v3.25.4

Allowance for expected credit losses | 12 Months Ended
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Dec. 31, 2025
Disclosure of allowance for expected credit losses [Abstract] |
Allowance for expected credit losses | Note 21: Allowance for expected credit losses 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 2025, the Group’s expected credit loss allowance was £3,228 million (2024: £3,481 million), of which £3,031 million (2024: £3,211 million) was in respect of drawn balances. The Group’s total expected credit loss allowances were as follows:
|  | At 31 December 2025 |  | At 31 December 2024
Allowance for expected credit losses |  | Stage 1 £m |  | Stage 2 £m |  | Stage 3 £m |  | POCI £m |  | Total £m |  | Stage 1 £m |  | Stage 2 £m |  | Stage 3 £m |  | POCI £m |  | Total £m
In respect of: |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
Loans and advances to banks |  | 1 |  | – |  | – |  | – |  | 1 |  | 1 |  | – |  | – |  | – |  | 1
UK mortgages |  | 51 |  | 207 |  | 309 |  | 159 |  | 726 |  | 53 |  | 273 |  | 335 |  | 187 |  | 848
Credit cards |  | 145 |  | 248 |  | 121 |  | – |  | 514 |  | 149 |  | 297 |  | 133 |  | – |  | 579
Other |  | 368 |  | 343 |  | 226 |  | – |  | 937 |  | 329 |  | 326 |  | 227 |  | – |  | 882
Retail |  | 564 |  | 798 |  | 656 |  | 159 |  | 2,177 |  | 531 |  | 896 |  | 695 |  | 187 |  | 2,309
Commercial Banking |  | 173 |  | 279 |  | 382 |  | – |  | 834 |  | 205 |  | 264 |  | 413 |  | – |  | 882
Other |  | – |  | – |  | – |  | – |  | – |  | – |  | – |  | – |  | – |  | –
Loans and advances to customers |  | 737 |  | 1,077 |  | 1,038 |  | 159 |  | 3,011 |  | 736 |  | 1,160 |  | 1,108 |  | 187 |  | 3,191
Debt securities |  | 4 |  | – |  | 1 |  | – |  | 5 |  | 3 |  | – |  | 1 |  | – |  | 4
Financial assets at amortised cost |  | 742 |  | 1,077 |  | 1,039 |  | 159 |  | 3,017 |  | 740 |  | 1,160 |  | 1,109 |  | 187 |  | 3,196
Other assets |  | 6 |  | – |  | 8 |  | – |  | 14 |  | 7 |  | – |  | 8 |  | – |  | 15
Provisions in relation to loan commitments and financial guarantees | 113 |  | 83 |  | 1 |  | – |  | 197 |  | 142 |  | 126 |  | 2 |  | – |  | 270
Total |  | 861 |  | 1,160 |  | 1,048 |  | 159 |  | 3,228 |  | 889 |  | 1,286 |  | 1,119 |  | 187 |  | 3,481
Expected credit loss in respect of financial assets at fair value through other comprehensive income (memorandum item) |  | 3 |  | – |  | – |  | – |  | 3 |  | 4 |  | – |  | – |  | – |  | 4
The calculation of the Group’s expected credit loss allowances and provisions against loan commitments and guarantees, which are set out above, requires the Group to make a number of judgements, assumptions and estimates. The most significant are set out below: Critical accounting judgements and key sources of estimation uncertainty
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
Definition of default 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. 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. Significant increase in credit risk 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. 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. The Group uses both quantitative and qualitative indicators to determine whether there has been a SICR for an asset. The setting of precise trigger points combined with risk indicators requires judgement and the use of different trigger points may have a material impact upon the ECL allowance. The Group monitors the effectiveness of SICR criteria on an ongoing basis. For UK mortgages a doubling of PD since origination is set as a quantitative SICR trigger. All originations post IFRS 9 adoption incorporate forward looking information, and for recent Interest Only accounts the likelihood of default occurring at the end of term. This is supplemented by qualitative triggers including where customers have surpassed their original contractual term through use of term extensions, where fraud is evident, or where an account is in arrears. Note 21: Allowance for expected credit losses continued For credit cards, loans and overdrafts an increase of three PD grades since origination on the retail master scale (RMS) shown below is set as a quantitative SICR trigger. Assets are also assumed to have suffered a SICR if they have either been in arrears on three occasions, or in default once, in the past 12 months.
