Report of the directors financial review risk report

6 Months Ended

Jun. 30, 2025

Report Of The Directors Financial Review Risk Report [Abstract]

Report Of The Directors Financial Review Risk Report

Summary of credit risk

The following disclosure presents the gross carrying/nominal amount of financial instruments to which the impairment requirements in IFRS 9

are applied and the associated allowance for ECL.

The following tables analyse loans by industry sector and represent the concentration of exposures on which credit risk is managed. The

allowance for ECL increased from $10.3bn at 31 December 2024 to $10.8bn at 30 June 2025.


Summary of financial instruments to which the impairment requirements in IFRS 9 are applied – by business segment
	Gross carrying/nominal amount						Allowance for ECL1
	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	233,677	301,611	307,233	149,110	234	991,865	(3,537)	(1,980)	(2,994)	(1,587)	(45)	(10,143)
Loans and advances to banks at amortised cost	12,145	6,779	67,285	18,386	3,002	107,597	(1)	(2)	(8)	(3)	(1)	(15)
Other financial assets measured at amortised cost	48,153	100,864	611,863	61,501	68,249	890,630	(23)	(23)	(50)	(25)	(1)	(122)
– cash and balances at central banks	6,228	52,987	167,701	18,745	699	246,360	—	—	—	—	—	—
– Hong Kong Government certificates of indebtedness	—	—	—	—	42,592	42,592	—	—	—	—	—	—
– reverse repurchase agreements – non- trading	4,020	19,322	253,279	5,518	1,065	283,204	—	—	—	—	—	—
– financial investments	33,016	25,836	64,104	27,829	15,438	166,223	(2)	(1)	(4)	(7)	—	(14)
– assets held for sale2	—	9	1,897	3,171	3	5,080	—	—	(5)	(6)	—	(11)
– other assets3	4,889	2,710	124,882	6,238	8,452	147,171	(21)	(22)	(41)	(12)	(1)	(97)
Total on-balance sheet	293,975	409,254	986,381	228,997	71,485	1,990,092	(3,561)	(2,005)	(3,052)	(1,615)	(47)	(10,280)
Loan and other credit- related commitments	111,631	106,862	356,822	116,165	225	691,705	(29)	(103)	(211)	(9)	—	(352)
Financial guarantees	647	1,098	13,180	1,680	—	16,605	(5)	(14)	(24)	(1)	—	(44)
Total off-balance sheet4	112,278	107,960	370,002	117,845	225	708,310	(34)	(117)	(235)	(10)	—	(396)
At 30 Jun 2025	406,253	517,214	1,356,383	346,842	71,710	2,698,402	(3,595)	(2,122)	(3,287)	(1,625)	(47)	(10,676)

	Fair value						Memorandum allowance for ECL5
	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
Debt instruments measured at FVOCI	138,366	31,888	159,488	58,149	8,017	395,908	(2)	(1)	(18)	(15)	(27)	(63)


Summary of financial instruments to which the impairment requirements in IFRS 9 are applied – by business segment (continued)
	Gross carrying/nominal amount						Allowance for ECL1
	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	238,416	269,141	287,842	137,789	7,185	940,373	(3,208)	(1,848)	(3,141)	(1,464)	(54)	(9,715)
Loans and advances to banks at amortised cost	13,034	7,505	63,524	15,713	2,276	102,052	(1)	(2)	(7)	(1)	(2)	(13)
Other financial assets measured at amortised cost	52,869	100,322	553,664	58,713	63,012	828,580	(25)	(9)	(39)	(19)	—	(92)
– cash and balances at central banks	5,565	63,981	177,095	20,260	773	267,674	—	—	—	—	—	—
– Hong Kong Government certificates of indebtedness	—	—	—	—	42,293	42,293	—	—	—	—	—	—
– reverse repurchase agreements – non- trading	2,896	13,188	229,672	5,844	949	252,549	—	—	—	—	—	—
– financial investments	40,345	20,072	56,537	25,059	11,969	153,982	(1)	(1)	(4)	(3)	—	(9)
– assets held for sale2	—	5	670	2,595	3	3,273	—	—	(4)	—	—	(4)
– other assets3	4,063	3,076	89,690	4,955	7,025	108,809	(24)	(8)	(31)	(16)	—	(79)
Total on-balance sheet	304,319	376,968	905,030	212,215	72,473	1,871,005	(3,234)	(1,859)	(3,187)	(1,484)	(56)	(9,820)
Loan and other credit- related commitments	109,369	90,848	307,197	111,762	191	619,367	(29)	(116)	(187)	(16)	—	(348)
Financial guarantees	1,171	939	13,186	1,702	—	16,998	(2)	(3)	(24)	—	—	(29)
Total off-balance sheet4	110,540	91,787	320,383	113,464	191	636,365	(31)	(119)	(211)	(16)	—	(377)
At 31 Dec 2024	414,859	468,755	1,225,413	325,679	72,664	2,507,370	(3,265)	(1,978)	(3,398)	(1,500)	(56)	(10,197)

	Fair value						Memorandum allowance for ECL5
	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total	Hong Kong	UK	CIB	IWPB	Corporate Centre	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
Debt instruments measured at FVOCI	128,568	26,405	137,538	51,516	2,097	346,124	(1)	(1)	(18)	(14)	(20)	(54)

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

case the ECL is recognised as a provision.

2 At 30 June 2025, the gross carrying amount comprised $2.3bn of loans and advances to customers and banks (31 December 2024: $1.1bn) and $2.8bn of other

financial assets at amortised cost (31 December 2024: $2.1bn) including the planned sales of our private banking and custody businesses in Germany ($3.7bn,

31 December 2024: $2.2bn), as well as our business in South Africa ($0.8bn, 31 December 2024: $0.4bn). The corresponding allowance for ECL comprised

$11m of loans and advances to customers and banks (31 December 2024: $4m) and $0.2m of other financial assets at amortised cost (31 December 2024:

$0.3m).

3Includes only those financial instruments that are subject to the impairment requirements of IFRS 9. ‘Other assets’ as presented within the summary

consolidated balance sheet on page 23 comprises both financial and non-financial assets, including cash collateral and settlement accounts.

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

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

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


Summary of credit risk (excluding debt instruments measured at FVOCI) by stage distribution and ECL coverage by industry sector
	Gross carrying/nominal amount1					Allowance for ECL					ECL coverage %
	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total	Stage 1	Stage 2	Stage 3	POCI2	Total
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%	%
Loans and advances to customers at amortised cost	852,669	115,338	23,550	308	991,865	(1,181)	(2,752)	(6,144)	(66)	(10,143)	0.1	2.4	26.1	21.4	1.0
– personal	421,134	43,900	3,921	—	468,955	(618)	(1,228)	(894)	—	(2,740)	0.1	2.8	22.8	—	0.6
– corporate and commercial	344,579	68,592	18,982	115	432,268	(502)	(1,487)	(5,084)	(66)	(7,139)	0.1	2.2	26.8	57.4	1.7
– non-bank financial institutions	86,956	2,846	647	193	90,642	(61)	(37)	(166)	—	(264)	0.1	1.3	25.7	—	0.3
Loans and advances to banks at amortised cost	107,428	166	3	—	107,597	(10)	(2)	(3)	—	(15)	—	1.2	100.0	—	—
Other financial assets measured at amortised cost	888,423	2,011	196	—	890,630	(74)	(17)	(31)	—	(122)	—	0.8	15.8	—	—
Loans and other credit-related commitments	668,179	22,482	1,040	4	691,705	(143)	(119)	(89)	(1)	(352)	—	0.5	8.6	25.0	0.1
– personal	263,998	1,978	122	—	266,098	(21)	(3)	(1)	—	(25)	—	0.2	0.8	—	—
– corporate and commercial	242,163	19,116	828	4	262,111	(111)	(113)	(87)	(1)	(312)	—	0.6	10.5	25.0	0.1
– financial	162,018	1,388	90	—	163,496	(11)	(3)	(1)	—	(15)	—	0.2	1.1	—	—
Financial guarantees	14,506	1,780	319	—	16,605	(10)	(8)	(26)	—	(44)	0.1	0.4	8.2	—	0.3
– personal	1,463	20	—	—	1,483	(1)	—	—	—	(1)	0.1	—	—	—	0.1
– corporate and commercial	9,128	1,639	271	—	11,038	(8)	(8)	(26)	—	(42)	0.1	0.5	9.6	—	0.4
– financial	3,915	121	48	—	4,084	(1)	—	—	—	(1)	—	—	—	—	—
At 30 Jun 20253	2,531,205	141,777	25,108	312	2,698,402	(1,418)	(2,898)	(6,293)	(67)	(10,676)	0.1	2.0	25.1	21.5	0.4

