Construction and application of financial fraud early warning model based on data mining

Teng Qin; Guanghua Cheng; Ziwei Wang

doi:10.1117/12.2639216

17 May 2022 Construction and application of financial fraud early warning model based on data mining

Teng Qin, Guanghua Cheng, Ziwei Wang

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 1225944 (2022) https://doi.org/10.1117/12.2639216
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

Financial fraud seriously destroys the principle of truthfulness and accuracy of information disclosure in the securities market. False information misleads stakeholders, brings them huge losses, and has a highly negative impact on the capital market. Therefore, exposing and curbing corporate financial fraud has always been the research focus of academic and practical circles. The application of data mining technology to the financial fraud early warning system of listed companies can enable enterprises to find, avoid and effectively prevent financial risks in time, to identify and curb the phenomenon of financial fraud effectively. Through the research, the overall recognition rates of the three fraud identification models for fraud examples and non-fraud examples are more than 80%. Through the comparison and improvement of three financial fraud recognition models, a comprehensive recognition model with high recognition rate and reliability is constructed.

Citation Download Citation

Teng Qin, Guanghua Cheng, and Ziwei Wang "Construction and application of financial fraud early warning model based on data mining", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 1225944 (17 May 2022); https://doi.org/10.1117/12.2639216

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