:		Total ECL £m
			Inflationary and interest rate risk £m		Other1 £m
At 31 December 2023
UK mortgages	991	–		61	63	1,115
Credit cards	703	–		92	15	810
Other Retail	866	–		33	46	945
Commercial Banking	1,124	340		–	(282)	1,182
Other	32	–		–	–	32
Total	3,716	340		186	(158)	4,084
At 31 December 2022
UK mortgages	946	–		49	214	1,209
Credit cards	698	–		93	(28)	763
Other Retail	903	–		53	60	1,016
Commercial Banking	972	1,008		–	(111)	1,869
Other	46	–		–	–	46
Total	3,565	1,008		195	135	4,903

Stage 3 ECL in Commercial Banking is largely assessed on an individual basis by the Business Support Unit using bespoke assessment of loss for each specific client based on potential recovery strategies. While these assessments are based on the Group’s latest economic view, the use of Group-wide multiple economic scenarios and weightings is not considered appropriate for these cases due to their individual characteristics. In place of this, a range of case-specific outcomes are considered with any alternative better or worse outcomes that carry a 25 per cent likelihood taken into account in establishing a probability-weighted ECL. At 31 December 2023, individually assessed provisions for Commercial Banking were £340 million (2022: £1,008 million) which reflected a range of £291 million to £413 million (2022: £908 million to £1,140 million), based on the range of alternative outcomes considered.

Impairment models fall within the Group’s model risk framework with model monitoring, periodic validation and back testing performed on model components, such as probability of default. Limitations in the Group’s impairment models or data inputs may be identified through the ongoing assessment and validation of the output of the models. In these circumstances, management applies appropriate judgemental adjustments to the ECL to ensure that the overall provision adequately reflects all material risks. These adjustments are determined by considering the particular attributes of exposures which have not been adequately captured by the impairment models and range from changes to model inputs and parameters, at account level, through to more qualitative post-model adjustments. Post-model adjustments are not typically calculated under each distinct economic scenario used to generate ECL, but on final modelled ECL. All adjustments are reviewed quarterly and are subject to internal review and challenge, including by the Audit Committee, to ensure that amounts are appropriately calculated and specific release criteria is identified.

During 2022 the intensifying inflationary pressures, alongside rising interest rates within the Group’s outlook created further risks not deemed to be fully captured by ECL models. These pressures played out in 2023 with households experiencing increased interest rates and living costs. These risks, whilst still present, are beginning to subside with inflation now reducing and interest rates now believed to have peaked. As a result, the judgements held in respect of inflationary and interest rate risks are at a slightly reduced level of £186 million (2022: £195 million). Other judgements continue to be applied for broader data and model limitations, both increasing and decreasing ECL. These include incremental risks associated with a material devaluation in commercial real estate prices present since 2022. Given ECL models only capture future price movements, and not the suppressed level, there is a risk that further losses are yet to emerge as well as greater risk on specific sector valuations. At 31 December 2023 judgemental adjustments resulted in net additional ECL allowances totalling £28 million (2022: £330 million).

There has been only modest evidence of credit deterioration in the UK mortgages portfolio through 2023 despite the high levels of inflation and the rising interest rate environment. Increases in new to arrears and defaults that have emerged are mainly driven by variable rate customers, who have experienced material increases in their monthly payment. Mortgage ECL models use UK Bank Rate as a driver of predicted defaults largely capturing the stretch on customers due to increased payments, and that has contributed materially to the elevated levels of ECL at 31 December 2023. The impact is also partly mitigated by stressed affordability assessments applied at loan origination which means most customers have demonstrated the ability to absorb payment shocks.

However, there remains a potential risk to affordability from continued inflationary pressures combined with higher interest rates, and that this may not be fully captured by the Group’s ECL models. The risk remains for customers maturing from low fixed rate deals, the accumulated impact on variable rate product holders, lower levels of real household income and rental cover value. Therefore a judgemental uplift in ECL has been taken in these segments of the mortgages portfolio, either where inflation is expected to present a more material risk, or where segments within the model do not recognise UK Bank Rate as a material driver of predicted defaults.

The Group’s ECL models for credit cards and personal loan portfolios use predictions of wage growth to account for future affordability stress. As elevated inflation erodes nominal wage growth, adjustments have been made to the econometric models to account for real, rather than nominal, income to produce adjusted predicted defaults. These adjustments also include the specific risk to affordability from increased housing costs, not captured by CPI. As these adjustments are made within predicted default models, they are calculated under each economic scenario and impact the staging of assets through increased PDs.