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

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

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

3The shift of ‘gross carrying amount’ between stage 1 and 2 arose mainly in Asia from higher average PD for the remaining term at the reporting date, reflecting updates to our PD models and ongoing market challenges. PDs at the reporting

date were compared with the PD calculated at origination.

Unless identified at an earlier stage, all financial assets are deemed to

have suffered a significant increase in credit risk when they are

30 days past due (‘DPD’) and are transferred from stage 1 to stage 2.

The following disclosure presents the ageing of stage 2 financial

assets by those less than 30 and greater than 30 DPD and therefore

presents those financial assets classified as stage 2 due to ageing

(30 DPD) and those identified at an earlier stage (less than 30 DPD).


Stage 2 days past due analysis
	Gross carrying amount				Allowance for ECL				ECL coverage %
	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD1	30 and > DPD1	Stage 2	Up-to- date	1 to 29 DPD	30 and > DPD
At 30 Jun 2025	$m	$m	$m	$m	$m	$m	$m	$m	%	%	%	%
Loans and advances to customers at amortised cost	115,338	112,022	2,027	1,289	(2,752)	(2,305)	(254)	(193)	2.4	2.1	12.5	15.0
– personal	43,900	41,722	1,346	832	(1,228)	(825)	(234)	(169)	2.8	2.0	17.4	20.3
– corporate and commercial	68,592	67,572	681	339	(1,487)	(1,451)	(20)	(16)	2.2	2.1	2.9	4.7
– non-bank financial institutions	2,846	2,728	—	118	(37)	(29)	—	(8)	1.3	1.1	—	6.8
Loans and advances to banks at amortised cost	166	166	—	—	(2)	(2)	—	—	1.2	1.2	—	—
Other financial assets measured at amortised cost	2,011	1,999	5	7	(17)	(16)	—	(1)	0.8	0.8	—	14.3

At 31 Dec 2024
Loans and advances to customers at amortised cost	93,248	90,157	1,888	1,203	(2,546)	(2,147)	(192)	(207)	2.7	2.4	10.2	17.2
– personal	39,919	37,676	1,361	882	(1,158)	(799)	(169)	(190)	2.9	2.1	12.4	21.5
– corporate and commercial	51,231	50,486	506	239	(1,358)	(1,326)	(21)	(11)	2.7	2.6	4.2	4.6
– non-bank financial institutions	2,098	1,995	21	82	(30)	(22)	(2)	(6)	1.4	1.1	9.5	7.3
Loans and advances to banks at amortised cost	198	198	—	—	(2)	(2)	—	—	1.0	1.0	—	—
Other financial assets measured at amortised cost	1,806	1,794	3	9	(5)	(5)	—	—	0.3	0.3	—	—

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

Measurement uncertainty and sensitivity analysis of ECL estimates

The recognition and measurement of ECL involves the use of

significant judgement and estimation. We form multiple scenarios

based on economic forecasts and distributional estimates and apply

these to credit risk models to estimate future credit losses. The

results are then probability-weighted to determine an unbiased ECL

estimate.

Management assessed the current economic environment, reviewed

the latest economic forecasts and discussed key risks before

selecting the economic scenarios and their weightings.

Management judgemental adjustments are used where modelled

allowance for ECL does not fully reflect the identified risks and

related uncertainty, or to capture significant late-breaking eventsMethodology

At 30 June 2025, four scenarios were used to capture the latest

economic expectations and to articulate management’s view of the

range of risks and potential outcomes. Scenarios are updated with

the latest economic forecasts and distributional estimates in each

quarter.

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

external consensus forecasts, market data and distributional

estimates of the entire range of economic outcomes. Consensus

estimates are deployed as conditioning variables in a proprietary

expansion of the scenario variables. The fourth scenario, the

Downside 2, represents management’s view of severe downside

risks.

The consensus Central scenario is deemed the ‘most likely’ scenario,

and usually attracts the largest probability weighting. The consensus

outer scenarios represent short-term cyclical deviations from the

Central scenario, where variable paths converge back to long-term

trend expectations. They are calibrated to a 10% probability.

The Downside 2 scenario is narrative-driven and explores a more

extreme economic outcome than those captured by the consensus

scenarios. In this scenario variables do not, by design, revert to long-

term trend expectations and may instead explore alternative states of

equilibrium, where economic variables move permanently away from

past trends. It is calibrated to a 5% probability.

This weighting scheme is deemed appropriate for the unbiased

estimation of ECL in most circumstances. However, management

may depart from this probability-based scenario weighting approach

when the economic outlook and forecasts are determined to be

particularly uncertain and risks are elevated.

Management assessed that risk and uncertainty around the Central

scenario projection remained elevated in the second quarter of 2025

and scenario weights were adjusted. Weight was reassigned from

the Central scenario to the consensus Downside scenario.

In the second quarter of 2025, outer scenarios for most markets have

been configured as demand shocks. To the downside, the

crystallisation of economic risks causes consumption and investment

to fall sharply and commodity prices to decline. Inflation is lower

relative to the Central scenario in most markets, although that

narrative is disrupted in the US and Mexico by the assumption of

higher tariff rates and a broad increase in import prices. Mexico is

affected in a similar way to the US on the supply side, given the

significance of its trade with the US and the assumption that

countries react to US tariffs with countermeasures. In the upside

scenario, robust economic growth drives investment and

consumption higher, causing a temporary acceleration of inflation.

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

emerging risks.

Description of economic scenarios

The economic assumptions presented in this section are formed by

HSBC with reference to external forecasts and estimates for the

purpose of calculating ECL.

Forecasts may change and remain subject to uncertainty. Outer

scenarios are designed to capture potential crystallisation of key

economic and financial risks and alternative paths for economic

variables.

The scenarios used to calculate ECL are described below.

The consensus Central scenario

HSBC’s Central scenario incorporates an expectation of slower global

growth across many of our key markets in 2025-2026, relative to the

fourth quarter of 2024. The deterioration reflects the anticipated

effect of greater policy uncertainty and higher US tariff rates on trade,

investment and employment. The scenario is consistent with the

tariff rate, measured as an effective trade-weighted average, of

13.7% in 2025 and 8.6% in 2026.

The notable exceptions are mainland China and Hong Kong, where

forecasts have improved. Recent data in these markets has

suggested that while tariffs and subdued consumer confidence will

continue to be headwinds in the months ahead, official support for

the respective economies is expected to ensure that the downturn is

less pronounced than previously expected, amid strong fiscal support

and increasingly supportive monetary conditions.

In the US and UK, household and business confidence has weakened

amid high policy uncertainty and restrictive interest rates. In Europe,

manufacturing remains in a protracted downturn, and trade policy

uncertainty is also weighing on sentiment. Planned increases in fiscal

spending to support tax cuts, welfare spending and defence are

expected to deliver only incremental additional growth, spread out

over several years.

