XML 23 R13.htm IDEA: XBRL DOCUMENT
v3.23.3

Reserves for Credit Losses | 9 Months Ended
--- | ---
Sep. 30, 2023
Receivables [Abstract] |
Reserve for Credit Losses | Reserves for Credit Losses Reserves for credit losses represent our best estimate of the expected credit losses in our outstanding portfolio of Card Member loans and receivables as of the balance sheet date. The CECL methodology requires us to estimate lifetime expected credit losses by incorporating historical loss experience, as well as current and future economic conditions over a reasonable and supportable period (R&S Period), which is approximately three years, beyond the balance sheet date. We make various judgments combined with historical loss experience to determine a reserve rate that is applied to the outstanding loan or receivable balance to produce a reserve for expected credit losses. We use a combination of statistically-based models that incorporate current and future economic conditions throughout the R&S Period. The process of estimating expected credit losses is based on several key models: Probability of Default (PD), Exposure at Default (EAD), and future recoveries for each month of the R&S Period. Beyond the R&S Period, we estimate expected credit losses by immediately reverting to long-term average loss rates. •PD models are used to estimate the likelihood an account will be written-off. •EAD models are used to estimate the balance of an account at the time of write-off. This includes balances less expected repayments based on historical payment and revolve behavior, which vary by customer. Due to the nature of revolving loan portfolios, the EAD models are complex and involve assumptions regarding the relationship between future spend and payment behaviors. •Recovery models are used to estimate amounts that are expected to be received from Card Members after default occurs, typically as a result of collection efforts. Future recoveries are estimated taking into consideration the time of default, time elapsed since default and macroeconomic conditions. We also estimate the likelihood and magnitude of recovery of previously written off accounts considering how long ago the account was written off and future economic conditions, even if such expected recoveries exceed expected losses. Our models are developed using historical loss experience covering the economic cycle and consider the impact of account characteristics on expected losses. This history includes the performance of loans and receivables modifications for borrowers experiencing financial difficulty, including their subsequent defaults. Future economic conditions that are incorporated over the R&S Period include multiple macroeconomic scenarios provided to us by an independent third party. Management reviews these economic scenarios each period and assigns probability weights to each scenario, generally with a consistent initial distribution. At times, due to macroeconomic uncertainty and volatility, management may apply judgment and assign different probability weights to scenarios. These macroeconomic scenarios contain certain variables, including unemployment rates and real gross domestic product (GDP), that are significant to our models. We also evaluate whether to include qualitative reserves to cover losses that are expected but, in our assessment, may not be adequately represented in the quantitative methods or the economic assumptions. We consider whether to adjust the quantitative reserves (higher or lower) to address possible limitations within the models or factors not included within the models, such as external conditions, emerging portfolio trends, the nature and size of the portfolio, portfolio concentrations, the volume and severity of past due accounts, or management risk actions. Lifetime losses for most of our loans and receivables are evaluated at an appropriate level of granularity, including assessment on a pooled basis where financial assets share similar risk characteristics, such as past spend and remittance behaviors, credit bureau scores where available, delinquency status, tenure of balance outstanding, amongst others. Credit losses on accrued interest are measured and presented as part of Reserves for credit losses on the Consolidated Balance Sheets and within the Provisions for credit losses in the Consolidated Statements of Income, rather than reversing interest income. Separate models are used for accounts deemed a troubled debt restructuring, which are measured individually and incorporate a discounted cash flow model. Loans and receivable balances are written off when we consider amounts to be uncollectible, which is generally determined by the number of days past due and is typically no later than 180 days past due for pay in full or revolving loans and 120 days past due for term loans. Loans and receivables in bankruptcy or owed by deceased individuals are generally written off upon notification. The following table reflects the range of macroeconomic scenario key variables used, in conjunction with other inputs, to calculate reserves for credit losses:
