Innovative Applications of BP Neural Networks in Financial Fraud Recognition

Authors

  • Zibin Geng
  • Junchen Liu
  • Jiuzhou Wang

DOI:

https://doi.org/10.62051/0wx73902

Keywords:

Financial fraud; XGBoost; BP neural network.

Abstract

In this study, through the use of machine learning models and BP neural network, a large amount of financial data is deeply mined and analysed. The research results show that the constructed model improves the financial fraud recognition accuracy to 0.94, which can achieve the discrimination of financial fraudulent account behaviours at a high accuracy rate, provide strong support for financial institutions, and effectively prevent financial fraud risks. This study aims to solve the problem of high variability and concealment of financial fraud, different from the direction of departure of the more significant results of fraud identification for financial transactions, but focuses on the portrayal and analysis of the characteristics of the financial fraud account, so as to achieve the efficient identification of the source of financial fraud decision-making.

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References

[1] Lv Jun. Research on fraud risk management of fintech platform based on artificial intelligence [D]. Beijing University of Posts and Telecommunications, 2023.

[2] P.C. Ning. Research on financial fraud detection method based on graph neural network [D]. Donghua University, 2023.

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[6] Shiqi Jiang. Research on credit card anti-fraud model [D]. Chongqing University, 2021.

[7] Ding Shuangs. Research on the identification of internet financial fraud behaviour based on big data [D]. Capital University of Economics and Business, 2017.

[8] Zhang Yuanyuan. Fraud identification based on feature engineering and mean uncertain logistic regression in advertising and banking [D]. Shandong University, 2024.

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[10] Liu Xiaofei. Research and application of knowledge graph in the field of anti-fraud in financial system [D]. University of International Business and Economics, 2024.

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Published

12-08-2024

How to Cite

Geng, Z., Liu, J. and Wang, J. (2024) “Innovative Applications of BP Neural Networks in Financial Fraud Recognition”, Transactions on Computer Science and Intelligent Systems Research, 5, pp. 1727–1732. doi:10.62051/0wx73902.