Abstract
This study estimates the prevalence of consumer fraud in China and investigates consumer fraud risk factors using a novel two-stage conceptual framework that differentiates fraud exposure from fraud victimization after exposure. Multivariate analyses show that multiple risk factors have opposite effects on the two stages, with older age, lower income, higher debt, lower education, and rural residency associated with a lower risk of fraud exposure but a higher risk of fraud victimization after exposure. Three variables are identified as risk factors in both processes: being a migrant, having a higher level of objective financial knowledge, and having at least one chronic condition. Our conceptual model and empirical results demonstrate the importance of utilizing a two-stage approach in consumer fraud victimization research that may help clarify the many mixed findings in the literature.
Similar content being viewed by others
Code availability
Stata codes are available from the authors upon request.
References
Alves, L. M., & Wilson, S. R. (2008). The effects of loneliness on telemarketing fraud vulnerability among older adults. Journal of Elder Abuse & Neglect, 20(1), 63–85. https://doi.org/10.1300/J084v20n01_04
Anderson, K. B. (2004). Consumer fraud in the United States: An FTC survey. Federal Trade Commission Washington, DC.
Anderson, K. B. (2013). Consumer fraud in the United States, 2011: The third FTC survey. Federal Trade Commission. Retrieved from https://www.ftc.gov/sites/default/files/documents/reports/consumer-fraud-united-states-2011-third-ftc-survey/130419fraudsurvey_0.pdf
Anderson, K. B. (2016). Mass-market consumer fraud: Who is most susceptible to becoming a victim? Retrieved from https://www.ftc.gov/system/files/documents/reports/mass-market-consumer-fraud-who-most-susceptible-becoming-victim/working_paper_332.pdf
Anderson, K. B. (2019). Mass-market consumer fraud in the United States: A 2017 update. Retrieved from https://www.ftc.gov/system/files/documents/reports/mass-market-consumer-fraud-united-states-2017-update/p105502massmarketconsumerfraud2017report.pdf
Australian Bureau of Statistics. (2016). 4528.0 - Personal Fraud, 2014–15. Retrieved from https://www.abs.gov.au/ausstats/abs@.nsf/cat/4528.0
Beach, S. R., Schulz, R., & Sneed, R. (2018). Associations between social support, social networks, and financial exploitation in older adults. Journal of Applied Gerontology, 37(8), 990–1011. https://doi.org/10.1177/0733464816642584
Beals, M., DeLiema, M., & Deevy, M. (2015). Framework for a taxonomy of fraud. Retrieved from http://longevity3.stanford.edu/wp-content/uploads/2015/11/Full-Taxonomy-report.pdf
Brenner, L., Meyll, T., Stolper, O., & Walter, A. (2020). Consumer fraud victimization and financial well-being. Journal of Economic Psychology, 76, 102243. https://doi.org/10.1016/j.joep.2019.102243
Burnes, D., Henderson, C. R., Jr., Sheppard, C., Zhao, R., Pillemer, K., & Lachs, M. S. (2017). Prevalence of financial fraud and scams among older adults in the United States: A systematic review and meta-analysis. American Journal of Public Health, 107(8), e13–e21. https://doi.org/10.2105/AJPH.2017.303821
Carstensen, L. L. (1992). Social and emotional patterns in adulthood: Support for socioemotional selectivity theory. Psychology and Aging, 7(3), 331–338. https://doi.org/10.1037/0882-7974.7.3.331
Chan, K. W. (2018). Urbanization with Chinese characteristics: The Hukou system and migration. Routledge.
Chan, K. W., & Zhang, L. (1999). The Hukou system and rural-urban migration in China: Processes and changes. The China Quarterly, 160, 818–855. https://doi.org/10.1017/S0305741000001351
Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics Simulation and Computation, 39(4), 860–864. https://doi.org/10.1080/03610911003650383
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press.
Consumer Fraud Research Group. (2006). Investor fraud study final report. NASD Investor Education Foundation. Retrieved from https://www.sec.gov/news/press/extra/seniors/nasdfraudstudy051206.pdf
Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608. https://doi.org/10.2307/2094589
Deevy, M., Lucich, S., & Beals, M. (2012). Scams, schemes & swindles. Financial Fraud Research Center. Retrieved from http://longevity.stanford.edu/wp-content/uploads/2017/01/Scams-Schemes-Swindles-FINAL-On-Website.pdf
DeLiema, M. (2015). Using mixed methods to identify the characteristics of older fraud victims. University of Southern California Dissertations and Theses. Retrieved from http://digitallibrary.usc.edu/cdm/ref/collection/p15799coll3/id/537449
DeLiema, M., Deevy, M., Lusardi, A., & Mitchell, O. S. (2020). Financial fraud among older Americans: Evidence and implications. The Journals of Gerontology: Series B, 75(4), 861–868. https://doi.org/10.1093/geronb/gby151
Dove, M. (2018). Predicting individual differences in vulnerability to fraud University of Portsmouth]. Retrieved from https://researchportal.port.ac.uk/portal/files/13066355/M.Dove_Thesis.pdf
Dowd, J. (1975). Aging as exchange: A preface to theory. Journal of Gerontology, 30(5), 584–594. https://doi.org/10.1093/geronj/30.5.584
Drew, J. M., & Cross, C. (2016). Fraud and its prey: Conceptualising social engineering tactics and its impact on financial literacy outcomes. Financial literacy and the limits of financial decision-making (pp. 325–340). Springer.