Global GDP is expected to grow by 2.3% in 2025 in the Central

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

2.5% over the entire forecast period.

The key features of our Central scenario are:

–GDP growth rates in most of our main markets are expected to slow

in 2025 compared with 2024, with only moderate recovery expected

in 2026. The exception is the UAE.

–Consistent with weaker expected growth, unemployment is forecast

to rise moderately in 2025, but remain low by historical standards.

–The expected evolution of inflation is more mixed by market. In the

US and the UK, it is set to remain above target through 2025 and

2026. In the US, the impact of tariffs on import prices is expected to

keep prices higher, whereas in the UK changes to utility prices and

employer taxes and wage costs are seen as the main driver of

higher inflation. In Hong Kong and mainland China, price inflation is

likely to remain subdued amid weak domestic demand and

continued strong manufacturing growth in mainland China.

–Housing market conditions also remain mixed, with prices forecast

to continue to fall in Hong Kong and mainland China in the near term

due to an excess of unsold inventory. Stronger growth is expected in

the UAE and Mexico, but price gains are expected to remain more

muted in the UK, US and France.

–Challenging conditions are also forecast to continue in certain

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

markets. Structural changes to demand in the office segment in

particular are driving lower valuations.

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

in 2025 and 2026. In the longer term, they are expected to remain at

a higher level than in the pre-pandemic period.

–The Brent crude oil price is forecast to average around $65 per barrel

over the forecast period.

The Central scenario was created from consensus forecasts available in

May, and reviewed continually until the end of June 2025.

The following table describes key macroeconomic variables in the consensus Central scenario.


Consensus Central scenario
	3Q25-2Q30 (as at 2Q25)							2025–2029 (as at 4Q24)
	UK	US	Hong Kong	Mainland China	France	UAE	Mexico	UK	US	Hong Kong	Mainland China	France	UAE	Mexico
GDP (annual average growth rate, %)
2025	0.9	1.5	1.8	4.3	0.5	4.2	0.2	1.2	2.0	1.7	4.0	0.9	4.4	0.9
2026	1.2	1.6	2.1	4.1	1.0	4.2	1.4	1.3	1.6	1.8	3.7	0.9	4.2	1.2
2027	1.5	2.0	2.4	4.0	1.3	4.0	2.0	1.8	1.6	3.5	4.3	1.4	3.9	1.7
2028	1.5	2.0	2.4	3.9	1.3	3.5	2.0	1.6	1.8	3.1	3.9	1.5	3.6	1.9
2029	1.5	1.9	2.4	3.8	1.2	3.4	2.0	1.6	2.0	2.7	3.7	1.4	3.6	2.0
5-year average1	1.4	1.8	2.2	3.9	1.1	3.7	1.7	1.5	1.8	2.6	3.9	1.2	3.9	1.5
Unemployment rate (%)
2025	4.6	4.4	3.2	5.2	7.6	2.6	3.1	4.9	4.4	3.3	5.2	7.5	2.7	3.5
2026	4.7	4.5	3.1	5.1	7.7	2.5	3.8	4.7	4.3	3.7	5.4	7.3	2.6	3.5
2027	4.5	4.3	3.1	5.1	7.5	2.5	3.4	4.5	4.3	3.3	5.2	7.2	2.6	3.5
2028	4.3	4.3	3.0	5.0	7.4	2.4	3.5	4.3	4.2	3.0	5.0	7.0	2.5	3.5
2029	4.1	4.1	3.0	5.0	7.2	2.4	3.4	4.3	4.1	2.9	5.0	7.0	2.5	3.5
5-year average1	4.4	4.3	3.1	5.1	7.5	2.4	3.5	4.5	4.2	3.2	5.2	7.2	2.6	3.5
House prices (annual average growth rate, %)
2025	3.5	3.7	(5.3)	(5.9)	2.1	13.5	7.1	1.4	4.4	(0.5)	(5.9)	2.1	9.3	7.6
2026	1.2	3.1	(1.2)	(1.5)	4.3	5.5	4.2	3.8	3.2	2.4	(0.7)	4.4	5.1	4.5
2027	2.4	3.0	4.2	0.6	4.9	3.6	4.3	4.6	2.4	3.0	3.2	4.4	3.6	4.2
2028	3.3	2.6	3.0	2.7	4.1	2.3	4.4	3.5	2.5	2.7	4.1	3.8	1.8	4.0
2029	2.7	2.4	2.6	2.9	3.3	1.8	4.1	2.7	2.6	2.7	2.9	3.1	1.3	4.0
5-year average1	2.4	2.8	1.6	0.7	3.9	3.9	4.4	3.2	3.0	2.1	0.7	3.6	4.2	4.9
Inflation (annual average growth rate, %)
2025	3.0	3.1	1.7	0.3	1.3	1.9	3.7	2.4	2.4	1.4	0.3	1.2	2.1	5.0
2026	2.3	2.8	1.8	0.9	1.6	2.0	3.6	2.1	2.8	1.9	1.0	1.6	1.9	3.9
2027	2.0	2.4	2.0	1.4	1.9	1.9	3.5	2.1	2.5	2.2	1.5	2.0	1.8	3.4
2028	2.1	2.3	2.0	1.6	2.3	1.9	3.5	2.0	2.2	2.2	1.7	2.3	1.9	3.4
2029	2.0	2.2	2.1	1.5	2.2	1.9	3.4	2.0	2.1	2.3	1.6	2.2	1.8	3.4
5-year average1	2.2	2.5	1.9	1.3	1.9	1.9	3.5	2.1	2.4	2.0	1.2	1.9	1.9	3.8
Central bank policy rate (annual average, %)2
2025	4.2	4.2	4.6	3.0	2.1	4.3	8.5	4.2	4.1	4.5	2.9	2.1	4.1	9.4
2026	3.7	3.5	3.9	2.8	1.6	3.5	7.4	3.9	3.7	4.1	2.9	1.8	3.8	8.8
2027	3.7	3.4	3.8	2.9	1.9	3.4	7.6	3.8	3.7	4.0	3.0	2.0	3.7	8.8
2028	3.8	3.5	3.9	2.9	2.2	3.6	7.9	3.7	3.6	4.0	3.2	2.0	3.6	8.9
2029	3.9	3.7	4.1	3.0	2.4	3.7	8.2	3.7	3.6	4.0	3.3	2.1	3.6	8.9
5-year average1	3.8	3.6	4.0	2.9	2.1	3.7	7.8	3.9	3.7	4.1	3.1	2.0	3.8	8.9

1The five-year average is calculated over the 20 quarter projection. For the 2Q25 scenario this is from 3Q25 to 2Q30. For the 4Q24 scenario it is from 1Q25 to 4Q29.

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

The graphs compare the respective Central scenario with current economic expectations beginning in the second quarter of 2025.

GDP growth: Comparison of Central scenarios

Hong Kong

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

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

Mainland China

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

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

The consensus Upside scenario

Compared to the Central scenario, the consensus Upside scenario

features stronger economic activity in the near term, before

converging to long-run trend expectations. It also incorporates lower

unemployment and higher asset prices than incorporated in the

Central scenario.

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

These include a rollback of tariff measures, deregulation, a de-

escalation in geopolitical tensions as the Russia-Ukraine war moves

quickly towards a conclusion and the conflict in the Middle East

subsides, and an improvement in the US-China relationship.

The following table describes key macroeconomic variables in the consensus Upside scenario.


