Assessment of technological capabilities to counter fraudulent practices in the banking sector
https://doi.org/10.26425/1816-4277-2022-10-193-204
Abstract
In connection with the strengthening of Western sanctions on the Russian banking sector, the number of malefactors, who enjoy the confidence of panicking depositors and the unstable situation in the banking market, has increased dramatically. The article discusses the key issues of the application of big data analysis as a technological basis for countering fraud in the practical activities of banks. The objectives of such a struggle are to determine the operations of intruders in the flow of large volumes of statistical information with the greatest accuracy and to take preventive measures to minimize damage. The purpose of the article is to assess the possibility of using machine learning technology by banks and develop an algorithm for detecting fraudulent transactions based on programming. Particular attention is paid to the current economic environment, its impact on the financial system as a whole, and in particular, on the reorientation of the banking sector to combat fraud in the context of increased fraud activity.
About the Authors
A. V. Berdyshev
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
Aleksandr V. Berdyshev, Cand. Sci. (Econ.), Assoc. Prof. at the Banking and Monetary Regulation Department
Moscow
I. E. Zarkhin
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
Ivan E. Zarkhin, Student
Moscow
A. A. Katysheva
Financial University under the Government of the Russian Federation
Russian Federation
Russian Federation
Arina A. Katysheva, Student
Moscow
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Review
For citations:
Berdyshev A.V., Zarkhin I.E., Katysheva A.A. Assessment of technological capabilities to counter fraudulent practices in the banking sector. Vestnik Universiteta. 2022;(10):193-204. (In Russ.) https://doi.org/10.26425/1816-4277-2022-10-193-204
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