Due to the Group suspending mortgage litigation activity between late-2014 and mid-2018 due to policy changes for the treatment of arrears, and as collections strategy normalises post COVID-19 pandemic, the Group’s experience of possessions data on which our models rely is limited. This reflects an adjustment made to allow for an increase in the time assumed between default and repossession. A number of defaulted accounts, equivalent in scale to the estimated shortfall in possessions experienced, have had their provision coverage judgementally increased to the level of those accounts already in repossession. A further adjustment is made to accounts which have been in default for more than 24 months, with an arrears balance increase in the last six months. These accounts have their probability of possession judgmentally set to an increased level based on observed historical losses incurred on accounts that were of an equivalent status.

The low level of repossession volumes throughout 2020 to 2022 restricted the calibration of Forced Sale Discount (FSD) model parameters which uses the achieved sales price experience over the last 12 months. Over this period management partly incorporated an increasing trend in FSD rates through judgementally extending the observation period. At December 2023 the level of sales volumes observed over the past 12 months has subsequently returned to an adequate level for model calibrations to again be performed removing the need for judgemental adjustment.

Management has observed an increasing degree of oversensitivity in the number of recently originated low risk accounts moving to Stage 2 through the PD trigger mechanism. This arises from a blend of factors currently present, with the combination of the Group’s current MES assumptions and the uplift approach applied, disproportionately applying greater forward-looking uplifts to recent vintages. Given these accounts have shown no significant movement in observed credit scores and were originated under a similar or more adverse economic outlook, an adjustment has been made pending a model rebuild. Management has judgementally increased the threshold applied to these accounts by one further grade (to what is set out on page F-73) which results in £6 billion of assets being moved back to Stage 1 which results in a lower 12-month ECL.

An adjustment is required to extend the lifetime used for Stage 2 exposures on Retail revolving products from a three-year modelled lifetime, which reflected the outcome data available when the ECL models were developed. Incremental defaults beyond year three are calculated through the extrapolation of the default trajectory observed throughout the three years and beyond. The judgement has reduced slightly in the period following refinement to the discounting methodology applied.

During 2023, the volume of UK corporate insolvencies continued to exhibit an increasing trend beyond December 2019 levels, revealing a marked misalignment between observed UK corporate insolvencies and the Group’s credit performance. This dislocation gives rise to uncertainty over the drivers of observed trends and the appropriateness of the Group’s Commercial Banking model response which uses observed UK corporate insolvencies data to anchor future loss estimates to. Given the Group’s asset quality remains strong with low new defaults, a negative adjustment is applied by using the long-term average rate. The larger negative adjustment in the period reflects the widening gap between the increasing industry level and the long-term average rate used.

Following a review on the loss given default approach for commercial exposures, management deems that ECL should be adjusted to mitigate limitations identified in the approach which are causing loss given defaults to be inflated. These include the benefit from amortisation of exposures relative to collateral values at default and a move to an exposure-weighted approach being adopted. These temporary adjustments will be addressed through future model development.

Rolling the forecast model forwards into the period has resulted in the material fall in CRE prices seen in late 2022 moving out of the model assumptions used to assess ECL. Given the model uses future changes in the metric as a driver of defaults and loss rates there is a risk that the model benefit that arises does not reflect the residual risk caused by the sustained low level of prices. Management therefore considers it appropriate to judgementally reinstate the CRE price drop within the ECL model assumptions given the materially reduced level in CRE prices could still trigger additional defaults Within this adjustment management has refined the potential impact on loss rates through capturing updated valuations as well as stressing valuations on specific sectors where evidence suggests valuations may lag achievable levels, notably in cases of stressed sale.

The estimate of expected credit losses is required to be based on an unbiased expectation of future economic scenarios. The approach used to generate the range of future economic scenarios depends on the methodology and judgements adopted. The Group’s approach is to start from a defined base case scenario, used for planning purposes, and to generate alternative economic scenarios around this base case. The base case scenario is a conditional forecast underpinned by a number of conditioning assumptions that reflect the Group’s best view of key future developments. If circumstances appear likely to materially deviate from the conditioning assumptions, then the base case scenario is updated.