Consensus Upside scenario (3Q25–2Q30)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-peak)1	11.0	(2Q30)	14.9	(2Q30)	19.1	(2Q30)	28.5	(2Q30)	8.4	(2Q30)	28.9	(2Q30)	16.4	(2Q30)
Unemployment rate (%, min)2	3.0	(1Q27)	3.6	(2Q27)	2.7	(2Q27)	4.6	(2Q27)	6.6	(2Q27)	2.0	(2Q27)	3.0	(3Q25)
House price index (%, start-to-peak)1	18.2	(2Q30)	24.7	(2Q30)	19.8	(2Q30)	9.4	(2Q30)	23.3	(2Q30)	24.2	(2Q30)	29.0	(2Q30)
Inflation rate (YoY % change, max)3	3.3	(4Q25)	3.6	(4Q25)	2.5	(4Q26)	2.2	(1Q26)	2.3	(4Q27)	2.5	(4Q25)	4.2	(1Q26)
Central bank policy rate (%, max)3	4.3	(3Q25)	4.4	(3Q25)	4.7	(3Q25)	3.3	(1Q26)	2.5	(2Q30)	4.4	(3Q25)	8.5	(2Q30)


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

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

2Lowest projected unemployment in the scenario.

3Highest/lowest projected policy rate and year-on-year percentage change in inflation in the scenario.Downside scenarios

Downside scenarios explore the intensification and crystallisation of a

number of key economic and financial risks. The scenarios are

modelled so that economic shocks drive consumption and investment

lower and commodity prices fall. The nature of the shock varies with

the evolution of the risk profile of each country.

For most markets, inflation and interest rates are lower in the

downside scenarios compared with the Central scenario. The notable

exceptions are the US and Mexico, where tariffs and

countermeasures are assumed to cause a temporary increase in

inflation above the Central scenario. Interest rates are also assumed

to rise to a higher level, before the effects of weaker consumption

demand begin to dominate.

Key downside risks include:

–an increase in protectionist policies, as countries that impose

tariffs are met with countermeasures. This lowers investment,

complicates international supply chains and reduces trade flows;

–broader and more prolonged conflict in the Middle East and the

Russia-Ukraine war, which undermine confidence and investment;

and

–continued differences between the US and China, which affects

economic confidence, and the global goods trade and supply

chains for critical technologies.

The consensus Downside scenario

In the consensus Downside scenario, economic activity is weaker

compared with the Central scenario and the impact of tariffs on the

global economy is worse than expected. The scenario is consistent

with the tariff rate, measured as an effective trade-weighted average,

rising to 27.6% in 2025, and remaining at that level in 2026.

In the scenario, GDP declines, rates of unemployment rise and asset

prices fall. The scenario features an increase in tariffs over and above

those assumed in the Central scenario and an escalation of

geopolitical tensions. In most markets, inflation declines relative to

the Central scenario, as tariffs are assumed to drive a drop in US

import demand. In the US and Mexico inflation is assumed to

increase as higher tariffs across a broad range of imported goods pass

through to prices. Rising unemployment and falling commodity prices

are also calibrated so that they weigh on activity.

The following table describes key macroeconomic variables in the consensus Downside scenario.


Consensus Downside scenario (3Q25–2Q30)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(0.9)	(3Q27)	(1.5)	(2Q26)	(4.2)	(1Q26)	(2.9)	(4Q25)	(0.6)	(1Q26)	(0.2)	(3Q25)	(1.4)	(4Q26)
Unemployment rate (%, max)2	6.2	(3Q26)	5.6	(1Q26)	4.5	(1Q27)	6.7	(2Q27)	8.8	(1Q26)	3.4	(2Q26)	4.2	(3Q26)
House price index (%, start-to-trough)1	(6.4)	(4Q26)	(0.7)	(2Q26)	(6.9)	(1Q26)	(10.0)	(1Q27)	0.2	(3Q25)	(1.0)	(3Q25)	0.7	(3Q25)
Inflation rate (YoY % change)3	1.3	(2Q26)	4.0	(4Q25)	0.9	(2Q26)	(2.8)	(2Q26)	0.6	(2Q26)	0.8	(2Q26)	4.3	(4Q25)
Central bank policy rate (%)3	2.4	(1Q28)	5.2	(4Q25)	5.6	(4Q25)	1.7	(1Q26)	0.4	(1Q26)	5.2	(4Q25)	10.2	(4Q25)


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

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

2The highest projected unemployment in the scenario.

3Due to the calibration of inflation and interest rates in 2Q, the table shows highest year-on-year percentage change in inflation and projected policy rates for the

US and Mexico, and lowest for other countries. For the UAE and Hong Kong, the policy rate is also shown as the maximum, consistent with the operation of US

dollar-linked exchange rates. For mainland China, the policy rate shown is the Loan Prime rate.

Downside 2 scenario

The Downside 2 scenario features a deep global recession and

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

The narrative incorporates the crystallisation of a number of risks

simultaneously, including significant increases in tariffs and a further

escalation of geopolitical crises globally. The scenario is consistent

with the tariff rate, measured as an effective trade-weighted average,

rising to 31.6% in 2025, and remaining at that level in 2026. In this

scenario, confidence and asset prices fall sharply. The subsequent

drop in demand leads to a steep fall in commodity prices, and a rapid

increase in unemployment.

The following table describes key macroeconomic variables in the Downside 2 scenario.


Downside 2 scenario (3Q25–2Q30)
	UK		US		Hong Kong		Mainland China		France		UAE		Mexico
GDP level (%, start-to-trough)1	(5.5)	(4Q26)	(4.2)	(3Q26)	(10.8)	(1Q27)	(6.3)	(3Q26)	(6.3)	(4Q26)	(5.2)	(4Q26)	(9.3)	(4Q26)
Unemployment rate (%, max)2	8.7	(4Q26)	8.7	(4Q26)	6.7	(2Q26)	6.9	(2Q27)	10.8	(2Q27)	4.0	(1Q26)	5.8	(4Q26)
House price index (%, start-to-trough)1	(26.8)	(2Q27)	(14.3)	(2Q26)	(22.1)	(2Q29)	(27.7)	(3Q27)	(6.8)	(4Q26)	(24.4)	(3Q27)	0.7	(3Q25)
Inflation rate (YoY % change)3	(1.9)	(2Q26)	4.3	(4Q25)	(1.4)	(4Q26)	(6.0)	(2Q26)	(0.4)	(3Q26)	0.7	(2Q26)	4.4	(4Q25)
Central bank policy rate (%)3	1.6	(3Q26)	5.3	(4Q25)	5.6	(4Q25)	1.4	(4Q26)	(0.1)	(2Q26)	5.3	(4Q25)	10.6	(4Q25)


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

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

2The highest projected unemployment in the scenario.

3 Due to the calibration of inflation and interest rates in 2Q, the table shows highest year-on-year percentage change in inflation and projected policy rates for the

US and Mexico, but lowest for other countries. For the UAE and Hong Kong, the policy rate is also shown as the maximum, consistent with the operation of US

dollar-linked exchange rates. For mainland China, the policy rate shown is the Loan Prime rate.

Scenario weightings

Scenario weightings are calibrated to probabilities that are determined

with reference to consensus forecast probability distributions.

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

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

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

scenarios and the probability distribution, takes into consideration the

relationship of the consensus scenario for both internal and external

assessments of risk.

In the second quarter of 2025, key considerations around uncertainty

attached to the Central scenario projections focused on:

–US import tariffs and bilateral tariff escalation globally. Discussion

noted the impact on trade and manufacturing supply chains and the

uncertainty attached to tariff rate assumptions;

–the outlook for real estate in our key markets, particularly in the US,

UK, Hong Kong and mainland China;

–some reduction in estimation and forecast uncertainty for UK

unemployment given ongoing methodology updates at the Office for

National Statistics; and

–geopolitical risks, including those arising from the conflict in the Middle

East and the Russia-Ukraine war.