RMS grade | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14
PD boundary 1 (%) | 0.10 | 0.40 | 0.80 | 1.20 | 2.50 | 4.50 | 7.50 | 10.00 | 14.00 | 20.00 | 30.00 | 45.00 | 99.99 | 100.00
1 Probability-weighted annualised lifetime probability of default. For Commercial Banking a doubling of PD with a minimum increase in PD of 1% since origination is treated as a SICR. This is complemented with the use of internal credit risk classifications and ratings as qualitative indicators to identify a SICR. The Group does not use the low credit risk exemption in its staging assessments, though more simplistic SICR criteria are applied for portfolios not listed above. All financial assets are assumed to have suffered a SICR if they are more than 30 days past due. Individual assessments and application of judgement in adjustments to modelled ECL The table below analyses total ECL allowances by portfolio, separately identifying the amounts that have been modelled, those that have been individually assessed and those arising through the application of judgemental adjustments.
| At 31 December 2025 |  | At 31 December 2024
| Modelled ECL £m | Individually assessed £m |  | Judgemental adjustments £m |  | Total £m |  | Modelled ECL £m |  | Individually assessed £m |  | Judgemental adjustments £m |  | Total £m
UK mortgages | 623 |  | – |  | 108 |  | 731 |  | 720 |  | – |  | 132 |  | 852
Credit cards | 540 |  | – |  | 63 |  | 603 |  | 681 |  | – |  | (7) |  | 674
Other Retail | 916 |  | – |  | 75 |  | 991 |  | 860 |  | – |  | 90 |  | 950
Commercial Banking | 555 |  | 355 |  | (22) |  | 888 |  | 894 |  | 354 |  | (259) |  | 989
Other | 15 |  | – |  | – |  | 15 |  | 16 |  | – |  | – |  | 16
Total | 2,649 |  | 355 |  | 224 |  | 3,228 |  | 3,171 |  | 354 |  | (44) |  | 3,481
Individually assessed ECL 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% likelihood taken into account in establishing a probability-weighted ECL. At 31 December 2025, individually assessed provisions for Commercial Banking were £355 million (2024: £354 million) which reflected a range of £276 million to £440 million (2024: £309 million to £437 million), based on the range of alternative outcomes considered. Application of judgement in adjustments to modelled ECL 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 models or data inputs may be identified through these assessments and review of model outputs, which may require appropriate judgemental adjustments to the ECL. 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 (in-model adjustments), through to more qualitative post-model adjustments. UK mortgages: £108 million (2024: £132 million) These adjustments principally comprise: Repossession risk: £85 million (2024: £110 million) Additional ECL continues to be held judgementally to capture the potential repossession and recovery risk from specific subsets of largely long-term defaulted cases. This is alongside an adjustment to capture a longer duration between default and repossession than model assumptions use on existing and future defaults. The reduction in the period reflects methodology refinement and latest data points on the population judged at risk. Adjustment for specific segments: £13 million (2024: £13 million) The Group monitors risks across specific segments of its portfolios which may not be fully captured through collective models. The judgement for fire safety and cladding uncertainty remains in place as the only Mortgages segment sufficiently material to address, given evidence of cases with defective cladding, or other fire safety issues. Credit cards: £63 million (2024: £(7) million) and Other Retail: £75 million (2024: £90 million) These adjustments principally comprise: Lifetime extension: Credit cards: £49 million (2024: £55 million) and Other Retail: £9 million (2024: £10 million) 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, to a