The base case scenario is central to a range of future economic scenarios generated by simulation of an economic model, for which the same conditioning assumptions apply as in the base case scenario. These scenarios are ranked by using estimated relationships with industry-wide historical loss data. With the base case already pre-defined, three other scenarios are identified as averages of constituent scenarios located around the 15th, 75th and 95th percentiles of the distribution. The full distribution is therefore summarised by a practical number of scenarios to run through ECL models representing an upside, the base case, and a downside scenario weighted at 30 per cent each, together with a severe downside scenario weighted at 10 per cent. The scenario weights represent the distribution of economic scenarios and not subjective views on likelihood. The inclusion of a severe downside scenario with a smaller weighting ensures that the non-linearity of losses in the tail of the distribution is adequately captured. Macroeconomic projections may employ reversionary techniques to adjust the paths of economic drivers towards long-run equilibria after a reasonable forecast horizon. The Group does not use such techniques to force the MES scenarios to revert to the base case planning view. Utilising such techniques would be expected to be immaterial for expected credit losses since loss sensitivity is highest over the initial five years of the projections. Most assets are expected to have matured, or reached the end of their behavioural life before the five-year horizon.

A forum under the chairmanship of the Chief Economist meets at least quarterly to review and, if appropriate, recommend changes to the method by which economic scenarios are generated, for approval by the Chief Financial Officer and Chief Risk Officer. In June 2022, the Group judged it appropriate to include an adjusted severe downside scenario to incorporate a high CPI inflation and UK Bank Rate profiles and to adopt this adjusted severe downside scenario to calculate the Group’s ECL. This is because the historic macroeconomic and loan loss data upon which the scenario model is calibrated imply an association of downside economic outcomes with easier monetary policy, and therefore low interest rates. The adjustment is considered to better reflect the risks around the Group’s base case view in an economic environment where the potential for supply shocks remains an elevated concern. The Group has continued to include a non-modelled severe downside scenario for Group ECL calculations for 31 December 2023 reporting.

The Group’s base case economic scenario has been updated to reflect ongoing geopolitical developments, and further evidence of easing of inflationary pressures allowing shifts to less restrictive monetary policies globally. The Group’s updated base case scenario has three conditioning assumptions: first, the wars in Ukraine and the Middle East remain geographically contained and do not lead to a major escalation in energy prices; second, China’s economic stabilisation policy is effective; and third, less restrictive monetary and fiscal policy throughout this year.

Based on these assumptions and incorporating the economic data published in the fourth quarter, the Group’s base case scenario is for slow expansion in GDP and a rise in the unemployment rate alongside modest changes in residential and commercial property prices. Following a reduction in inflationary pressures, UK Bank Rate is expected to be lowered during 2024. Risks around this base case economic view lie in both directions and are largely captured by the generation of alternative economic scenarios.

The five-year average reflects the average annual growth rate, or level, over the five-year period. It includes movements within the current reporting year, such that the position as at 31 December 2023 covers the five years 2023 to 2027. The inclusion of the reporting year within the five-year period reflects the need to predict variables which remain unpublished at the reporting date and recognises that credit models utilise both level and annual changes. The use of calendar years maintains a comparability between the annual assumptions presented.

The peak or trough for any metric may occur intra year and therefore not be identifiable from the annual assumptions, so they are also disclosed. For GDP, house price growth and commercial real estate price growth, the peak, or trough, reflects the highest, or lowest cumulative quarterly position reached relative to the start of the five-year period, which as at 31 December 2023 is 1 January 2023. Given these metrics may exhibit increases followed by greater falls, the start to trough movements quoted may be smaller than the equivalent ‘peak to trough’ movement (and vice versa for start to peak). Unemployment, UK Bank Rate and CPI inflation reflect the highest, or lowest, quarterly level reached in the five-year period.