For the second quarter of 2025, scenario weights were adjusted to the

downside to reflect greater risk and uncertainty around the Central

scenario projection. Management assessed that the change was

appropriate given elevated market measures of volatility and policy

uncertainty.

As a consequence, the consensus Central scenario for all key markets

was assigned a weight of 65%, down from 75% at 31 December 2024.

The weight assigned to the consensus Upside scenario was left

unchanged at 10%. The remaining 25% was assigned to the two

Downside scenarios. The consensus Downside scenario received a

weight of 20%, up from 10% at 31 December 2024. The weight assigned

to the Downside 2 scenario was left unchanged at 5%.

In light of the Israel-Iran conflict in the Middle East during June 2025,

management monitored developments and assessed potential

implications. Given the limited lasting consequences for global markets,

including oil, and the swift subsequent de-escalation, no additional action

was deemed necessary for economic scenarios or weights.

The following table describes the probabilities assigned in each scenario.


Scenario weightings, %
	Standard weights	UK	US	Hong Kong	Mainland China	France	UAE	Mexico
2Q25
Upside	10	10	10	10	10	10	10	10
Central	75	65	65	65	65	65	65	65
Downside	10	20	20	20	20	20	20	20
Downside 2	5	5	5	5	5	5	5	5

4Q24
Upside	10	10	10	10	10	10	10	10
Central	75	75	75	75	75	75	75	75
Downside	10	10	10	10	10	10	10	10
Downside 2	5	5	5	5	5	5	5	5

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

Hong Kong

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

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

Mainland China

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

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

Critical estimates and judgements

The calculation of ECL under IFRS 9 involved significant judgements,

assumptions and estimates at 30 June 2025. These included:

–the selection and configuration of economic scenarios, given the

constant change in economic conditions and distribution of

economic risks; and

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

similar observable historical conditions cannot be captured by the

credit risk modelsHow economic scenarios are reflected in ECL

calculations

The methodologies for the application of forward economic guidance

into the calculation of ECL for wholesale and retail portfolios are set

out on page 155 of the Annual Report and Accounts 2024. Models are

used to reflect economic scenarios in ECL estimates. These models

are based largely on historical observations and correlations with

default.

Economic forecasts and ECL model responses to these forecasts are

subject to a degree of uncertainty. The models continue to be

supplemented by management judgemental adjustments where

required.

Management judgemental adjustments

The management judgemental adjustments in relation to ECL allowance are detailed on page 155 of the Annual Report and Accounts 2024.


Management judgemental adjustments to ECL1
	At 30 Jun 2025			At 31 Dec 2024
	Retail	Wholesale2	Total	Retail	Wholesale2	Total
	$bn	$bn	$bn	$bn	$bn	$bn
Modelled ECL (A)3	2.7	1.9	4.6	2.6	2.0	4.6
Banks, sovereigns, government entities and low-risk counterparties		0.0	0.0		0.0	0.0
Corporate lending adjustments		0.2	0.2		0.1	0.1
Other credit judgements	0.1	—	0.1	0.0		0.0
Total management judgemental adjustments (B)4	0.1	0.2	0.3	0.0	0.1	0.1
Other adjustments (C)5	0.1	0.3	0.4	(0.0)	0.1	0.1
Final ECL (A + B + C)6	2.8	2.4	5.2	2.6	2.2	4.8

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

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

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

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

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

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

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

30 June 2025 a qualitative industry sector framework adjustment increased the Wholesale portfolio allowance for ECL by $0.1bn.

6As presented within our internal credit risk governance (see page 139 of the Annual Report and Accounts 2024).

In the wholesale portfolio, management judgemental adjustments

were an increase to modelled allowance for ECL of $0.2bn

(31 December 2024: $0.1bn increase), mostly to reflect heightened

uncertainty in specific sectors and geographies, including real estate

sector adjustments as a result of ongoing market challenges.

Compared with 31 December 2024, management judgemental

adjustments increased by $0.1bn at 30 June 2025.

In the retail portfolio, management judgemental adjustments were an

increase to modelled allowance for ECL of $0.1bn at 30 June 2025

(31 December 2024: $0.0bn).Management judgemental adjustments

in relation to other credit judgements increased allowance for ECL by

$0.1bn (31 December 2024: $0.0bn). Adjustments relate to market-

specific uncertainties across a number of geographies.

Economic scenarios sensitivity analysis of

ECL estimates

The economic scenarios sensitivity analysis of ECL estimates is

detailed on page 156 of the Annual Report and Accounts 2024.

Wholesale and retail sensitivity

The wholesale and retail sensitivity tables present the 100%-

weighted results for each of the four scenarios. These exclude

portfolios held by the insurance business, private banking and small

portfolios, and as such cannot be directly compared with personal and

wholesale lending presented in other credit risk tables. In both the

wholesale and retail analysis, the comparative period results for

Downside 2 scenarios are also not directly comparable with the

current period, because they reflect different risks relative to the

consensus scenarios for the period end.

The wholesale and retail sensitivity analysis is stated inclusive of

management judgemental adjustments, as appropriate to each

scenario.

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

financial instruments is the same under each scenario. For exposures

with similar risk profile and product characteristics, the sensitivity

impact is therefore largely the result of changes in macroeconomic

assumptions.

Wholesale analysis

At 30 June 2025, the highest level of 100% scenario-weighted ECL

was observed in the UK and Hong Kong. This higher ECL impact was

largely driven by significant exposure in these regions. In the

wholesale portfolio, off-balance sheet financial instruments have a

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

point of default, and consequently the ECL sensitivity impact is lower

in relation to its nominal amount when compared with an on-balance

sheet exposure with similar risk profile.

Compared with 31 December 2024, the Downside 2 ECL impact

decreased by $1.4bn, mostly in the UK due to new PD models. These

models include a recent calibration of credit risk experience under a

higher interest rate environment, and result in a reduction of

sensitivity to severe stress under similar conditions.


Wholesale IFRS 9 ECL sensitivity to future economic conditions1,2,3
By geography at 30 Jun 20255	Reported Gross carrying amount4	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL
By geography at 30 Jun 20255	$m	$m	$m	$m	$m	$m
UK	439,863	618	579	521	732	1,082
US	199,656	215	191	169	298	515
Hong Kong	467,487	814	758	607	966	1,524
Mainland China	134,762	236	190	121	387	681
Mexico	35,806	91	82	65	110	273
UAE	60,542	59	57	49	65	101
France	191,111	128	118	102	143	190
Other geographies6	478,479	262	227	172	390	767
Total	2,007,707	2,423	2,202	1,808	3,091	5,133
of which:
Stage 1	1,838,904	707	665	536	837	915
Stage 2	168,803	1,685	1,537	1,272	2,254	4,218


By geography at 31 Dec 20245
UK	432,160	717	667	526	850	2,389
US	202,888	216	201	205	247	461
Hong Kong	450,966	659	616	465	906	1,496
Mainland China	137,960	178	141	84	329	886
Mexico	34,713	69	61	46	86	302
UAE	58,909	51	49	40	58	120
France	184,591	82	80	69	97	125
Other geographies6	455,823	234	216	176	304	774
Total	1,958,010	2,205	2,031	1,612	2,877	6,555
of which:
Stage 1	1,830,264	689	632	494	797	803
Stage 2	127,746	1,516	1,399	1,118	2,080	5,751

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

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

3Excludes defaulted obligors. For a detailed breakdown of performing and non-performing wholesale portfolio exposures, see page 60.

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

stage 2 under the Downside 2 scenario.

5Geographies include all legal entities which share a common set of macroeconomic scenarios for the majority of exposures.

6Includes small portfolios that use less complex modelling approaches and are not sensitive to macroeconomic changes.

