IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies

Under the IFRS 9 impairment model, entities must estimate the PD (Probability of Default) for all financial assets (and other elements) not measured at fair value through profit or loss. There are several methodologies for estimating this PD from market or historical information. However, in some c...

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Main Authors: David Delgado-Vaquero, José Morales-Díaz, Constancio Zamora-Ramírez
Format: Article
Language:English
Published: Universidad de Murcia 2020-07-01
Series:Revista de Contabilidad: Spanish Accounting Review
Subjects:
Online Access:https://revistas.um.es/rcsar/article/view/370951
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spelling doaj-f5835b7462234a7489417cf2ffa2db932020-11-25T02:14:16ZengUniversidad de MurciaRevista de Contabilidad: Spanish Accounting Review1138-48911988-46722020-07-0123210.6018/rcsar.370951IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companiesDavid Delgado-Vaquero0José Morales-Díaz1Constancio Zamora-Ramírez2EY SpainUniversidad Complutense de MadridUniversity of Seville Under the IFRS 9 impairment model, entities must estimate the PD (Probability of Default) for all financial assets (and other elements) not measured at fair value through profit or loss. There are several methodologies for estimating this PD from market or historical information. However, in some cases entities do not possess market or historical information concerning a counterparty. For such cases, we propose a model called Financial Ratios Scoring (FRS), by means of which an entity can obtain a “shadow rating” for a counterparty as a first step in estimating the PD. The model differentiates from other recent models in several aspects, such as the size of the database and the fact that it is focused on non-rated companies, for example. It is based on scoring the counterparty according to its key financial ratios. The score will place the counterparty on a percentile within a previously constructed sector distribution using companies with a credit rating published by rating agencies or financial vendors. We have tested the model reliability by calculating the internal credit rating of several companies (which have an official/quoted credit rating), and by comparing the rating obtained with the official one, and obtained positive results. https://revistas.um.es/rcsar/article/view/370951IFRS 9Impairment of Financial AssetsProbability of DefaultCredit Rating
collection DOAJ
language English
format Article
sources DOAJ
author David Delgado-Vaquero
José Morales-Díaz
Constancio Zamora-Ramírez
spellingShingle David Delgado-Vaquero
José Morales-Díaz
Constancio Zamora-Ramírez
IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
Revista de Contabilidad: Spanish Accounting Review
IFRS 9
Impairment of Financial Assets
Probability of Default
Credit Rating
author_facet David Delgado-Vaquero
José Morales-Díaz
Constancio Zamora-Ramírez
author_sort David Delgado-Vaquero
title IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
title_short IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
title_full IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
title_fullStr IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
title_full_unstemmed IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for non-rated companies
title_sort ifrs 9 expected loss: a model proposal for estimating the probability of default for non-rated companies
publisher Universidad de Murcia
series Revista de Contabilidad: Spanish Accounting Review
issn 1138-4891
1988-4672
publishDate 2020-07-01
description Under the IFRS 9 impairment model, entities must estimate the PD (Probability of Default) for all financial assets (and other elements) not measured at fair value through profit or loss. There are several methodologies for estimating this PD from market or historical information. However, in some cases entities do not possess market or historical information concerning a counterparty. For such cases, we propose a model called Financial Ratios Scoring (FRS), by means of which an entity can obtain a “shadow rating” for a counterparty as a first step in estimating the PD. The model differentiates from other recent models in several aspects, such as the size of the database and the fact that it is focused on non-rated companies, for example. It is based on scoring the counterparty according to its key financial ratios. The score will place the counterparty on a percentile within a previously constructed sector distribution using companies with a credit rating published by rating agencies or financial vendors. We have tested the model reliability by calculating the internal credit rating of several companies (which have an official/quoted credit rating), and by comparing the rating obtained with the official one, and obtained positive results.
topic IFRS 9
Impairment of Financial Assets
Probability of Default
Credit Rating
url https://revistas.um.es/rcsar/article/view/370951
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