more representative lifetime. Incremental defaults beyond year three are calculated through the extrapolation of the default trajectory observed throughout the three years and beyond. Adjustments to loss rates: Credit cards: £nil (2024: £(57) million) and Other Retail: £25 million (2024: £47 million) A number of adjustments were previously made to the loss given default (LGD) assumptions used within unsecured and motor credit models. For unsecured portfolios, the previous adjustments reflected the impact of changes in collection debt sale strategy on the Group’s LGD models, incorporating up to date customer performance and forward flow debt sale pricing. These impacts have now been integrated into the model solution following model refinements. The remaining adjustment for UK Motor Finance, within Other Retail, captures the observed loss rates and the latest outlook on used car prices. Note 21: Allowance for expected credit losses continued Commercial Banking: £(22) million (2024: £(259) million) These adjustments principally comprise: Corporate insolvency rates: £(122) million (2024: £(253) million) The volume of UK corporate insolvencies continues to exhibit an elevated trend beyond December 2019 levels, revealing a marked misalignment between observed UK corporate insolvencies and the Group’s equivalent credit performance. This dislocation gives rise to uncertainty over the drivers of the observed trends in the metric 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 stable credit performance, a negative adjustment is applied by reverting judgementally to the long-term average of the insolvency rate. The scale of the negative adjustment reduced in the period reflecting both the reduction in observed actual UK corporate insolvencies rates, narrowing the gap of the misalignment, as well from changes due to the interaction with the implementation of loss rate model enhancements in the period. Adjustments to loss given defaults (LGDs): £50 million (2024: £(80) million) In preceding years, adjustments have been required to mitigate limitations identified in the modelling approach which were causing loss given defaults to be inflated. These included the lack of benefit from amortisation of exposures relative to collateral values at default, and the need to reflect an exposure-weighted calculation. These two adjustments have been released following respective enhancements to models. One remaining adjustment remains for a specific segment of the SME portfolio which judgementally applies a more appropriate blended LGD rate from credit risk profile segments more aligned to experience. Corporate income gearing (CIG) adjustment: £nil (2024: £37 million) An adjustment was raised at 31 December 2024, based upon the assessment of Corporate Income Gearing, a model parameter for affordability used in Commercial Banking. This adjustment reversed the modelled ECL release seen from updating CIG drivers (interest rates), given interest rates had merely reached a plateau which translated into a slower year-on-year increase. This slowdown gave a modelled ECL release not judged representative of the continued pressure on borrowers and business margins. However, the maintenance of those improvements in drivers over the first half of 2025 (including sustained lower base rates) gives support for the modelled release to now be recognised, removing the judgemental adjustment. Commercial Real Estate (CRE) price reduction: £nil (2024: £35 million) This adjustment recognised the potential impact on loss rates from valuations on specific CRE sectors where evidence suggested valuations may lag achievable levels, notably in cases of stressed sale. Recent performance reflects stabilisation in valuations and improved confidence in the CRE sector, removing the judgemental adjustment. Global tariff and geo-political disruption risks: £50 million (2024: £nil) This new adjustment is to recognise the potential risks to specific drivers across various corporate sectors not reflected in broad macroeconomic model drivers. These are potential nuanced risks to businesses inherent in the base case which could also worsen in the downside scenarios. This assessment is judgemental and apportioned across all sectors given the uncertainty of how these risks would emerge. Generation of multiple economic scenarios 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% each, together with a severe downside scenario weighted at 10%. 