Assessment of technological capabilities to counter fraudulent practices in the banking sector
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 o...
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| Format: | Article |
| Language: | English |
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Publishing House of the State University of Management
2022-11-01
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| Series: | Вестник университета |
| Subjects: | |
| Online Access: | https://vestnik.guu.ru/jour/article/view/3900 |
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| _version_ | 1832541627574386688 |
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| author | A. V. Berdyshev I. E. Zarkhin A. A. Katysheva |
| author_facet | A. V. Berdyshev I. E. Zarkhin A. A. Katysheva |
| author_sort | A. V. Berdyshev |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a1e767b4f4f84b59b972644d1347ba20 |
| institution | Kabale University |
| issn | 1816-4277 2686-8415 |
| language | English |
| publishDate | 2022-11-01 |
| publisher | Publishing House of the State University of Management |
| record_format | Article |
| series | Вестник университета |
| spelling | doaj-art-a1e767b4f4f84b59b972644d1347ba202025-02-04T08:28:14ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152022-11-0101019320410.26425/1816-4277-2022-10-193-2042610Assessment of technological capabilities to counter fraudulent practices in the banking sectorA. V. Berdyshev0I. E. Zarkhin1A. A. Katysheva2Financial University under the Government of the Russian FederationFinancial University under the Government of the Russian FederationFinancial University under the Government of the Russian FederationIn 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.https://vestnik.guu.ru/jour/article/view/3900bankstransactionsfraudulent transactionsbig dataartificial intelligencemachine learninganti-fraud systems |
| spellingShingle | A. V. Berdyshev I. E. Zarkhin A. A. Katysheva Assessment of technological capabilities to counter fraudulent practices in the banking sector Вестник университета banks transactions fraudulent transactions big data artificial intelligence machine learning anti-fraud systems |
| title | Assessment of technological capabilities to counter fraudulent practices in the banking sector |
| title_full | Assessment of technological capabilities to counter fraudulent practices in the banking sector |
| title_fullStr | Assessment of technological capabilities to counter fraudulent practices in the banking sector |
| title_full_unstemmed | Assessment of technological capabilities to counter fraudulent practices in the banking sector |
| title_short | Assessment of technological capabilities to counter fraudulent practices in the banking sector |
| title_sort | assessment of technological capabilities to counter fraudulent practices in the banking sector |
| topic | banks transactions fraudulent transactions big data artificial intelligence machine learning anti-fraud systems |
| url | https://vestnik.guu.ru/jour/article/view/3900 |
| work_keys_str_mv | AT avberdyshev assessmentoftechnologicalcapabilitiestocounterfraudulentpracticesinthebankingsector AT iezarkhin assessmentoftechnologicalcapabilitiestocounterfraudulentpracticesinthebankingsector AT aakatysheva assessmentoftechnologicalcapabilitiestocounterfraudulentpracticesinthebankingsector |