Lloyds Banking (LLOBF) Provision for Credit Losses (2016 - 2025)
Lloyds Banking (LLOBF) reported Provision for Credit Losses of $3.84 billion for the quarter ended Dec 31, 2025, up 29.4% from $2.97 billion a year earlier.
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Analysis
Lloyds Banking (LLOBF) Provision for Credit Losses (2016 - 2025) Analysis & Trends
Over the twelve months ended Dec 31, 2025, Lloyds Banking's Provision for Credit Losses came in at $11.5 billion, up 70.0% year-over-year; for the year ended Dec 31, 2023, it was $514.94 million, down 69.8% from the prior year.
- Provision for Credit Losses has a five-year compound annual growth rate of -17.7% (years ended Dec 2018 to Dec 2023).
- By year, Provision for Credit Losses came in at $1.71 billion in the year ended Dec 31, 2022, -$1.55 billion in the year ended Dec 31, 2021, $4.96 billion in the year ended Dec 31, 2020 (+187.4%) and $1.73 billion in the year ended Dec 31, 2019 (+26.3%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Provisions (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 896.53 Bn | 896.53 Bn | - | 2.74 Bn |
| 2 | Bank Of America | 354.20 Bn | -2,021.91 Bn | - | 1.24 Bn |
| 3 | Hsbc Holdings | 303.54 Bn | -1,800.05 Bn | - | - |
| 4 | Royal Bank Of Canada | 283.29 Bn | -546.75 Bn | - | 717.20 Mn |
| 5 | Morgan Stanley | 281.19 Bn | -262.84 Bn | - | 103.00 Mn |
| 6 | Goldman Sachs | 256.26 Bn | -3,487.19 Bn | - | 368.00 Mn |
| 7 | Wells Fargo & Company | 253.33 Bn | 253.33 Bn | - | 1.03 Bn |
| 8 | Mitsubishi Ufj Financial | 238.77 Bn | -102.62 Bn | 10.89 Bn | - |
| 9 | American Express | 216.03 Bn | 15.51 Bn | - | 985.00 Mn |
| 10 | Lloyds Banking | 111.85 Bn | -403.70 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2025 | 3.84 Bn |
| Dec 31, 2024 | 2.97 Bn |
| Dec 31, 2023 | 2.58 Bn |
| Dec 31, 2022 | 2.11 Bn |
| Jun 30, 2017 | -894.47 Mn |
| Mar 31, 2017 | -433.56 Mn |
| Sep 30, 2016 | -1.31 Bn |
API Access
Lloyds Banking Provision for Credit Losses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=provision-for-credit-losses&ticker=LLOBF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "provision-for-credit-losses", "ticker": "LLOBF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=provision-for-credit-losses&ticker=LLOBF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();