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 minimal after the initial five years of the projections. 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. Since 30 September 2025, the non-modelled adjustments previously applied to UK Bank Rate and CPI inflation in the severe downside scenario have been removed. This is because the incremental ECL impact is no longer considered sufficiently material to justify their application. Accordingly, its removal has had no material impact on ECL. Note 21: Allowance for expected credit losses continued Base case and MES economic assumptions The Group’s base case economic scenario has been updated to reflect global developments and changes in domestic economic policy. The Group’s updated base case scenario has the following conditioning assumptions. First, developments in global conflicts, technology or financial sector issues do not cause a significant degree of financial market volatility. Second, the US effective tariff rate is maintained at levels prevailing at the balance sheet date pending a switch to a sector-based tariff framework. Third, the UK’s macroeconomic framework for monetary and fiscal policy remains in place, alongside broader continuity on other areas of government policy. Based on these assumptions and incorporating the economic data published for the third quarter of 2025, the Group’s base case scenario is for a slow expansion in gross domestic product (GDP) and a further rise in the unemployment rate alongside small gains in residential and commercial property prices. With underlying inflationary pressures expected to recede, modest further reductions in UK Bank Rate are expected to continue in 2026. Risks around this base case economic view lie in both directions and are largely captured by the generation of alternative economic scenarios. The Group has taken into account the latest available information at the reporting date in defining its base case scenario and generating alternative economic scenarios. The scenarios include forecasts for key variables as at the fourth quarter of 2025. Actual data for this period, or restatements of past data, may have since emerged prior to publication and have not been included. Scenarios by year The key UK economic assumptions made by the Group are shown in the following tables across a number of measures explained below. Annual assumptions Gross domestic product (GDP) growth and Consumer Price Index (CPI) inflation are presented as an annual change, house price growth and commercial real estate price growth are presented as the growth in the respective indices over each year. Unemployment rate and UK Bank Rate are averages over the year. Five year average 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 2025 covers the five years 2025 to 2029. 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. Five year start to peak and trough 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 2025 is 1 January 2025. 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. Note 21: Allowance for expected credit losses continued
At 31 December 2025 | 2025 % | 2026 % | 2027 % | 2028 % | 2029 % | 2025 to 2029 average % | Start to peak % | Start to trough %
Upside |  |  |  |  |  |  |  |
Gross domestic product growth | 1.4 | 2.0 | 2.3 | 1.6 | 1.6 | 1.8 | 9.4 | 0.7