Retail analysis

At 30 June 2025, the most significant level of allowance for ECL

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

Mortgages reflected the lowest level of allowance for ECL sensitivity

across most markets given the significant levels of collateral relative

to the exposure values. Credit cards and other unsecured lending

across stages 1 and 2 are more sensitive to economic forecasts and

therefore reflected the highest level of allowance for ECL sensitivity

during the first half of 2025.

Compared with 31 December 2024, the Downside 2 ECL decreased

by $0.4bn, primarily in Hong Kong credit cards and other unsecured

lending due to the reducing severity of house price forecasts.


Retail IFRS 9 ECL sensitivity to future economic conditions1
	At 30 Jun 2025						At 31 Dec 2024
By geography	Reported gross carrying amount	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL	Reported gross carrying amount	Reported allowance for ECL	Consensus Central scenario allowance for ECL	Consensus Upside scenario allowance for ECL	Consensus Downside scenario allowance for ECL	Downside 2 scenario allowance for ECL
By geography	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
UK
Mortgages	181,192	150	138	130	158	293	163,541	126	117	107	132	288
Credit cards	7,990	339	336	317	338	414	7,415	280	275	265	276	447
Other	9,404	267	263	238	275	346	8,249	241	233	217	243	351
Mexico
Mortgages	8,187	187	183	175	190	237	7,482	165	162	155	168	215
Credit cards	2,294	384	379	374	385	479	2,227	337	333	330	338	423
Other	3,821	430	426	422	431	593	3,722	419	416	413	422	593
Hong Kong
Mortgages	105,399	7	6	5	8	12	106,866	5	5	4	5	10
Credit cards	9,097	289	257	253	301	496	9,419	293	275	268	300	770
Other	6,194	110	108	107	112	137	6,210	106	102	101	105	249
UAE
Mortgages	2,097	7	7	7	7	7	1,993	8	8	8	8	8
Credit cards	545	34	33	32	34	39	536	31	31	31	31	35
Other	658	18	17	17	18	20	688	17	17	17	17	19
US
Mortgages	17,736	7	7	7	8	10	16,965	6	6	6	6	8
Credit cards	188	14	14	13	14	16	193	15	14	14	15	17
Other geographies
Mortgages	54,323	123	117	112	131	177	51,064	131	127	124	136	180
Credit cards	3,665	170	169	167	173	198	3,500	162	159	156	164	223
Other	2,488	78	77	74	78	92	2,292	72	72	69	73	93
Total	415,278	2,613	2,539	2,452	2,662	3,567	392,361	2,413	2,351	2,285	2,440	3,928
of which: mortgages	368,934	481	459	436	502	736	347,910	440	425	405	456	708
Stage 1	328,914	55	49	46	63	119	311,875	51	47	43	58	129
Stage 2	37,499	144	133	120	149	287	33,761	126	117	107	129	275
Stage 3	2,521	282	278	269	290	330	2,274	263	261	255	269	304
of which: credit cards	23,779	1,229	1,188	1,157	1,246	1,642	23,290	1,116	1,086	1,064	1,124	1,915
Stage 1	19,784	320	313	299	331	513	19,915	276	267	258	284	701
Stage 2	3,708	695	660	643	700	907	3,107	655	634	621	656	1,027
Stage 3	287	215	215	215	215	223	267	185	185	185	185	188
of which: others	22,565	902	891	859	915	1,189	21,161	856	839	816	860	1,305
Stage 1	19,717	224	218	204	232	415	18,574	216	204	193	217	532
Stage 2	2,285	385	381	363	391	473	2,005	360	355	343	363	483
Stage 3	563	293	293	293	293	301	583	279	279	279	279	290

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

The ECL impact of the scenarios and management judgemental

adjustments are highly sensitive to movements in economic

forecasts. Based upon the sensitivity tables presented above, if the

Group ECL balance (excluding wholesale stage 3, which is assessed

individually) was estimated solely on the basis of the Central scenario,

Upside scenario, Downside 1 scenario or the Downside 2 scenario at

30 June 2025, it would increase/(decrease) as presented in the below

table.


	Retail1	Wholesale1
Total Group ECL at 30 Jun 2025	$bn	$bn
Reported ECL	2.6	2.4
Scenarios
100% consensus Central scenario	(0.1)	(0.1)
100% consensus Upside scenario	(0.2)	(0.5)
100% consensus Downside scenario	0.0	0.8
100% Downside 2 scenario	1.0	2.9


Total Group ECL at 31 Dec 2024
Reported ECL	2.4	2.2
Scenarios
100% consensus Central scenario	(0.1)	(0.2)
100% consensus Upside scenario	(0.1)	(0.6)
100% consensus Downside scenario	0.0	0.7
100% Downside 2 scenario	1.5	4.3

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

At 30 June 2025, the Group reported ECL allowance increased by

$0.2bn in both the retail and wholesale portfolios, compared with

31 December 2024.

The Downside 2 ECL allowance decreased for both the retail and

wholesale portfolios. In the wholesale portfolio this was mainly due to

new PD models, and in the retail portfolio this was due to the reduced

severity of house price forecasts in Hong Kong.

Reconciliation of changes in gross

carrying/nominal amount and

allowances for loans and advances to

banks and customers

The following disclosure provides a reconciliation by stage of the

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

advances to banks and customers, including loan commitments and

financial guarantees. Movements are calculated on a quarterly basis

and therefore fully capture stage movements between quarters. If

movements were calculated on a year-to-date basis they would only

reflect the opening and closing position of the financial instrument.

The transfers of financial instruments represent the impact of stage

transfers upon the gross carrying/nominal amount and associated

allowance for ECL.

The net remeasurement of ECL arising from stage transfers

represents the increase or decrease due to these transfers, for

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

ECL measurement basis. Net remeasurement excludes the

underlying customer risk rating (‘CRR’)/PD movements of the financial

instruments transferring stage. This is captured, along with other

credit quality movements in the ‘changes in risk parameters – credit

quality’ line item.

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

impact from volume movements within the Group’s lending portfolio

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

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

parameters – further lending/repayment’.


Reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees

	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2025	1,489,687	(1,232)	115,898	(2,674)	23,823	(6,148)	93	(51)	1,629,501	(10,105)
Transfers of financial instruments:	(44,123)	(459)	39,727	936	4,396	(477)	—	—	—	—
– transfers from stage 1 to stage 2	(82,621)	205	82,621	(205)	—	—	—	—	—	—
– transfers from stage 2 to stage 1	39,013	(639)	(39,013)	639	—	—	—	—	—	—
– transfers to stage 3	(693)	4	(4,617)	609	5,310	(613)	—	—	—	—
– transfers from stage 3	178	(29)	736	(107)	(914)	136	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	360	—	(341)	—	(19)	—	—	—	—
Changes due to modifications not derecognised	—	—	—	—	(7)	—	—	—	(7)	—
Net new and further lending/ repayments	44,603	(59)	(22,112)	317	(2,225)	680	213	(8)	20,479	930
Changes to risk parameters – credit quality	—	186	—	(1,227)	—	(1,998)	—	(5)	—	(3,044)
Changes to models used for ECL calculation	—	(72)	—	250	—	(15)	—	—	—	163
Assets written off	—	—	—	—	(2,029)	2,029	—	—	(2,029)	2,029
Credit-related modifications that resulted in derecognition	—	—	—	—	(88)	9	—	—	(88)	9
Foreign exchange and others1,2	57,658	(68)	6,253	(142)	1,042	(323)	6	(3)	64,959	(536)
At 30 Jun 2025	1,547,825	(1,344)	139,766	(2,881)	24,912	(6,262)	312	(67)	1,712,815	(10,554)
ECL income statement change for the period		415		(1,001)		(1,352)		(13)		(1,951)
Recoveries										136
Others										(141)
Total ECL income statement change for the period										(1,956)


Reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees (continued)
	At 30 Jun 2025		6 months ended 30 Jun 2025
	Gross carrying/ nominal amount	Allowance for ECL	ECL release/ (charge)
	$m	$m	$m
As above	1,712,815	(10,554)	(1,956)
Other financial assets measured at amortised cost	890,630	(122)	(31)
Non-trading reverse purchase agreement commitments	94,957	—	—
Performance and other guarantees not considered for IFRS 9	—	—	49
Summary of financial instruments to which the impairment requirements in IFRS 9 are applied – by business segment/Summary consolidated income statement	2,698,402	(10,676)	(1,938)
Debt instruments measured at FVOCI	395,908	(63)	(3)
Total allowance for ECL/total income statement ECL change for the period	N/A	(10,739)	(1,941)

1Total includes $1.3bn of gross carrying loans and advances to customers and banks, which were classified to assets held for sale, and corresponding allowance

for ECL of $6m, reflecting planned business disposals as disclosed in Note 15 on page 98.

