Research Article
Probability of Default (PD) per Province to Estimate a More Granular Impairment Credit Loss for Bank ABC
@INPROCEEDINGS{10.4108/eai.31-3-2022.2320969, author={Mompo Octaria Tambunan and Dewi Hanggraeni}, title={Probability of Default (PD) per Province to Estimate a More Granular Impairment Credit Loss for Bank ABC}, proceedings={Proceedings of the 1st International Conference on Contemporary Risk Studies, ICONIC-RS 2022, 31 March-1 April 2022, South Jakarta, DKI Jakarta, Indonesia}, publisher={EAI}, proceedings_a={ICONIC-RS}, year={2022}, month={8}, keywords={ifrs 9 probability of default granular transition matrix regression model}, doi={10.4108/eai.31-3-2022.2320969} }- Mompo Octaria Tambunan
Dewi Hanggraeni
Year: 2022
Probability of Default (PD) per Province to Estimate a More Granular Impairment Credit Loss for Bank ABC
ICONIC-RS
EAI
DOI: 10.4108/eai.31-3-2022.2320969
Abstract
This paper aims to provide a more granular approach to the Probability of Default (PD) modeling process following the International Financial Reporting Standard (IFRS) 9 framework by calculating PWD credits per province at ABC Bank. The PD model will be formed using a transition matrix and multiple regression analysis, using historical credit data on Bank and macroeconomic factors for 2013-2020. The results showed that inter-provincial PD credit at ABC Bank resulted in more granular PWD credit than the model without provinces. The new model develops a smaller and actual impairment according to conditions in the province. Based on this analysis, the Bank can determine its expansion strategy in the future, namely channeling credit to regions with small PD.