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Credit Risk Modelling: Migration Rates Systems with Renewal and an IFRS9-baseline

Authors: Landini Simone; Mariacristina Uberti; Simone Casellina;

Credit Risk Modelling: Migration Rates Systems with Renewal and an IFRS9-baseline

Abstract

In 2014 the International Accounting Standards Board (IASB) promulgated the International Financial Reporting Standard 9 (IFRS9) ([1, 4]). This new accounting standard substitutes the previous IASB39-Financial Instrument since January 2018 and banks are operating with effort to meet the many technical and normative innovations introduced to provide more reliable and well-balanced estimates of Expected Losses (EL). Among these, we focus our attention on two aspects that have impact on the EL estimation that must be (a) prospective and (b) segmented. Moreover, according to the recent prudential standard (Credit Risk Directive, [2], and Credit Risk Regulation [3]), the capital requirements should be forward-looking and consistent with the Unexpected Losses measurement. The first part of the paper summarizes the main traits of a model for the micro-simulation of a portfolio of a bank that, under the influence of the macroeconomic cycle, dynamically renews with entries and exits and that estimates migration rates matrices conditionally to the cycle ([5]). The second part prospectively extrapolates future migration matrices for the open system portfolio, and it implements an accounting IFRS9-baseline by reshaping the configuration of the grades according to the segmentation in a 3-stage bucketing. Furthermore, consistently with these accounting principles a forward-looking estimate of the UL for the bank is introduced. Differently from the more standard static-closed-sample approach, and although developed upon an in-silico bank’s portfolio, the obtained results give hints that (a) opening the migration rates matrices to entries and exits and (b) implementing a prospective and segmented estimation of their future dynamics, the bank may expect to a more reliable and less costly estimates of the EL and UL.

Country
Italy
Keywords

Credit Risk; Migration Rates Modelling; Expected Loss; Unexpected Loss.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green