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This paper evaluates few of the popular approaches usedfor estimating Expected Credit Loss (ECL) by embedding the forecasts of future economic conditions as per IFRS 9 requirement. It is argued that although existing literature suggests superior performance of reduced form model over structural model, for individual financial institutions, developing reduced form model can be a challenge due to:
(a) Difficulty in modeling linkage between macro-economic indicators and portfolio delinquency (especially for retail portfolio)
(b) Forecasting of future macro-economic scenarios which are often subjective and may significantly differ across similar institutions.
A generalized version of the structural model is presented which can incorporate variation in default rate due to credit rating grades and correlation parameter is jointly calibrated along with the unobservable factor. It is possible to incorporate macro-economic factors in this model and can be applied to both retail and corporate portfolio.
JEL Classification: G17, G18
Keywords: IFRS 9, Expected Credit Loss (ECL), TTC PD, PIT PD, structural model and reduced form model.
(ProQuest: ... denotes formulae omitted.)
Section I
Introduction
In November 2009, the IASB issued the chapters of IFRS 9 relating to the classification and measurement of financial assets. Subsequently in July 2014 the completed version of IFRS 9 was published. In this version, IASB added to IFRS 9 the impairment requirements related to the accounting for expected credit losses (ECL) on an entity's financial assets and commitments to extend credit. Ministry of corporate affairs under government of India has also issued guideline (February 2015), 'Indian Accounting Standard (Ind AS) 109 Financial Instruments' for adoption of IFRS 9 for Indian entities where the impairment requirements related to the accounting for ECL is similar as per the IFRS 9 guideline.
The objective of this paper is to evaluate one of the key requirement of ECL estimation as stated in the measurement of expected credit losses section in the guideline 5.5.17 (c).
5.5.17. An entity shall measure expected credit losses of a financial instrument in a way that reflects:
(a) An unbiased and probability-weighted amount that is determined by evaluating a range of possible outcomes;
(b) The time value of money
(c) Reasonable and supportable information that is available without undue cost or effort at the reporting date about past events, current conditions and...