At 31 December 2023	2023 %	2024 %	2025 %	2026 %	2027 %	2023 to 2027 average %	Start to peak %	Start to trough %
Upside
Gross domestic product	0.3	1.5	1.7	1.7	1.9	1.4	8.1	0.2
Unemployment rate	4.0	3.3	3.1	3.1	3.1	3.3	4.2	3.0
House price growth	1.9	0.8	6.9	7.2	6.8	4.7	25.7	(1.2)
Commercial real estate price growth	(3.9)	9.0	3.8	1.3	1.3	2.2	11.5	(3.9)
UK Bank Rate	4.94	5.72	5.61	5.38	5.18	5.37	5.79	4.25
CPI inflation	7.3	2.7	3.1	3.2	3.1	3.9	10.2	2.1
Base case
Gross domestic product	0.3	0.5	1.2	1.7	1.9	1.1	6.4	0.2
Unemployment rate	4.2	4.9	5.2	5.2	5.0	4.9	5.2	3.9
House price growth	1.4	(2.2)	0.5	1.6	3.5	1.0	4.8	(1.2)
Commercial real estate price growth	(5.1)	(0.2)	0.1	0.0	0.8	(0.9)	(1.2)	(5.3)
UK Bank Rate	4.94	4.88	4.00	3.50	3.06	4.08	5.25	3.00
CPI inflation	7.3	2.7	2.9	2.5	2.2	3.5	10.2	2.1
Downside
Gross domestic product	0.2	(1.0)	(0.1)	1.5	2.0	0.5	3.4	(1.2)
Unemployment rate	4.3	6.5	7.8	7.9	7.6	6.8	8.0	3.9
House price growth	1.3	(4.5)	(6.0)	(5.6)	(1.7)	(3.4)	2.0	(15.7)
Commercial real estate price growth	(6.0)	(8.7)	(4.0)	(2.1)	(1.2)	(4.4)	(1.2)	(20.4)
UK Bank Rate	4.94	3.95	1.96	1.13	0.55	2.51	5.25	0.43
CPI inflation	7.3	2.8	2.7	1.8	1.1	3.2	10.2	1.0
Severe downside
Gross domestic product	0.1	(2.3)	(0.5)	1.3	1.8	0.1	1.0	(2.9)
Unemployment rate	4.5	8.7	10.4	10.5	10.1	8.8	10.5	3.9
House price growth	0.6	(7.6)	(13.3)	(12.7)	(7.5)	(8.2)	2.0	(35.0)
Commercial real estate price growth	(7.7)	(19.5)	(10.6)	(7.7)	(5.2)	(10.3)	(1.2)	(41.8)
UK Bank Rate – modelled	4.94	2.75	0.49	0.13	0.03	1.67	5.25	0.02
UK Bank Rate – adjusted1	4.94	6.56	4.56	3.63	3.13	4.56	6.75	3.00
CPI inflation – modelled	7.3	2.7	2.2	0.9	(0.2)	2.6	10.2	(0.3)
CPI inflation – adjusted1	7.6	7.5	3.5	1.3	1.0	4.2	10.2	0.9
Probability-weighted
Gross domestic product	0.3	0.1	0.8	1.6	1.9	0.9	5.4	0.1
Unemployment rate	4.2	5.3	5.9	5.9	5.7	5.4	6.0	3.9
House price growth	1.4	(2.5)	(0.9)	(0.3)	1.8	(0.1)	2.0	(2.8)
Commercial real estate price growth	(5.3)	(1.9)	(1.1)	(1.0)	(0.2)	(1.9)	(1.2)	(9.9)
UK Bank Rate – modelled	4.94	4.64	3.52	3.02	2.64	3.75	5.25	2.59
UK Bank Rate – adjusted1	4.94	5.02	3.93	3.37	2.95	4.04	5.42	2.89
CPI inflation – modelled	7.3	2.7	2.8	2.3	1.9	3.4	10.2	1.9
CPI inflation – adjusted1	7.4	3.2	3.0	2.4	2.0	3.6	10.2	2.0


Base case scenario by quarter1 At 31 December 2023	First quarter 2023 %	Second quarter 2023 %	Third quarter 2023 %	Fourth quarter 2023 %	First quarter 2024 %	Second quarter 2024 %	Third quarter 2024 %	Fourth quarter 2024 %
Gross domestic product	0.3	0.0	(0.1)	0.0	0.1	0.2	0.3	0.3
Unemployment rate	3.9	4.2	4.2	4.3	4.5	4.8	5.0	5.2
House price growth	1.6	(2.6)	(4.5)	1.4	(1.1)	(1.5)	0.5	(2.2)
Commercial real estate price growth	(18.8)	(21.2)	(18.2)	(5.1)	(4.1)	(3.8)	(2.2)	(0.2)
UK Bank Rate	4.25	5.00	5.25	5.25	5.25	5.00	4.75	4.50
CPI inflation	10.2	8.4	6.7	4.0	3.8	2.1	2.3	2.8


