Abstract - Transformation of the Forecast Assessment of Expected Credit Losses in Monitoring and Assessment of Credit Risk in Commercial Banks

Journal of Reviews on Global Economics

Transformation of the Forecast Assessment of Expected Credit Losses in Monitoring and Assessment of Credit Risk in Commercial Banks  Pages 23-29

Elena V. Travkina, Yuliya N. Solnyshkova, Oksana A. Kazankina, Elena G. Azmanova and Yuliya V. Morozova


DOI: https://doi.org/10.6000/1929-7092.2020.09.04/span>

Published: 29 January 2020


Abstract: The article presents the results of the systematization of issues arising in connection with the transformation of the banks forecast assessment of expected credit losses during the monitoring and evaluation of credit risk in commercial banks. Based on the data obtained on the introduction of IFRS 9 "Financial instruments" into the banking sector, it is concluded that in banking practice there is uncertainty regarding the long-term impact of credit risk, and there are significant difficulties with the use of a large amount of additional information, which creates certain difficulties in calculating future credit losses of banks. It is noted that the current use of the model of predictive assessment of expected credit losses of customers in the monitoring and evaluation of credit risk in the bank should take into account the selected collective or individual basis of assessment. The article presents a comprehensive approach to the use of the impairment model of expected losses in banking as a basic tool for modeling expected credit losses in order to form provisions for impairment with the allocation. The modification of this model will depend on the specifics of the bank's credit activities and portfolio, the types of its financial instruments, the sources of available information, as well as the IT systems used. Validation of this model will reduce the expected credit losses, reduce the amount of estimated reserves, as well as improve the efficiency of the Bank as a whole.

Keywords: Assessment of expected credit losses, credit risk, default, bank borrower, financial instruments.

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