Jinglin Jiang;Su Lin;Zhengwei Wang;Hongyu Xiang;

• 1:PBC School of Finance
• 2: Tsinghua University
• 3:School of Finance and Accounting
• 4: Fuzhou University of International Studies and Trade

Abstract：

Financial fraud has a non-negligible negative impact on households, society and financial markets. Therefore, it is important to study the factors that influence residents to become potential victims of financial fraud. Using data from China Family Panel Studies(CFPS), this paper empirically examines the relationship between residents' financial literacy and their possibility of becoming victims of potential frauds. Results show that residents with higher levels of financial literacy were less likely to be victims of potential fraudulent projects than those with lower levels of financial literacy. Specifically, a one-standard-deviation increase in financial literacy is associated with 9.9% decrease in the probability of residents becoming victims of a potential fraudulent project, and this effect also holds in those with lower levels of assets. Further tests show that this effect is more pronounced in people who use internets. These results sheds light on the understanding of financial knowledge's role in preventing the risk of financial fraud.

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Foundation: 国家自然科学基金青年项目“支付科技的社会治理作用——以携童乞讨为例”（72103110）;国家自然科学基金青年项目“基金投资者的社会责任投资偏好”（72203024）;; 福建省社会科学基金青年项目“数据要素化视角下数据资产估值的逻辑阐释、关联解读与体系构建”（FJ2024C024）的资助

Authors: Jinglin Jiang;Su Lin;Zhengwei Wang;Hongyu Xiang;

References：

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• (1)数据来源:《人民公安报》2019年3月5日文章《织密天网筑牢堤坝合力攻坚“天下无诈”》。此外,根据中国人民银行网站报道,2021年,中国人民银行支付结算司累计向公安部门移送可疑账户线索430万户,推送资金预警信息242.8万条,成功避免145.5万群众受骗(中国人民银行支付结算司,2022),详见http://www.pbc.gov.cn/redianzhuanti/118742/4489076/4499026/index.html (2)根据中国证券业协会网站报道:https://www.sac.net.cn/wzgn/zt/zgzqyxhclsszn/mtbd/202108/t20210830_147366.html (3)中国家庭金融调研(CHFS)是西南财经大学中国家庭金融调查与研究中心在全国开展的微观家庭调研,关于数据的描述可以参考秦芳等(2016)和尹志超等(2015)。 (4)尽管在调研问卷中包含了两个相关问题:“过去一年,您家遇到过下列哪些形式的诈骗?”以及“您家是否因此遭受损失?”,但考虑到对第一个问题存在“不精准报告”(inaccurate reporting)的问题,Wei et al.(2021)参考Engels et al.(2020)的做法,假设所有受访者都“接触”过欺诈,仅通过“您家是否因此遭受损失?”这个问题的回答,来确定因变量取值。当且仅当第二个问题回答为“否”时,因变量“fraud detection”(识别诈骗)取1,否则取0。 (5)调研问卷题目中设定的50%的年收益,并非作为区分投资项目欺诈风险的阈值;而是通过设定非常高的年收益水平,使得对应的投资项目具有非常高的金融欺诈风险。 (6)0.525个百分点为Probit回归计算出的边际效应。下文的回归中的边际效应也是依此方法计算。 (7)如果仅使用“如果有广告宣称有一个年收益50%的投资项目,您会投资吗?”或仅使用“如果关系非常好的亲友告诉您有一个年收益50%的投资项目,您会投资吗?”作为被解释变量的构建依据,结果也是类似的。 (8)限于篇幅,结果留存备案。