In the era of increased regulatory scrutiny, banks and other lenders have a growing need for Point-in-Time default risk estimates to satisfy IFRS9 and CECL accounting standards. However, the methodology and construction of these estimates vary significantly between different institutions. These institutional differences mean a simple impairment calculation for a standard loan could potentially vary by several million dollars, putting some firms at an obvious disadvantage during auditing periods.
Consensus credit data presents an opportunity for lenders to assess their internal models and identify where calibrations and methods differ from their peer group. Credit Transition Matrices (CTMs), created using Consensus data from Credit Benchmark, record the frequency of Consensus changes in 7-category credit notches over a set period of time. These CTMs can then be powered up to give estimated “Real World” Cumulative Probability of Default term structure curves for each credit category, which can in turn be converted into approximate Point-in-Time curves.
The latest whitepaper from Credit Benchmark details the creation of these PIT equivalent curves and examines their applicability for IFRS9 and CECL purposes.
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