Naslov
Internal model for IFRS 9 - expected credit losses calculation

Autori
Volarević, Hrvoje ; Varović, Mario

Izvornik
Ekonomski pregled : mjesečnik Hrvatskog društva ekonomista Zagreb (0424-7558) 69 (2018), 3; 269-279

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni

Ključne riječi
(IFRS 9 ; Expected Credit Losses (ECL) ; Exposure at Default (EAD) ; Loss Given Default (LGD) ; Probability of Default (PD) ; Analytic Hierarchy Process (AHP) ; internal model)

Sažetak
This article explores and analyzes the implementation problem of International Financial Reporting Standard 9 (IFRS 9) which is in use from 1 January 2018. IFRS 9 is most relevant for financial institutions, but also for all business subjects with a significant share of financial assets in their Balance sheet. The main objective of this article is the implementation of new impairment model for financial instruments, which is measurable through Expected Credit Losses (ECL). The use of this model is in correlation with a credit risk of the company for which it is necessary to determine basic variables of the model: Exposure at Default (EAD), Loss Given Default (LGD) and Probability of Default (PD). Basel legislation could be used for LGD calculation while PD calculation is based on specific methodology with two different solutions. In the first option, PD is taken as an external data from reliable rating agencies. When there is no external rating, an internal model for PD calculation has to be created. In order to develop an internal model, authors of this article propose application of multi-criteria decision-making model based on Analytic Hierarchy Process (AHP) method. Input data in the model are based on information from financial statements while MS Excel is used for calculation of such multi- criteria problem. Results of internal model are mathematically related with PD values for each analyzed company. Simple implementation of this internal model is an advantage compared to other much more complicated models.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Ekonomija, Interdisciplinarne društvene znanosti

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