At 31 December 2022	2022 %	2023 %	2024 %	2025 %	2026 %	2022 to 2026 average %	Start to peak %	Start to trough %
Upside
Gross domestic product	4.1	0.1	1.1	1.7	2.1	1.8	6.5	0.4
Unemployment rate	3.5	2.8	3.0	3.3	3.4	3.2	3.8	2.8
House price growth	2.4	(2.8)	6.5	9.0	8.0	4.5	24.8	(1.1)
Commercial real estate price growth	(9.4)	8.5	3.5	2.6	2.3	1.3	7.2	(9.4)
UK Bank Rate	1.94	4.95	4.98	4.63	4.58	4.22	5.39	0.75
CPI inflation	9.0	8.3	4.2	3.3	3.0	5.5	10.7	2.9
Base case
Gross domestic product	4.0	(1.2)	0.5	1.6	2.1	1.4	4.3	(1.1)
Unemployment rate	3.7	4.5	5.1	5.3	5.1	4.8	5.3	3.6
House price growth	2.0	(6.9)	(1.2)	2.9	4.4	0.2	6.4	(6.3)
Commercial real estate price growth	(11.8)	(3.3)	0.9	2.8	3.1	(1.8)	7.2	(14.8)
UK Bank Rate	1.94	4.00	3.38	3.00	3.00	3.06	4.00	0.75
CPI inflation	9.0	8.3	3.7	2.3	1.7	5.0	10.7	1.6
Downside
Gross domestic product	3.9	(3.0)	(0.5)	1.4	2.1	0.8	1.2	(3.6)
Unemployment rate	3.8	6.3	7.5	7.6	7.2	6.5	7.7	3.6
House price growth	1.6	(11.1)	(9.8)	(5.6)	(1.5)	(5.4)	6.4	(24.3)
Commercial real estate price growth	(13.9)	(15.0)	(3.7)	0.4	1.4	(6.4)	7.2	(29.6)
UK Bank Rate	1.94	2.93	1.39	0.98	1.04	1.65	3.62	0.75
CPI inflation	9.0	8.2	3.3	1.3	0.3	4.4	10.7	0.2
Severe downside
Gross domestic product	3.7	(5.2)	(1.0)	1.3	2.1	0.1	0.7	(6.4)
Unemployment rate	4.1	9.0	10.7	10.4	9.7	8.8	10.7	3.6
House price growth	1.1	(14.8)	(18.0)	(11.5)	(4.2)	(9.8)	6.4	(40.1)
Commercial real estate price growth	(17.3)	(28.8)	(9.9)	(1.3)	3.2	(11.6)	7.2	(47.8)
UK Bank Rate – modelled	1.94	1.41	0.20	0.13	0.14	0.76	3.50	0.12
UK Bank Rate – adjusted1	2.44	7.00	4.88	3.31	3.25	4.18	7.00	0.75
CPI inflation – modelled	9.0	8.2	2.6	(0.1)	(1.6)	3.6	10.7	(1.7)
CPI inflation – adjusted1	9.7	14.3	9.0	4.1	1.6	7.7	14.8	1.5
Probability-weighted
Gross domestic product	4.0	(1.8)	0.2	1.5	2.1	1.2	3.4	(1.8)
Unemployment rate	3.7	5.0	5.8	5.9	5.7	5.2	5.9	3.6
House price growth	1.9	(7.7)	(3.2)	0.7	2.9	(1.2)	6.4	(9.5)
Commercial real estate price growth	(12.3)	(5.8)	(0.8)	1.6	2.3	(3.1)	7.2	(18.6)
UK Bank Rate – modelled	1.94	3.70	2.94	2.59	2.60	2.76	3.89	0.75
UK Bank Rate – adjusted1	1.99	4.26	3.41	2.91	2.91	3.10	4.31	0.75
CPI inflation – modelled	9.0	8.3	3.6	2.1	1.4	4.9	10.7	1.3
CPI inflation – adjusted1	9.1	8.9	4.3	2.5	1.7	5.3	11.0	1.6


Base case scenario by quarter1 At 31 December 2022	First quarter 2022 %	Second quarter 2022 %	Third quarter 2022 %	Fourth quarter 2022 %	First quarter 2023 %	Second quarter 2023 %	Third quarter 2023 %	Fourth quarter 2023 %
Gross domestic product	0.6	0.1	(0.3)	(0.4)	(0.4)	(0.4)	(0.2)	(0.1)
Unemployment rate	3.7	3.8	3.6	3.7	4.0	4.4	4.7	4.9
House price growth	11.1	12.5	9.8	2.0	(3.0)	(8.4)	(9.8)	(6.9)
Commercial real estate price growth	18.0	18.0	8.4	(11.8)	(16.9)	(19.8)	(15.9)	(3.3)
UK Bank Rate	0.75	1.25	2.25	3.50	4.00	4.00	4.00	4.00
CPI inflation	6.2	9.2	10.0	10.7	10.0	8.9	8.0	6.1

The table below shows the Group’s ECL for the probability-weighted, upside, base case, downside and severe downside scenarios, with the severe downside scenario incorporating adjustments made to CPI inflation and UK Bank Rate paths. The stage allocation for an asset is based on the overall scenario probability-weighted probability of default and hence the staging of assets is constant across all the scenarios. In each economic scenario the ECL for individual assessments is held constant reflecting the basis on which they are evaluated. Judgemental adjustments applied through changes to model inputs or parameters, or more qualitative post model adjustments, are apportioned across the scenarios in proportion to modelled ECL where this better reflects the sensitivity of these adjustments to each scenario. The probability-weighted view shows the extent to which a higher ECL allowance has been recognised to take account of multiple economic scenarios relative to the base case; the uplift being £678 million compared to £692 million at 31 December 2022.


