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 ca...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universidad de Murcia |
| Repositorio: | DIGITUM. Depósito Digital Institucional de la Universidad de Murcia |
| OAI Identifier: | oai:digitum.um.es:10201/94542 |
| Acceso en línea: | https://doi.org/10.6018/rcsar.370951 http://hdl.handle.net/10201/94542 |
| Access Level: | acceso abierto |
| Palabra clave: | IFRS 9 Impairment of Financial Assets Probability of Default Credit rating Deterioro de Activos Financieros Probabilidad de Quiebra Rating Crediticio CDU::6 - Ciencias aplicadas::65 - Gestión y organización. Administración y dirección de empresas. Publicidad. Relaciones públicas. Medios de comunicación de masas |
| Sumario: | 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 |
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