2This includes $7.2bn of gross carrying loans and advances to customers and corresponding allowance for ECL of $7m in relation to the retained portfolio of home

and other loans associated with the sale of our retail banking operations in France, which were classified to assets held for sale in 2Q25, reflecting the planned

disposal as disclosed in Note 15 on page 98.

he allowance for ECL for loans and advances to customers and banks and relevant loan commitments and financial guarantees increased by $449m

from $10,105m at 31 December 2024, to $10,554m at 30 June 2025. This increase was driven by:

–$3,044m relating to underlying credit quality changes, including the

credit quality impact of financial instruments transferring between

stages; and

–foreign exchange and other movements of $536m.

These were partly offset by:

–$2,029m of assets written off, of which $1,227m in relation to

wholesale lending and $802m in relation to personal lending;

–$930m relating to volume movements, which included the ECL

allowance associated with new originations, assets derecognised and

further pending repayment;

–$163m relating to changes to models used for ECL calculation; and

–$9m relating to the credit-related modifications that resulted in

derecognition.

The ECL charge for the period of $1,951m presented in the previous table

consisted of $3,044m relating to underlying credit quality changes,

including the credit quality impact of financial instruments transferring

between stages. These were partly offset by $930m relating to underlying

net book volume, as well as $163m relating to changes to models used

for ECL calculation, which reflected updates to our PD models.


Reconciliation of changes in gross carrying/nominal amount and allowances for loans and advances to banks and customers including loan commitments and financial guarantees (continued)
	Non-credit impaired				Credit impaired
	Stage 1		Stage 2		Stage 3		POCI		Total
	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL	Gross carrying/ nominal amount	Allowance for ECL
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
At 1 Jan 2024	1,496,805	(1,300)	153,084	(3,102)	20,799	(7,063)	85	(30)	1,670,773	(11,495)
Transfers of financial instruments:	(19,629)	(1,259)	6,652	2,302	12,977	(1,043)	—	—	—	—
– transfers from stage 1 to stage 2	(116,211)	419	116,211	(419)	—	—	—	—	—	—
– transfers from stage 2 to stage 1	98,731	(1,627)	(98,731)	1,627	—	—	—	—	—	—
– transfers to stage 3	(2,799)	16	(12,230)	1,321	15,029	(1,337)	—	—	—	—
– transfers from stage 3	650	(67)	1,402	(227)	(2,052)	294	—	—	—	—
Net remeasurement of ECL arising from transfer of stage	—	959	—	(831)	—	(144)	—	—	—	(16)
Changes due to modifications not derecognised	—	—	—	—	(25)	—	—	—	(25)	—
Net new and further lending/repayments	87,833	(168)	(37,731)	589	(5,246)	1,689	7	(7)	44,863	2,103
Changes to risk parameters – credit quality	—	363	—	(1,773)	—	(3,945)	—	(11)	—	(5,366)
Changes to models used for ECL calculation	—	68	—	(4)	—	(20)	—	—	—	44
Assets written off	—	—	—	—	(4,459)	4,459	—	—	(4,459)	4,459
Credit-related modifications that resulted in derecognition	—	—	—	—	—	—	—	—	—	—
Foreign exchange and others1,2,3,4	(75,322)	105	(6,107)	145	(223)	(81)	1	(3)	(81,651)	166
At 31 Dec 2024	1,489,687	(1,232)	115,898	(2,674)	23,823	(6,148)	93	(51)	1,629,501	(10,105)
ECL income statement change for the period		1,222		(2,019)		(2,420)		(18)		(3,235)
Recoveries										260
Other	—	—	—	—	—	—	—	—	—	(158)
Total ECL income statement change for the period2										(3,133)


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

1Total includes $3.7bn of gross carrying loans and advances, which were classified from assets held for sale, and a corresponding allowance for ECL of $46m,

reflecting planned business disposals as disclosed in Note 15 on page 98.

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

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

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

Argentina during 2024.

4The 31 December 2024 total ECL income statement change of $3,133m is attributable to $882m for the six months ended 30 June 2024 and $2,251m to the six

months ended 31 December 2024.

Credit quality of financial instruments

We assess the credit quality of all financial instruments that are

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

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

determined based on relative deterioration of credit quality since initial

recognition. Accordingly, for non-credit-impaired financial instruments,

there is no direct relationship between the credit quality assessment

and stages 1 and 2, though typically the lower credit quality bands

exhibit a higher proportion in stage 2.

The five credit quality classifications each encompass a range of

granular internal credit rating grades assigned to wholesale and

personal lending businesses and the external ratings attributed by

external agencies to debt securities, as shown in the following table.

Personal lending credit quality is disclosed based on a 12-month point-

in-time PD adjusted for multiple economic scenarios. The credit

quality classifications for wholesale lending are based on internal

credit risk ratings.