	At 31 December 2023					At 31 December 2022
	Probability- weighted £m	Upside £m	Base case £m	Downside £m	Severe downside £m	Probability- weighted £m	Upside £m	Base case £m	Downside £m	Severe downside £m
UK mortgages	1,115	395	670	1,155	4,485	1,209	514	790	1,434	3,874
Credit cards	810	600	771	918	1,235	763	596	727	828	1,180
Other Retail	945	850	920	981	1,200	1,016	907	992	1,056	1,290

Commercial Banking	1,182	793	1,013	1,383	2,250	1,869	1,459	1,656	2,027	3,261
Other	32	32	32	32	32	46	46	46	47	47
ECL allowance	4,084	2,670	3,406	4,469	9,202	4,903	3,522	4,211	5,392	9,652

The impact of isolated changes in the UK unemployment rate and House Price Index (HPI) has been assessed on a univariate basis. Although such changes would not be observed in isolation, as economic indicators tend to be correlated in a coherent scenario, this gives insight into the sensitivity of the Group’s ECL to gradual changes in these two critical economic factors. The assessment has been made against the base case with staging held flat to the reported probability-weighted view and is assessed through the direct impact on modelled ECL and only includes judgemental adjustments applied through changes to model inputs.

The table below shows the Group’s ECL and drawn balances for the upside, base case, downside and severe downside scenarios, with staging of assets based on each specific scenario probability of default. In each economic scenario the ECL for individual assessments is held constant reflecting the basis on which they are evaluated. Judgemental adjustments applied through changes to model inputs or parameters, or more qualitative post-model adjustments, are apportioned across the scenarios in proportion to modelled ECL where this better reflects the sensitivity of these adjustments to each scenario. A probability-weighted scenario is not shown as this view does not reflect the basis on which ECL is calculated. Comparing the probability-weighted ECL in the table above to the base case ECL with base case scenario specific staging, as shown in the table below, results in an uplift of £596 million compared to £820 million at 31 December 2022.


	Drawn balances1				ECL allowance				Coverage ratio2
At 31 December 2023	Upside £m	Base case £m	Downside £m	Severe downside £m	Upside £m	Base case £m	Downside £m	Severe downside £m	Upside %	Base case %	Downside %	Severe downside %
Stage 1
UK mortgages	270,131	269,581	266,388	129,736	20	40	84	153	–	–	–	0.1
Credit cards	13,338	12,668	12,109	10,966	169	211	242	298	1.3	1.7	2.0	2.7
Other Retail	39,260	38,939	38,373	30,202	360	384	404	448	0.9	1.0	1.1	1.5
Commercial Banking	98,202	97,394	92,919	78,781	165	260	376	431	0.2	0.3	0.4	0.6
Other	7,632	7,632	7,632	7,632	14	16	17	20	0.2	0.2	0.2	0.3
Total	428,563	426,214	417,421	257,317	728	911	1,123	1,350	0.2	0.2	0.3	0.5

Stage 2
UK mortgages	24,998	25,548	28,741	165,393	73	139	316	4,074	0.3	0.6	1.1	2.5
Credit cards	2,195	2,865	3,424	4,567	302	437	567	859	13.7	15.3	16.6	18.8
Other Retail	5,711	6,032	6,598	14,769	325	378	424	619	5.7	6.3	6.4	4.2
Commercial Banking	4,487	5,295	9,770	23,908	259	379	722	2,466	5.8	7.2	7.4	10.3
Other	–	–	–	–	–	–	–	–	–	–	–	–
Total	37,391	39,740	48,533	208,637	959	1,333	2,029	8,018	2.6	3.4	4.2	3.8

