Anti-Fraud Analysis during the COVID-19 Pandemic: A Global Perspective

Xiaoqian Zhu, Yinghui Wang, Yanpeng Chang, Rongda Chen () and Jianping Li
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Xiaoqian Zhu: School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China¶MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation at the University of Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China
Yinghui Wang: School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China†Institutes of Science and Development, Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China
Yanpeng Chang: ��Institutes of Science and Development, Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China‡School of Public Policy and Management, University of Chinese Academy of Sciences, Shijingshan District, Beijing 100049, P. R. China
Rongda Chen: �School of Finance, Zhejiang University of Finance and Economics, Xiasha Higher Education Park, Hangzhou, Zhejiang 310018, P. R. China
Jianping Li: School of Economics and Management, University of Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China¶MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation at the University of Chinese Academy of Sciences, Haidian District, Beijing 100190, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 01, 37-55

Abstract: The ongoing coronavirus disease 2019 (COVID-19) pandemic has brought unexpected economic downturns and accelerated digital transformation, leading to stronger financial fraud motives and more complicated fraud schemes. Although scholars, practitioners, and regulators have begun to focus on the new characteristics of financial fraud, a systematic and effective anti-fraud strategy during the pandemic still needs to be explored. This paper comprehensively analyzes the lessons of anti-fraud that we should learn from the COVID-19 pandemic. By exploring the complex motives and schemes of fraud, we summarize the characteristics of financial fraud activities and further analyze the regulatory challenges posed by financial fraud during the outbreak. To better cope with the fraudulent activities during the pandemic, policy proposals on how to improve the supervision of financial fraud activities are put forward. In particular, the panoramic data and graph-based techniques are powerful tools for future fraud detection.

Keywords: Financial fraud; COVID-19 pandemic; financial regulatory; graph neural network; big data (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219622023400023

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