|  | U.S. Unemployment Rate |  | U.S. GDP Growth (Contraction) (a)
|  | September 30, 2023 |  | December 31, 2022 |  | September 30, 2023 |  | December 31, 2022
Third quarter of 2023 |  | 4% |  | 3% - 7% |  | 2% |  | 5% - (2)%
Fourth quarter of 2023 |  | 3% - 6% |  | 3% - 8% |  | 4% - (3)% |  | 6% - 0.2%
Fourth quarter of 2024 |  | 3% - 8% |  | 3% - 7% |  | 2% - 1% |  | 3% - 2%
Fourth quarter of 2025 |  | 4% - 7% |  | 3% - 6% |  | 4% - 2% |  | 4% - 3%
(a)Real GDP quarter over quarter percentage change seasonally adjusted to annualized rates. Changes in Card Member Loans Reserve for Credit Losses Card Member loans reserve for credit losses increased for both the three and nine months ended September 30, 2023, primarily driven by increases in loans outstanding and higher delinquencies. Card Member loans reserve for credit losses increased for the three months ended September 30, 2022, primarily driven by an increase in loans outstanding and deterioration in the macroeconomic outlook at that time. Card Member loans reserve for credit losses increased for the nine months ended September 30, 2022, primarily driven by an increase in loans outstanding and deterioration in the macroeconomic outlook at that time, partially offset by a reduction in COVID-19 pandemic-driven reserves. The following table presents changes in the Card Member loans reserve for credit losses for the three and nine months ended September 30:
|  | Three Months Ended September 30, |  | Nine Months Ended September 30,
(Millions) |  | 2023 |  | 2022 |  | 2023 |  | 2022
Beginning Balance |  | $ | 4,390 |  |  | $ | 2,997 |  |  | $ | 3,747 |  |  | $ | 3,305 |
Provisions (a) |  | 982 |  |  | 596 |  |  | 2,691 |  |  | 757 |
Net write-offs (b) |  |  |  |  |  |  |  |
Principal |  | (525) |  |  | (203) |  |  | (1,412) |  |  | (560) |
Interest and fees |  | (114) |  |  | (56) |  |  | (310) |  |  | (161) |
Other (c) |  | (12) |  |  | (15) |  |  | 5 |  |  | (22) |
Ending Balance |  | $ | 4,721 |  |  | $ | 3,319 |  |  | $ | 4,721 |  |  | $ | 3,319 |
(a)Provisions for principal, interest and fee reserve components. Provisions for credit losses includes reserve build (release) and replenishment for net write-offs. (b)Principal write-offs are presented less recoveries of $138 million and $133 million for the three months ended September 30, 2023 and 2022, respectively, and $396 million and $415 million for the nine months ended September 30, 2023 and 2022, respectively. Recoveries of interest and fees were not significant. (c)Primarily includes foreign currency translation adjustments of $(13) million and $(16) million for the three months ended September 30, 2023 and 2022, respectively, and $5 million and $(22) million for the nine months ended September 30, 2023 and 2022, respectively. Changes in Card Member Receivables Reserve for Credit Losses Card Member receivables reserve for credit losses decreased for both the three and nine months ended September 30, 2023, primarily driven by lower delinquencies. Card Member receivables reserve for credit losses increased for the three months ended September 30, 2022, primarily driven by higher delinquencies. Card Member receivables reserve for credit losses increased for the nine months ended September 30, 2022, primarily driven by an increase in receivables outstanding and higher delinquencies. The following table presents changes in the Card Member receivables reserve for credit losses for the three and nine months ended September 30:
|  | Three Months Ended September 30, |  | Nine Months Ended September 30,
(Millions) |  | 2023 |  | 2022 |  | 2023 |  | 2022
Beginning Balance |  | $ | 210 |  |  | $ | 119 |  |  | $ | 229 |  |  | $ | 64 |
Provisions (a) |  | 206 |  |  | 165 |  |  | 658 |  |  | 383 |
Net write-offs (b) |  | (241) |  |  | (122) |  |  | (714) |  |  | (284) |
Other (c) |  | (1) |  |  | (3) |  |  | 1 |  |  | (4) |
Ending Balance |  | $ | 174 |  |  | $ | 159 |  |  | $ | 174 |  |  | $ | 159 |
(a)Provisions for principal and fee reserve components. Provisions for credit losses includes reserve build (release) and replenishment for net write-offs. (b)Net write-offs are presented less recoveries of $73 million and $60 million for the three months ended September 30, 2023 and 2022, respectively, and $218 million and $195 million for the nine months ended September 30, 2023 and 2022, respectively. (c)Primarily includes foreign currency translation adjustments.

X
- Definition The entire disclosure for allowance for credit losses. + References Reference 1: http://fasb.org/us-gaap/role/ref/legacyRef -Name Accounting Standards Codification -Topic 310 -Publisher FASB -URI https://asc.fasb.org//310/tableOfContent + Details
Name: | us-gaap_AllowanceForCreditLossesTextBlock
Namespace Prefix: | us-gaap_
Data Type: | dtr-types:textBlockItemType
Balance Type: | na
Period Type: | duration

X
- References No definition available. + Details
Name: | us-gaap_ReceivablesAbstract
Namespace Prefix: | us-gaap_
Data Type: | xbrli:stringItemType
Balance Type: | na
Period Type: | duration