Stage 3
UK mortgages	4,337	4,337	4,337	4,337	78	225	457	963	1.8	5.2	10.5	22.2
Credit cards	284	284	284	284	122	122	122	122	43.0	43.0	43.0	43.0
Other Retail	452	452	452	452	238	242	248	261	52.7	53.5	54.9	57.7
Commercial Banking	2,068	2,068	2,068	2,068	426	426	426	426	20.6	20.6	20.6	20.6
Other	39	39	39	39	16	16	16	16	41.0	41.0	41.0	41.0
Total	7,180	7,180	7,180	7,180	880	1,031	1,269	1,788	12.3	14.4	17.7	24.9

POCI
UK mortgages3	7,854	7,854	7,854	7,854	213	213	213	213	2.7	2.7	2.7	2.7

Total
UK mortgages	307,320	307,320	307,320	307,320	384	617	1,070	5,403	0.1	0.2	0.4	1.8
Credit cards	15,817	15,817	15,817	15,817	593	770	931	1,279	3.8	4.9	5.9	8.1
Other Retail	45,423	45,423	45,423	45,423	923	1,004	1,076	1,328	2.0	2.2	2.4	2.9
Commercial Banking	104,757	104,757	104,757	104,757	850	1,065	1,524	3,323	0.8	1.0	1.5	3.2
Other	7,671	7,671	7,671	7,671	30	32	33	36	0.4	0.4	0.4	0.5
Total	480,988	480,988	480,988	480,988	2,780	3,488	4,634	11,369	0.6	0.7	1.0	2.4


	Drawn balances1				ECL allowance				Coverage ratio2
At 31 December 2022	Upside £m	Base case £m	Downside £m	Severe downside £m	Upside £m	Base case £m	Downside £m	Severe downside £m	Upside %	Base case %	Downside %	Severe downside %
Stage 1
UK mortgages	272,780	264,062	259,684	112,102	39	55	91	106	–	–	–	0.1
Credit cards	12,277	11,583	11,111	9,049	112	157	195	255	0.9	1.4	1.8	2.8
Other Retail	36,001	35,356	34,807	30,927	242	274	298	346	0.7	0.8	0.9	1.1
Commercial Banking	99,319	98,481	87,192	51,452	137	222	323	339	0.1	0.2	0.4	0.7
Other	4,301	4,301	4,301	4,301	42	42	43	43	1.0	1.0	1.0	1.0
Total	424,678	413,783	397,095	207,831	572	750	950	1,089	0.1	0.2	0.2	0.5

Stage 2
UK mortgages	26,520	35,238	39,616	187,198	137	242	557	6,649	0.5	0.7	1.4	3.6
Credit cards	2,426	3,120	3,592	5,654	338	449	534	952	13.9	14.4	14.9	16.8
Other Retail	3,671	4,316	4,865	8,745	390	453	501	839	10.6	10.5	10.3	9.6
Commercial Banking	6,663	7,501	18,790	54,530	214	304	745	3,777	3.2	4.1	4.0	6.9
Other	–	–	–	–	–	–	–	–	–	–	–	–
Total	39,280	50,175	66,863	256,127	1,079	1,448	2,337	12,217	2.7	2.9	3.5	4.8

Stage 3
UK mortgages	3,416	3,416	3,416	3,416	40	184	443	840	1.2	5.4	13.0	24.6
Credit cards	289	289	289	289	113	113	113	113	39.1	39.1	39.1	39.1
Other Retail	558	558	558	558	254	257	260	264	45.5	46.1	46.6	47.3
Commercial Banking	3,371	3,371	3,371	3,371	1,074	1,074	1,074	1,074	31.9	31.9	31.9	31.9
Other	6	6	6	6	4	4	4	4	66.7	66.7	66.7	66.7
Total	7,640	7,640	7,640	7,640	1,485	1,632	1,894	2,295	19.4	21.4	24.8	30.0

POCI
UK mortgages3	9,622	9,622	9,622	9,622	253	253	253	253	2.6	2.6	2.6	2.6

Total
UK mortgages	312,338	312,338	312,338	312,338	469	734	1,344	7,848	0.2	0.2	0.4	2.5
Credit cards	14,992	14,992	14,992	14,992	563	719	842	1,320	3.8	4.8	5.6	8.8
Other Retail	40,230	40,230	40,230	40,230	886	984	1,059	1,449	2.2	2.4	2.6	3.6
Commercial Banking	109,353	109,353	109,353	109,353	1,425	1,600	2,142	5,190	1.3	1.5	2.0	4.7
Other	4,307	4,307	4,307	4,307	46	46	47	47	1.1	1.1	1.1	1.1
Total	481,220	481,220	481,220	481,220	3,389	4,083	5,434	15,854	0.7	0.8	1.1	3.3

