CECL and the Credit Cycle

Loudis, Bert; Ranish, Benjamin

doi:10.17016/feds.2019.061

Cited by 3 publications

(2 citation statements)

References 34 publications

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“…and 40% for segments of revolver accounts. Consistent with existing research (Covas and Nelson, 2018;Loudis and Ranish, 2019), our analysis implies that the larger the forecast error, the larger the level of provision expenses that will have to be allocated during downturn economic conditions rather than prior to the downturn.…”

Section: Discussionsupporting

confidence: 85%

“…The analysis until this point has relied on the convenient assumption of perfect foresight to focus our attention on the important topic of the impact of payment allocation assumptions on CECL allowances. However, several studies in the growing CECL quantification literature put special emphasis on the potential sensitivity of CECL projections to macroeconomic forecast error (Chae et al, 2018;Covas and Nelson, 2018;DeRitis and Zandi, 2018;Loudis and Ranish, 2019). In this subsection, we directly address the topic of the sensitivity of CECL loss projections to macroeconomic forecast error of the kind experienced during the last recession.…”

Section: Assessing the Potential Impact Of Macroeconomic Forecast Errormentioning

confidence: 99%

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From Incurred Loss to Current Expected Credit Loss (CECL): A Forensic Analysis of the Allowance for Loan Losses in Unconditionally Cancelable Credit Card Portfolios

Canals-Cerdá

2020

Working Paper (Federal Reserve Bank of Philadelphia)

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The Current Expected Credit Loss (CECL) framework represents a new approach for calculating the allowance for credit losses. Credit cards are the most common form of revolving consumer credit and are likely to present conceptual and modeling challenges during CECL implementation. We look back at nine years of account-level credit card data, starting with 2008, over a time period encompassing the bulk of the Great Recession as well as several years of economic recovery. We analyze the performance of the CECL framework under plausible assumptions about allocations of future payments to existing credit card loans, a key implementation element. Our analysis focuses on three major themes: defaults, balances, and credit loss. Our analysis indicates that allowances are significantly impacted by specific payment allocation assumptions as well as downturn economic conditions. We also compare projected allowances with realized credit losses and observe a significant divergence resulting from the revolving nature of credit card portfolios. We extend our analysis across segments of the portfolio with different risk profiles. Interestingly, less risky segments of the portfolio are proportionally more impacted by specific payment assumptions and downturn economic conditions. We also analyze the impact of macroeconomic forecast error and find that it can be substantial and can be impacted by CECL implementation design features. Overall, our findings suggest that the effect of the new allowance framework on a specific credit card portfolio will depend critically on its risk profile. Thus, our findings should be interpreted qualitatively, rather than quantitatively. Finally, the goal is to gain a better understanding of the sensitivity of allowances to plausible variations in assumptions about the allocation of future payments to present credit card loans. Thus, we do not offer specific best practice guidance.

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Section: Discussionsupporting

confidence: 85%

Section: Assessing the Potential Impact Of Macroeconomic Forecast Errormentioning

confidence: 99%

From Incurred Loss to Current Expected Credit Loss (CECL): A Forensic Analysis of the Allowance for Loan Losses in Unconditionally Cancelable Credit Card Portfolios

Canals-Cerdá

2020

Working Paper (Federal Reserve Bank of Philadelphia)

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The Procyclicality of Impairment Accounting: Comparing Expected Losses Under IFRS 9 and US GAAP

2023

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Are Incurred Loss Standards Countercyclical? A Case Study Using U.S. Bank Holding Company Data

Hancock

Hafften

2022

JRFM

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After the 2008 global financial crisis, U.S. bank holding companies needing to cover larger-than-expected loan losses raised concerns that existing provision accounting may be procyclical. Most related studies have found evidence of procyclicality using either aggregate time-series data or “as-reported” panel data. We test the null hypothesis that provisions were a constant fraction of nonperforming loans across the economic cycle. We create a “forced” panel, which incorporates the entities acquired by each holding company in the quarters prior to their mergers. As in the related literature, we fail to reject the null hypothesis with “as-reported” data; however, we reject the null hypothesis with the “forced” panel. This finding suggests that holding companies built up provisions to some degree during the pre-crisis period to cover larger future losses. These actions reduced capital and likely depressed lending in the pre-crisis period; such countercyclical impacts are consistent with post-crisis macroprudential policies.

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CECL and the Credit Cycle

Cited by 3 publications

References 34 publications

From Incurred Loss to Current Expected Credit Loss (CECL): A Forensic Analysis of the Allowance for Loan Losses in Unconditionally Cancelable Credit Card Portfolios

From Incurred Loss to Current Expected Credit Loss (CECL): A Forensic Analysis of the Allowance for Loan Losses in Unconditionally Cancelable Credit Card Portfolios

The Procyclicality of Impairment Accounting: Comparing Expected Losses Under IFRS 9 and US GAAP

Are Incurred Loss Standards Countercyclical? A Case Study Using U.S. Bank Holding Company Data

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