Bank risk management in the conditions of financial system instability

Kazbekova, K. M.; Адамбекова, А. А.; Baimukhanova, Sariya; Kenges, G. K.; Bokhaev, Daurenbek

doi:10.9770/jesi.2020.7.4(46)

Cited by 7 publications

(2 citation statements)

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“…Firstly, the system takes the software object as the basic unit to complete the test (1) The data type of program is reasonable.…”

Section: Unit Testmentioning

confidence: 99%

“…With the rapid development of the global economy, the logistics industry has also ushered in a period of rapid development. The volatility of the global economic development makes the role of logistics finance in the market economic environment and its important position in the market environment more and more obvious [1][2]. However, while the logistics financial business plays an important role in the operation of market economy, the emergence of various risks also plagues the smooth development of logistics financial business of logistics companies to a great extent [3][4].…”

Section: Introductionmentioning

confidence: 99%

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Bank Financial Business Risk Assistant Management System Based on Clustering Algorithm

Wang¹

2021

Proceedings of the 2021 International Conference on Public Relations and Social Sciences (ICPRSS 2021)

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In recent years, compliance risk has gradually become an important risk faced by China's commercial banks in addition to credit risk, market risk and operational risk. The lifeline of commercial banks is risk management. In view of the harmfulness of the financial crisis, this paper tries to find out the relevant index parameters that have obvious impact on the financial risk. By building a prediction model, it can predict the risk that may have an impact on China, effectively find the potential financial risk, serve the operation of the macro financial market, and improve the accuracy of financial supervision. In this paper, the current web crawler technology and clustering data mining analysis technology are applied to build an efficient audit risk management system based on bank financial risk management. It takes a lot of time, manpower and energy to screen the original messy and high-risk huge basic data, which effectively improves the management and control efficiency of audit risk in the current social security field, it reduces the workload of audit risk identification and control in the audit process, and can be popularized in some areas. Based on the construction of chaotic neural network prediction model based on wavelet clustering algorithm and FCM clustering algorithm, this paper makes an empirical comparison of the early warning effect of the two models, and compares the advantages and disadvantages of adding different clustering algorithms and chaotic neural network prediction through empirical comparison. After model comparison and analysis, it is found that the risk prediction system of chaotic neural network prediction model based on wavelet clustering algorithm has high accuracy, and the maximum error is only 0.1173, which meets the needs of users.

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“…Firstly, the system takes the software object as the basic unit to complete the test (1) The data type of program is reasonable.…”

Section: Unit Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bank Financial Business Risk Assistant Management System Based on Clustering Algorithm

Wang¹

2021

Proceedings of the 2021 International Conference on Public Relations and Social Sciences (ICPRSS 2021)

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Financial Risk Management of Small and Medium Sized Enterprises in the Internet Environment

Tan

2022

2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City

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The system for assessing the socio-economic sustainability of the region for the development of entrepreneurial networks in conditions of restrictions using the methods of mathematical modeling

Jallal

Gabrielyan²,

Burkaltseva³

et al. 2023

E3S Web of Conf.

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The subject of the research is scientific and methodological provisions for the study of assessing the socio-economic sustainability of the region for the development of entrepreneurial networks in conditions of restrictions. The purpose of the study is to assess the socio-economic accountability of the region (using the example of the Federal Districts of the Russian Federation). The authors improved the methodology for assessing the socio-economic sustainability of the region, identified assessment indicators and substantiated their threshold values by methods of mathematical modeling. The most financially stable and unstable regions were identified. Recommendations are given for the most vulnerable regions.

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Bank risk management in the conditions of financial system instability

Cited by 7 publications

References 0 publications

Bank Financial Business Risk Assistant Management System Based on Clustering Algorithm

Bank Financial Business Risk Assistant Management System Based on Clustering Algorithm

Financial Risk Management of Small and Medium Sized Enterprises in the Internet Environment

The system for assessing the socio-economic sustainability of the region for the development of entrepreneurial networks in conditions of restrictions using the methods of mathematical modeling

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