Unemployment rate | 4.8 | 4.2 | 3.2 | 3.1 | 3.2 | 3.7 | 5.1 | 3.0
House price growth | 0.8 | 3.5 | 7.1 | 6.9 | 6.0 | 4.8 | 26.4 | (0.1)
Commercial real estate price growth | 1.2 | 7.9 | 4.9 | 1.7 | 0.8 | 3.2 | 17.3 | 0.6
UK Bank Rate | 4.13 | 3.94 | 4.59 | 5.07 | 5.33 | 4.61 | 5.39 | 3.75
CPI inflation | 3.4 | 2.6 | 2.4 | 2.8 | 3.1 | 2.9 | 3.8 | 2.1
Base case |  |  |  |  |  |  |  |
Gross domestic product growth | 1.4 | 1.2 | 1.4 | 1.5 | 1.6 | 1.4 | 7.6 | 0.7
Unemployment rate | 4.8 | 5.2 | 4.8 | 4.6 | 4.5 | 4.8 | 5.3 | 4.5
House price growth | 0.8 | 1.6 | 1.9 | 2.2 | 3.1 | 1.9 | 9.8 | (0.1)
Commercial real estate price growth | 1.2 | 0.6 | 1.7 | 0.5 | 0.2 | 0.9 | 4.4 | 0.6
UK Bank Rate | 4.13 | 3.44 | 3.25 | 3.44 | 3.50 | 3.55 | 4.50 | 3.25
CPI inflation | 3.4 | 2.6 | 2.2 | 2.2 | 2.3 | 2.6 | 3.8 | 2.1
Downside |  |  |  |  |  |  |  |
Gross domestic product growth | 1.4 | (0.3) | (0.5) | 1.1 | 1.6 | 0.7 | 3.6 | 0.1
Unemployment rate | 4.8 | 6.6 | 7.5 | 7.4 | 7.0 | 6.7 | 7.6 | 4.5
House price growth | 0.8 | (0.2) | (4.7) | (5.7) | (2.8) | (2.6) | 0.9 | (12.2)
Commercial real estate price growth | 1.2 | (7.1) | (4.2) | (2.7) | (2.3) | (3.1) | 1.3 | (14.4)
UK Bank Rate | 4.13 | 2.74 | 1.09 | 0.75 | 0.52 | 1.85 | 4.50 | 0.45
CPI inflation | 3.4 | 2.6 | 2.0 | 1.4 | 1.0 | 2.1 | 3.8 | 0.8
Severe downside |  |  |  |  |  |  |  |
Gross domestic product growth | 1.4 | (1.9) | (1.8) | 0.7 | 1.4 | 0.0 | 1.3 | (2.8)
Unemployment rate | 4.8 | 8.3 | 10.2 | 9.9 | 9.4 | 8.5 | 10.3 | 4.5
House price growth | 0.8 | (1.2) | (11.1) | (12.2) | (7.8) | (6.5) | 0.8 | (28.4)
Commercial real estate price growth | 1.2 | (17.4) | (9.8) | (7.4) | (5.4) | (8.0) | 1.3 | (34.0)
UK Bank Rate | 4.13 | 1.91 | 0.10 | 0.03 | 0.01 | 1.24 | 4.50 | 0.01
CPI inflation | 3.4 | 2.6 | 1.7 | 0.5 | (0.4) | 1.6 | 3.8 | (0.7)
Probability-weighted |  |  |  |  |  |  |  |
Gross domestic product growth | 1.4 | 0.7 | 0.8 | 1.3 | 1.6 | 1.2 | 6.1 | 0.7
Unemployment rate | 4.8 | 5.6 | 5.7 | 5.5 | 5.4 | 5.4 | 5.8 | 4.5
House price growth | 0.8 | 1.3 | 0.2 | (0.2) | 1.1 | 0.6 | 2.8 | (0.1)
Commercial real estate price growth | 1.2 | (1.3) | (0.3) | (0.9) | (0.9) | (0.4) | 1.3 | (2.6)
UK Bank Rate | 4.13 | 3.23 | 2.69 | 2.78 | 2.81 | 3.13 | 4.50 | 2.64
CPI inflation | 3.4 | 2.6 | 2.2 | 2.0 | 1.9 | 2.4 | 3.8 | 1.8
Base case scenario by quarter 1 At 31 December 2025 | First quarter 2025 % | Second quarter 2025 % | Third quarter 2025 % | Fourth quarter 2025 % | First quarter 2026 % | Second quarter 2026 % | Third quarter 2026 % | Fourth quarter 2026 %
Gross domestic product growth | 0.7 | 0.3 | 0.1 | 0.3 | 0.3 | 0.3 | 0.4 | 0.4
Unemployment rate | 4.5 | 4.7 | 5.0 | 5.1 | 5.3 | 5.3 | 5.2 | 5.1
House price growth | 2.9 | 2.7 | 1.3 | 0.8 | 1.3 | 1.6 | 1.6 | 1.6
Commercial real estate price growth | 2.5 | 2.6 | 2.6 | 1.2 | 0.5 | 0.2 | 0.1 | 0.6
UK Bank Rate | 4.50 | 4.25 | 4.00 | 3.75 | 3.75 | 3.50 | 3.25 | 3.25
CPI inflation | 2.8 | 3.5 | 3.8 | 3.7 | 3.3 | 2.6 | 2.2 | 2.2
1 Gross domestic product growth is presented quarter-on-quarter. House price growth, commercial real estate growth and CPI inflation are presented year-on-year, i.e. from the equivalent quarter in the previous year. Unemployment rate and UK Bank Rate are presented as at the end of each quarter. Note 21: Allowance for expected credit losses continued
At 31 December 2024 | 2024 % | 2025 % | 2026 % | 2027 % | 2028 % | 2024 to 2028 average % | Start to peak % | Start to trough %
Upside |  |  |  |  |  |  |  |
Gross domestic product growth | 0.8 | 1.9 | 2.2 | 1.5 | 1.4 | 1.6 | 8.9 | 0.7
Unemployment rate | 4.3 | 3.5 | 2.8 | 2.7 | 2.8 | 3.2 | 4.4 | 2.7
House price growth | 3.4 | 3.7 | 6.5 | 6.6 | 5.4 | 5.1 | 28.2 | 0.4
Commercial real estate price growth | 0.7 | 7.8 | 6.7 | 3.2 | 0.5 | 3.7 | 20.0 | (0.8)
UK Bank Rate | 5.06 | 4.71 | 5.02 | 5.19 | 5.42 | 5.08 | 5.50 | 4.50
CPI inflation | 2.6 | 2.8 | 2.6 | 2.9 | 3.0 | 2.8 | 3.5 | 2.0
Base case |  |  |  |  |  |  |  |
