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Modern high technologies
ISSN 1812-7320
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ИФ РИНЦ = 1,279

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FORECASTING BANK DEPOSITORS’ APPLICATION FOR INSURANCE USING MACHINE LEARNING MODELS

Gorelik A.V. 1, Grigorev A.P. 2
1 Federal State Institution of Higher Education «Russian University of Transport»
2 State Corporation "Deposit Insurance Agency"
The Central Bank of the Russian Federation annually revokes the license of dozens of banks, each of which has thousands, and sometimes tens of thousands of depositors. Federal law dated December 23, 2003 No. 177 «On Bank Deposit Insurance in Russian Federation» provides for the right of every individual bank depositor to apply for insurance reimbursement (up to 1.4 million rubles per person per bank) in case of bank license revocation. To do this, they usually contact the nearest office of the agent Bank that accepts applications for payment on behalf of the Deposit insurance Agency. However not all depositors take care to use their right. As a result, certain amounts of money remain unclaimed from Deposit Insurance Agency. This paper discusses some machine-learning models to predict the probability of individual depositor to apply for insurance reimbursement. For each model, variable parameters are described, for which optimal values are given within the framework of the problem under consideration, as well as the results of its work presented in several metrics. The degree of conditionality of the facts that depositors apply for insurance compensation is determined by various demographic and material factors.
ensemble methods
banks
depositors
decision trees
machine learning
nearest neighbor method
insurance compensation

Библиографическая ссылка

Горелик А.В., Григорьев А.П. ПРОГНОЗИРОВАНИЕ ОБРАЩЕНИЙ ВКЛАДЧИКОВ БАНКА ЗА СТРАХОВЫМ ВОЗМЕЩЕНИЕМ С ПОМОЩЬЮ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ // Современные наукоемкие технологии. 2020. № 11-1. С. 21-24;
URL: https://top-technologies.ru/en/article/view?id=38292 (дата обращения: 01.07.2026).