CECL And IFRS9 Fuel Demand For Credit Data


Banks are gearing up for major accounting changes over the next few years. Credit risk and modelling teams are now working with accounting policy divisions to draw up implementation plans for Current Expected Credit Loss (CECL: US) and International Financial Reporting Standard 9 (IFRS9: ex-US).

Details can be found here on the ABA website and here on the FASB website

From a credit point of view, the main change is the requirement to assess credit risk for loans over multiple time horizons. This is especially acute in the US, where banks governed by CECL need to assess the likely extent of impairment over the entire life of a loan. IFRS9 only requires this when the credit outlook has deteriorated significantly.

Credit Benchmark crowdsource the Probability of Default estimates from a growing number of global IRB banks. This provides a robust, detailed and frequently updated source of credit data which can be used to construct transition matrices and cumulative PD term structures. It also provides early warning of deterioration in the credit environment.

This probability data is ‘Real World’ rather than market-implied, so it does not contain any liquidity risk premium. As a result, it gives a more accurate assessment of the likely impairment to a loan over its lifetime, and that number will typically be noticeably lower than a market implied estimate. Because this data is ‘Through-the-Cycle’, it also lends itself to the longer time horizons required by CECL and IFRS9.

We will be presenting detailed analysis on this topic at the IACPM conference in Washington DC on the 4th November.


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Credit Benchmark brings together internal credit risk views from over 40 leading global financial institutions. The contributions are anonymized, aggregated, and published in the form of consensus ratings and aggregate analytics to provide an independent, real-world perspective of credit risk. Risk and investment professionals at banks, insurance companies, asset managers and other financial firms use the data for insights into the unrated, monitoring and alerting within their portfolios, benchmarking, assessing and analyzing trends, and fulfilling regulatory requirements and capital.