Gross domestic product growth | 0.8 | 1.0 | 1.4 | 1.5 | 1.5 | 1.2 | 7.0 | 0.7
Unemployment rate | 4.3 | 4.7 | 4.7 | 4.5 | 4.5 | 4.5 | 4.8 | 4.2
House price growth | 3.4 | 2.1 | 1.0 | 1.4 | 2.4 | 2.0 | 10.5 | 0.4
Commercial real estate price growth | 0.7 | 0.3 | 2.5 | 1.9 | 0.0 | 1.1 | 5.4 | (0.8)
UK Bank Rate | 5.06 | 4.19 | 3.63 | 3.50 | 3.50 | 3.98 | 5.25 | 3.50
CPI inflation | 2.6 | 2.8 | 2.4 | 2.4 | 2.2 | 2.5 | 3.5 | 2.0
Downside |  |  |  |  |  |  |  |
Gross domestic product growth | 0.8 | (0.5) | (0.4) | 1.0 | 1.5 | 0.5 | 3.2 | 0.0
Unemployment rate | 4.3 | 6.0 | 7.4 | 7.4 | 7.1 | 6.4 | 7.5 | 4.2
House price growth | 3.4 | 0.6 | (5.5) | (6.6) | (3.4) | (2.4) | 4.0 | (11.4)
Commercial real estate price growth | 0.7 | (7.8) | (3.1) | (0.9) | (2.3) | (2.7) | 0.7 | (12.9)
UK Bank Rate | 5.06 | 3.53 | 1.56 | 0.96 | 0.68 | 2.36 | 5.25 | 0.59
CPI inflation | 2.6 | 2.8 | 2.3 | 1.8 | 1.2 | 2.1 | 3.5 | 0.9
Severe downside |  |  |  |  |  |  |  |
Gross domestic product growth | 0.8 | (1.9) | (1.5) | 0.7 | 1.3 | (0.1) | 1.2 | (2.4)
Unemployment rate | 4.3 | 7.7 | 10.0 | 10.0 | 9.7 | 8.4 | 10.2 | 4.2
House price growth | 3.4 | (0.8) | (12.4) | (13.6) | (8.8) | (6.7) | 3.4 | (29.2)
Commercial real estate price growth | 0.7 | (17.4) | (8.5) | (5.5) | (5.7) | (7.5) | 0.7 | (32.3)
UK Bank Rate – modelled | 5.06 | 2.68 | 0.28 | 0.08 | 0.02 | 1.62 | 5.25 | 0.02
UK Bank Rate – adjusted 1 | 5.06 | 4.03 | 2.70 | 2.23 | 1.95 | 3.19 | 5.25 | 1.88
CPI inflation – modelled | 2.6 | 2.8 | 1.9 | 1.0 | 0.1 | 1.7 | 3.5 | (0.2)
CPI inflation – adjusted 1 | 2.6 | 3.6 | 2.1 | 1.4 | 0.8 | 2.1 | 3.9 | 0.7
Probability-weighted |  |  |  |  |  |  |  |
Gross domestic product growth | 0.8 | 0.5 | 0.8 | 1.2 | 1.4 | 1.0 | 5.7 | 0.7
Unemployment rate | 4.3 | 5.0 | 5.5 | 5.4 | 5.3 | 5.1 | 5.5 | 4.2
House price growth | 3.4 | 1.8 | (0.7) | (1.0) | 0.4 | 0.8 | 5.3 | 0.4
Commercial real estate price growth | 0.7 | (1.7) | 1.0 | 0.7 | (1.1) | (0.1) | 0.7 | (1.3)
UK Bank Rate – modelled | 5.06 | 4.00 | 3.09 | 2.90 | 2.88 | 3.59 | 5.25 | 2.88
UK Bank Rate – adjusted 1 | 5.06 | 4.13 | 3.33 | 3.12 | 3.08 | 3.74 | 5.25 | 3.06
CPI inflation – modelled | 2.6 | 2.8 | 2.4 | 2.2 | 1.9 | 2.4 | 3.5 | 1.8
CPI inflation – adjusted 1 | 2.6 | 2.9 | 2.4 | 2.3 | 2.0 | 2.4 | 3.5 | 1.9
1 The adjustment to UK Bank Rate and CPI inflation in the severe downside was considered to better reflect the risks around the Group’s base case view in an economic environment where the risks of supply and demand shocks are more balanced.
Base case scenario by quarter 1 At 31 December 2024 | First quarter 2024 % | Second quarter 2024 % | Third quarter 2024 % | Fourth quarter 2024 % | First quarter 2025 % | Second quarter 2025 % | Third quarter 2025 % | Fourth quarter 2025 %
Gross domestic product growth | 0.7 | 0.4 | 0.0 | 0.1 | 0.2 | 0.3 | 0.3 | 0.3
Unemployment rate | 4.3 | 4.2 | 4.3 | 4.4 | 4.5 | 4.6 | 4.7 | 4.8
House price growth | 0.4 | 1.8 | 4.6 | 3.4 | 3.6 | 4.0 | 3.0 | 2.1
Commercial real estate price growth | (5.3) | (4.7) | (2.8) | 0.7 | 1.8 | 1.4 | 0.9 | 0.3
UK Bank Rate | 5.25 | 5.25 | 5.00 | 4.75 | 4.50 | 4.25 | 4.00 | 4.00
CPI inflation | 3.5 | 2.1 | 2.0 | 2.5 | 2.4 | 3.0 | 2.9 | 2.7
1 Gross domestic product growth is presented quarter-on-quarter. House price growth, commercial real estate growth and CPI inflation are presented year-on-year, i.e. from the equivalent quarter in the previous year. Unemployment rate and UK Bank Rate are presented as at the end of each quarter. Note 21: Allowance for expected credit losses continued ECL sensitivity to economic assumptions The following table shows the Group’s ECL for the probability-weighted, upside, base case, downside and severe downside scenarios. The stage allocation for an asset is based on the overall 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 on a statutory basis being £366 million compared to £445 million at 31 December 2024.