Distribution of financial instruments to which the impairment requirements in IFRS 9 are applied, by credit quality and stage allocation
	At 30 Jun 2025								At 31 Dec 2024
	Gross carrying/nominal amount						Allowance for ECL	Net	Gross carrying/nominal amount						Allowance for ECL	Net
	Strong	Good	Satisfactory	Sub- standard	Credit impaired	Total	Allowance for ECL	Net	Strong	Good	Satisfactory	Sub- standard	Credit impaired	Total	Allowance for ECL	Net
	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m	$m
Loans and advances to customers at amortised cost	531,379	210,722	201,620	24,479	23,665	991,865	(10,143)	981,722	515,266	193,080	186,416	22,906	22,705	940,373	(9,715)	930,658
– stage 1	510,598	180,542	155,546	5,983	—	852,669	(1,181)	851,488	498,415	170,420	150,818	4,767	—	824,420	(1,078)	823,342
– stage 2	20,781	30,180	45,881	18,496	—	115,338	(2,752)	112,586	16,851	22,660	35,598	18,139	—	93,248	(2,546)	90,702
– stage 3	—	—	—	—	23,550	23,550	(6,144)	17,406	—	—	—	—	22,615	22,615	(6,040)	16,575
– POCI	—	—	193	—	115	308	(66)	242	—	—	—	—	90	90	(51)	39
Loans and advances to banks at amortised cost	95,955	5,377	6,111	151	3	107,597	(15)	107,582	92,621	4,255	5,040	134	2	102,052	(13)	102,039
– stage 1	95,880	5,340	6,076	132	—	107,428	(10)	107,418	92,528	4,226	4,981	117	—	101,852	(9)	101,843
– stage 2	75	37	35	19	—	166	(2)	164	93	29	59	17	—	198	(2)	196
– stage 3	—	—	—	—	3	3	(3)	—	—	—	—	—	2	2	(2)	—
– POCI	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Other financial assets measured at amortised cost	755,386	86,905	47,766	377	196	890,630	(122)	890,508	702,570	85,700	39,660	497	153	828,580	(92)	828,488
– stage 1	755,052	86,039	47,083	249	—	888,423	(74)	888,349	702,373	85,032	38,977	239	—	826,621	(64)	826,557
– stage 2	334	866	683	128	—	2,011	(17)	1,994	197	668	683	258	—	1,806	(5)	1,801
– stage 3	—	—	—	—	196	196	(31)	165	—	—	—	—	153	153	(23)	130
– POCI	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Loans and other credit- related commitments	441,769	150,302	88,854	9,736	1,044	691,705	(352)	691,353	400,120	131,396	77,220	9,670	961	619,367	(348)	619,019
– stage 1	439,548	144,242	78,922	5,467	—	668,179	(143)	668,036	398,779	125,956	67,949	4,547	—	597,231	(137)	597,094
– stage 2	2,221	6,060	9,932	4,269	—	22,482	(119)	22,363	1,341	5,440	9,271	5,123	—	21,175	(121)	21,054
– stage 3	—	—	—	—	1,040	1,040	(89)	951	—	—	—	—	958	958	(90)	868
– POCI	—	—	—	—	4	4	(1)	3	—	—	—	—	3	3	—	3
Financial guarantees	7,265	4,353	4,117	551	319	16,605	(44)	16,561	7,365	4,263	4,399	723	248	16,998	(29)	16,969
– stage 1	7,130	3,942	3,304	130	—	14,506	(10)	14,496	7,352	4,192	3,625	184	—	15,353	(8)	15,345
– stage 2	135	411	813	421	—	1,780	(8)	1,772	13	71	774	539	—	1,397	(5)	1,392
– stage 3	—	—	—	—	319	319	(26)	293	—	—	—	—	248	248	(16)	232
– POCI	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Total	1,831,754	457,659	348,468	35,294	25,227	2,698,402	(10,676)	2,687,726	1,717,942	418,694	312,735	33,930	24,069	2,507,370	(10,197)	2,497,173
Debt instruments at FVOCI1
– stage 1	376,703	11,973	8,141	4,580	—	401,397	(37)	401,360	336,264	9,448	7,290	—	—	353,002	(31)	352,971
– stage 2	59	68	489	506	—	1,122	(21)	1,101	49	—	478	380	—	907	(23)	884
– stage 3	—	—	—	—	31	31	(5)	26	—	—	—	—	—	—	—	—
– POCI	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
Total	376,762	12,041	8,630	5,086	31	402,550	(63)	402,487	336,313	9,448	7,768	380	—	353,909	(54)	353,855

1For the purposes of this disclosure, gross carrying value is defined as the amortised cost of a financial asset, before adjusting for any loss allowance. As such, the gross carrying value of debt instruments at FVOCI will not reconcile to the

balance sheet as it excludes fair value gains and losses.


Non-trading VaR, 99% 10 day
	Interest rate	Credit spread	Portfolio diversification1	Total
	$m	$m	$m	$m
Half-year to 30 Jun 2025	446.6	217.5	(118.8)	545.3
Average	455.4	207.1	(126.7)	535.8
Maximum	575.3	240.0		617.5
Minimum	378.9	181.3		458.0

Half-year to 30 Jun 2024	682.4	333.2	(224.1)	791.5
Average	740.5	337.2	(241.4)	836.3
Maximum	1,000.6	369.1		1,097.6
Minimum	474.2	324.3		572.2

Half year to 31 Dec 2024	528.4	246.1	(220.7)	553.8
Average	466.9	292.9	(204.5)	555.3
Maximum	691.3	342.4		799.5
Minimum	292.1	242.4		408.7

1When VaR is calculated at a portfolio level, natural offsets in risk can occur when compared with aggregating VaR at the asset class level. This difference is called

portfolio diversification. The asset class VaR maxima and minima reported in the table occurred on different dates within the reporting period. For this reason, we

do not report an implied portfolio diversification measure between the maximum (minimum) asset class VaR measures and the maximum (minimum) total VaR

measures in this table.


Trading VaR, 99% 1 day
	Foreign exchange and commodity	Interest rate	Equity	Credit spread	Portfolio diversification1	Total
	$m	$m	$m	$m	$m	$m
Half-year to 30 Jun 2025	11.2	20.5	18.2	13.1	(28.3)	34.6
Average	14.7	31.4	15.6	11.3	(34.3)	38.8
Maximum	26.9	54.9	20.9	17.9		57.1
Minimum	7.0	18.7	12.3	6.4		27.3

Half-year to 30 Jun 2024	20.6	47.5	15.7	9.9	(41.1)	52.7
Average	15.4	57.1	14.0	10.2	(37.1)	59.7
Maximum	29.8	78.1	17.6	12.7		83.3
Minimum	6.9	42.0	12.7	6.6		45.7

Half-year to 31 Dec 2024	14.6	34.9	16.3	8.2	(35.7)	38.3
Average	15.0	39.7	15.5	9.7	(33.2)	46.7
Maximum	27.2	59.3	20.5	13.1		63.2
Minimum	8.6	24.8	13.6	6.9		37.0

1Asset class VaR reported in the table above is calculated by using a 500-day historical window. Total VaR, which is utilised for internal risk management and for

regulatory capital, is the maximum of VaR calculated by using a 250-day historical window and VaR calculated by using a 500-day historical window. When VaR is

calculated at a portfolio level, natural offsets in risk can occur when compared with aggregating VaR at the asset class level. This difference is called portfolio

diversification. The asset class VaR maxima and minima reported in the table occurred on different dates within the reporting period. For this reason, we do not

report an implied portfolio diversification measure between the maximum (minimum) asset class VaR measures and the maximum (minimum) total VaR

measures in this table.


Balance sheet of insurance manufacturing subsidiaries by type of contract
	Life direct participating and investment DPF contracts	Life other1	Other contracts2	Shareholder assets and liabilities	Total
	$m	$m	$m	$m	$m
Financial assets	107,933	5,069	6,652	6,596	126,250
– financial assets designated and otherwise mandatorily measured at fair value through profit or loss	103,127	4,757	5,330	1,100	114,314
– derivatives	169	11	2	1	183
– financial investments – at amortised cost	537	80	1,012	4,279	5,908
– financial assets at fair value through other comprehensive income	—	—	4	67	71
– other financial assets	4,100	221	304	1,149	5,774
Insurance contract assets	15	159	—	—	174
Reinsurance contract assets	—	6,334	—	—	6,334
Other assets and investment properties3	27,985	63	38	4,148	32,234
Total assets at 30 Jun 2025	135,933	11,625	6,690	10,744	164,992
Liabilities under investment contracts designated at fair value	—	—	6,332	—	6,332
Insurance contract liabilities	112,618	4,831	—	—	117,449
Reinsurance contract liabilities	—	691	—	—	691
Deferred tax	—	—	—	12	12
Other liabilities	24,883	44	—	7,862	32,789
Total liabilities	137,501	5,566	6,332	7,874	157,273
Total equity	—	—	—	7,719	7,719
Total liabilities and equity at 30 Jun 2025	137,501	5,566	6,332	15,593	164,992

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

1‘Life other’ mainly includes protection insurance contracts as well as reinsurance contracts. The reinsurance contracts primarily provide diversification benefits

over the life participating and investment discretionary participation feature (‘DPF‘) contracts.

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

3At 30 June 2025 ’Other assets and investment properties’ includes $27,860m (31 December 2024: $24,222m) and ’Other liabilities’ includes $26,858m

(31 December 2024: $23,420m) in respect of the classification of the French life insurance business assets and liabilities as held for sale. Further details are

provided on page 98.