The Group continues to develop capabilities to quantify the potential impact of climate risks on ECL. This includes identifying the climate-related risk drivers that could influence future credit losses for loan portfolios that have the highest sensitivity to climate risks and commencing the use of more quantitative analysis on the impact of these risk drivers on ECL. This initial assessment has focused on specific climate-related risk drivers, with the intention to broaden and further develop the assessment in future years. The approach leverages the Group’s climate scenario analysis, to identify the potential physical and transition risk impacts on credit quality. Retail mortgages and Commercial Banking portfolios were identified to have the highest sensitivity to climate risk, with both physical and transition risk drivers assessed. The assessment used a combination of macroeconomic and sector level modelling alongside similar techniques used in estimating judgemental adjustments for non-climate related risks at sector and segment level.

An assessment was performed on the Group’s internally generated economic scenarios used in the measurement of expected credit losses against external scenarios published by the Network for Greening the Financial System (NGFS) in November 2023. The analysis found the Group’s base case, incorporating the impact of assumed policies over a five-year planning horizon, was positioned broadly within the range of the NGFS climate scenarios considered to be the most plausible, with limited differences in both directions for key impairment drivers. The Group’s MES downside and severe downside together comprising 40 per cent weighting in ECL calculations, are generally more severe than the most adverse NGFS scenario (Net Zero 2050). The assessment suggests that no material changes are required to the Group’s existing suite of economic scenarios.

In Retail, the potential incremental impact of climate factors on key economic drivers has been isolated from a range of NGFS scenarios management judged most plausible (Current Policies, Delayed Transition and Fragmented World scenarios). The incremental risk to ECL was then quantified by overlaying the specific climate impact of these scenarios on macroeconomic drivers, the Group’s base case and MES scenarios. Given these more plausible scenarios exhibited very similar impacts, management modelled the ECL impact from the Delayed Transition scenario, which assumes strong environmental policies are needed to compensate for the absence of early action. The results from the most material portfolios, UK mortgages and credit card ECL models allowed management to conclude on an immaterial ECL impact for Retail.

In Commercial Banking, an exploratory top-down analysis using newly developed sectoral modelling was adopted to estimate the ECL impact of climate risk on commercial credit conditions. This assessment specifically segmented agriculture, automotive, transport, oil and gas and real estate sectors where climate impacts were judged to be more significant. Sector-specific, climate-adjusted credit cycle indices (CCI) were used to calculate probability of default and resulting ECL. These adjusted CCI model inputs combined external NGFS scenarios with client level valuation impacts where available, alongside historic impairment data. Taking into account methodological limitations, the additional ECL required was shown to be immaterial. However, the analysis has been an informative exercise to take further forward in 2024.

In the UK mortgage portfolio, an affordability stress for customers was applied, by considering a scenario with minimum EPC requirements being introduced for the UK and estimated average retrofitting costs to bring the estimated EPC distribution for the current UK mortgage portfolio into alignment. The potential default risk from additional costs linked to retrofitting risks was assessed, with independent EPC data used to estimate the ECL impact from increased costs to customers for upgrading or retrofitting to meet a potential legislative target of EPC rating of C by 2028 for BTL. The provision impact was assessed using sensitivity analysis that utilises the relationship between disposable income and probability of default. The impact on ECL has been estimated to be less than £5 million for the potential legislative requirement in place for BTL.

Consideration has also been given to flooding risk – a delayed transition climate outlook, out to 2035 was assessed, resulting in over 80 per cent of the book expected to have no risk of flood damage. The impact on ECL related to the affordability risk from flood damage has been estimated to be immaterial. Whilst this supports no judgemental adjustment to ECL being required, the narrow scope does not capture the wider impact on loss rates emanating from being located in a high risk area.

The assessments are limited due to the degree of uncertainty underpinning key assumptions used, as well as the developmental nature of the data, approach and models used in the quantification. These include, but are not limited to the analyses being restricted to PD impacts only, client level valuation impacts not incorporating climate transition plans, only considering the most material hazard (flooding) for UK mortgages and more broadly the political landscape, future climate data enhancements and further model development.

However, the conclusions made using the Group’s best internal view of likely outcomes across all analyses further strengthens management’s view there is a low residual risk of material error or omission in the Group’s financial statements due to climate-related risks at present and as a result no adjustments have been made to the ECL measured as at 31 December 2023. The current behavioural lives of the Group’s lending dilutes the potential exposure to the later emergence of potential physical climate impacts, with the incorporation of climate risk within underwriting assessments in Commercial Banking providing further mitigation on more recent originations.