| At 31 December 2025 |  | At 31 December 2024
| 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 | 731 | 341 | 510 | 937 | 1,943 |  | 852 | 345 | 567 | 1,064 | 2,596
Credit cards | 603 | 498 | 579 | 674 | 777 |  | 674 | 518 | 641 | 773 | 945
Other Retail | 991 | 922 | 969 | 1,036 | 1,126 |  | 950 | 843 | 923 | 1,010 | 1,172
Commercial Banking | 888 | 690 | 789 | 1,010 | 1,414 |  | 989 | 745 | 889 | 1,125 | 1,608
Other | 15 | 15 | 15 | 15 | 15 |  | 16 | 16 | 16 | 16 | 17
ECL allowance | 3,228 | 2,466 | 2,862 | 3,672 | 5,275 |  | 3,481 | 2,467 | 3,036 | 3,988 | 6,338
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 impacts are assessed as changes to probability-weighted modelled ECL inclusive of the impacts upon staging of assets, excluding post model adjustments. In previous assessments, impacts were assessed as changes to base case modelled ECL only (at 100% weighting) with staging held flat to the reported view, and similarly excluded post model adjustments. The updated approach addresses the limitations of the prior methodology and provides a more representative view of the potential impact of these sensitivities. The ECL impact due to a change in unemployment has reduced in 2025 compared to 2024 as a result of lower loss rates within the Commercial Banking model. The HPI reduction versus 2024 is due to lower default rates and a reduced proportion of assets in Stage 2 for UK mortgages, following strong credit performance in the year. The table below shows the impact on the Group’s ECL resulting from a 1 percentage point increase or decrease in the UK unemployment rate. The increase or decrease is presented based on the adjustment phased evenly over the first 10 quarters of all four scenarios. A more immediate increase or decrease would drive a more material ECL impact as it would be fully reflected in both 12-month and lifetime probability of defaults.
| At 31 December 2025 |  | At 31 December 2024 1
| 1pp increase in unemployment £m | 1pp decrease in unemployment £m |  | 1pp increase in unemployment £m | 1pp decrease in unemployment £m
UK mortgages | 11 | (11) |  | 13 | (12)
Credit cards | 54 | (53) |  | 54 | (53)
Other Retail | 25 | (25) |  | 23 | (24)
Commercial Banking | 58 | (48) |  | 113 | (82)
ECL impact | 148 | (137) |  | 203 | (171)
1 For 2025, impacts are assessed as changes to probability-weighted modelled ECL inclusive of the impacts upon staging of assets, excluding post model adjustments. The comparative period has been represented on a consistent basis. The table below shows the impact on the Group’s ECL in respect of UK mortgages of an increase or decrease in loss given default for a 10 percentage point increase or decrease in HPI. The increase or decrease is presented based on the adjustment phased evenly over the first 10 quarters of all four scenarios.
| At 31 December 2025 |  | At 31 December 2024 1
| 10pp increase in HPI £m | 10pp decrease in HPI £m |  | 10pp increase in HPI £m | 10pp decrease in HPI £m
ECL impact | (172) | 261 |  | (207) | 312
1 For 2025, impacts are assessed as changes to probability-weighted modelled ECL inclusive of the impacts upon staging of assets, excluding post model adjustments. The comparative period has been represented on a consistent basis. Assessment of climate risk impacts on ECL 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. The approach leverages the Group’s climate scenario analysis, to identify the potential physical and transition risk impacts on credit quality. UK mortgages and Commercial Banking portfolios are judged to have the highest sensitivity to climate risk, with both physical and transition risk drivers assessed. UK mortgages physical and transition risks – additional costs arising from regulatory obligations of increased energy efficiency standards to reduce carbon emissions and increased flood risk and coastal erosion, through property repair or rebuild and/or increased insurance premia. This can result in affordability pressure, as well as decrease in property valuation, for borrowers owning low EPC rated properties or those in areas prone to flooding or coastal erosion. Note 21: Allowance for expected credit losses continued Commercial Banking physical and transition risks – increased costs or revenue disruption, or both, arising from chronic and acute physical hazards from rising temperatures. Companies adapting to a sudden transition scenario could potentially lead to increased transition costs in operations, direct carbon costs, and deteriorating financial performance due to changing consumer perspectives. Macroeconomic and sector scenario risk assessments Assessments were 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 (NGF S). The potential incremental impact of climate factors on key economic drivers was isolated from the Phase V NGFS Delayed Transition scenario, which management judged the most plausible. The incremental risk to ECL was then quantified by overlaying the specific climate impact of this scenario onto macroeconomic drivers within the Group’s base case and MES scenarios. The results from the most material Retail portfolios, UK mortgages and Credit cards allowed management to conclude on an immaterial ECL impact for Retail below £10 million (31 December 2024: below £5 million), and in Commercial Banking a separate climate assessment performed at sector level, resulted in an ECL impact of below £15 million (31 December 2024: below £15 million). The Group’s MES downside and severe downside scenarios, together comprising a 40% 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 used within the ECL calculation. In Commercial Banking, a top-down analysis using sectoral modelling was repeated to estimate the specific ECL impact of climate risk on commercial credit conditions. This assessment specifically targets agriculture, automotive, transport, oil and gas, real estate and utilities sectors where climate impacts were judged to be more significant. Resulting 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 Phase V scenarios with client level valuation impacts where available, alongside historic impairment data. The Phase V scenarios introduced a physical risk approach, requiring adjustments to ensure appropriate timing of impacts. Considering methodological limitations, the additional ECL required was shown to be immaterial. The Group recognises the ongoing uncertainty and limitations of climate scenario modelling, including external concerns reported in late 2025 for physical risk approaches. While NGFS scenarios continue to provide a consistent benchmark for assessing climate-related risks in ECL, they are used with prudent adjustments. Physical and transition risk assessments The Group has enhanced its assessment of transition risk on the UK mortgage portfolio. Scope has been extended from Probability of Default (PD) impacts only to also include Loss Given Default (LGD) considerations. The affordability stress resulting from home retrofitting costs associated with higher EPC regulatory rating requirements, under multiple scenarios was re-calculated. The provision impact was assessed by transforming the account level assessment of affordability and valuation impacts to adjust inputs used in existing PD and LGD parameters. As at 31 December 2025, the impact on ECL has been estimated to be less than £10 million (31 December 2024: less than £10 million) across buy-to-let (BTL), mainstream and legacy portfolios. The physical risk assessment on the UK mortgage portfolio in 2025 continued to include both flooding and coastal erosion risk. The impacts were based on an internally defined delayed transition outlook, out to 2050, aligned with the Group’s transition methodology. The assessment showed that over 80% of the book was not exposed to flood risk damage. Over 99% had no risk to coastal erosion damage. The impact on ECL to customers exposed to the affordability risk from flood and coastal erosion 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. Similarly the current assessment excludes the potential affordability shocks or reduced insurance coverage that could occur due to possible changes to insurance policy initiatives in this area.
Assessment | Nature of risk assessed | Portfolios assessed | ECL impact At 31 December 2025 | ECL impact At 31 December 2024
Macroeconomic impact from climate scenario | Scenario risk – macro level | Retail | < £10 million | < £5 million
Sector level impacts from climate scenario | Scenario risk – sector level | Commercial Banking (excluding Business Banking) | < £15 million | < £15 million
Retrofitting cost to meet EPC regulation | Transition risk | UK mortgages | < £10 million | < £10 million
Flood risk | Physical risk | UK mortgages | < £5 million | < £5 million
T he climate risk assessment s above remain limited due to the degree of uncertainty underpinning key assumptions used, as well as the continuing 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 for Commercial Banking; considering only the most material hazards for UK mortgages (flood and coastal erosion); client valuation impacts not incorporating climate transition plans; the physical risk modelling for corporates currently excluding broader components such as supply chain impacts, and more broadly the political landscape; future climate data enhancements and further model development. The ECL impacts resulting from these climate risk assessments remain immaterial. This continues to support management’s view that there is a low residual risk of material error or omission in the Group’s financial statements due to climate-related risks and as a result no adjustments have been made to ECL measured as at 31 December 2025. The current behavioural lives of the Group’s lending dilute the potential exposure to the later emergence of potential physical climate impacts, with the incorporation of climate risk, in credit policy, as a qualitative underwriting assessment within the Commercial Banking credit process and the origination process for mortgages providing further mitigation on more recent originations.

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