Environics Research Group. (2008). Final report: 2007 Canadian Consumer Mass Marketing Fraud Survey. Competition Bureau Canada. Retrieved from https://www.ic.gc.ca/eic/site/112.nsf/vwapj/Environics-CompetitionBureau-MMF-FinalRReport-Feb2008.pdf/$file/Environics-CompetitionBureau-MMF-FinalRReport-Feb2008.pdf
Fan, J. X., & Yu, Z. (2021). Understanding aging and consumer fraud victimization in the Chinese context: A two-stage conceptual approach. Journal of Elder Abuse & Neglect. https://doi.org/10.1080/08946566.2021.1937428
Federal Trade Commission. (2017). Consumer sentinel network data book. Retrieved from https://www.ftc.gov/sites/default/files/documents/reports/consumer-fraud-united-states-ftc-survey/040805confraudrpt.pdf
FINRA Investor Education Foundation. (2013). Fraud susceptibility in the United States: Research report from a 2012 national survey. Retrieved from https://www.finrafoundation.org/sites/finrafoundation/files/Financial-Fraud-And-Fraud-Susceptibility-In-The-United-States_0_0_0.pdf
Friedman, M. (1992). Confidence swindles of older consumers. Journal of Consumer Affairs, 26(1), 20–46. https://doi.org/10.1111/j.1745-6606.1992.tb00014.x
Gan, L., Yin, Z., Jia, N., Xu, S., Ma, S., & Zheng, L. (2013). Data you need to know about China: Research Report of China Household Finance Survey 2012. Springer Science & Business Media.
Hauk, N., Hüffmeier, J., & Krumm, S. (2018). Ready to be a silver surfer? A meta-analysis on the relationship between chronological age and technology acceptance. Computers in Human Behavior, 84, 304–319. https://doi.org/10.1016/j.chb.2018.01.020
Hindelang, M. J., Gottfredson, M. R., & Garofalo, J. (1978). Victims of personal crime: An empirical foundation for a theory of personal victimization. Ballinger.
Holtfreter, K., Reisig, M. D., & Blomberg, T. G. (2005). Consumer fraud victimization in Florida: An empirical study. St. Thomas Law Review, 18(3), 761–790.
Judges, R. A., Gallant, S. N., Yang, L., & Lee, K. (2017). The role of cognition, personality, and trust in fraud victimization in older adults. Frontiers in Psychology, 8, 588. https://doi.org/10.3389/fpsyg.2017.00588
Kerley, K. R., & Copes, H. (2002). Personal fraud victims and their official responses to victimization. Journal of Police and Criminal Psychology, 17(1), 19–35. https://doi.org/10.1007/BF02802859
Lee, C. S. (2021). Online fraud victimization in China: A case study of Baidu Tieba. Victims & Offenders, 16(3), 343–362. https://doi.org/10.1080/15564886.2020.1838372
Lee, J., & Soberon-Ferrer, H. (1997). Consumer vulnerability to fraud: Influencing factors. Journal of Consumer Affairs, 31(1), 70–89. https://doi.org/10.1111/j.1745-6606.1997.tb00827.x
Li, J., & Rose, N. (2017). Urban social exclusion and mental health of China’s rural-urban migrants—A review and call for research. Health & Place, 48, 20–30. https://doi.org/10.1016/j.healthplace.2017.08.009
Li, J. C. M., Yu, M., Wong, G. T. W., & Ngan, R. M. H. (2016). Understanding and preventing financial fraud against older citizens in Chinese society: Results of a focus group study. International Journal of Offender Therapy and Comparative Criminology, 60(13), 1509–1531. https://doi.org/10.1177/0306624X15579258
Lusardi, A. (2015). Financial literacy: Do people know the ABCs of finance? Public Understanding of Science, 24(3), 260–271. https://doi.org/10.1177/0963662514564516
McAlvanah, P., Anderson, K. B., Letzler, R., & Mountjoy, J. (2015). Fraudulent advertising susceptibility: An experimental approach. Federal Trade Commission Working Paper No. 325. Retrieved from https://www.ftc.gov/reports/fraudulent-advertising-susceptibility-experimental-approach
McGhee, J. L. (1983). The vulnerability of elderly consumers. The International Journal of Aging and Human Development, 17(3), 223–246. https://doi.org/10.2190/7J2P-DGE5-GYHH-DCRX
Moon, M. (1990). Consumer issues and the elderly. The Journal of Consumer Affairs, 24, 235–244.
Morgan, R. (2021). Financial fraud in the United States, 2017. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics Bulletin. Retrieved from https://www.bjs.gov/index.cfm?ty=pbdetail&iid=7366
National Bureau of Statistics of China. (2016). China Statistics Yearbook 2016. Retrieved from http://www.stats.gov.cn/tjsj/ndsj/2016/indexeh.htm
National Bureau of Statistics of China. (2020). 2020 Migrant Workers Monitoring Survey Report 20212020. Retrieved from http://www.stats.gov.cn/tjsj/zxfb/202104/t20210430_1816933.html
Ohrnberger, J., Fichera, E., & Sutton, M. (2017). The relationship between physical and mental health: A mediation analysis. Social Science & Medicine, 195, 42–49. https://doi.org/10.1016/j.socscimed.2017.11.008
Pak, K., & Shadel, D. (2011). AARP Foundation national fraud victim study AARP Research and Strategic Analysis. Retrieved from https://assets.aarp.org/rgcenter/general/fraud-victims-11.pdf
Raval, D. (2021). Who is victimized by fraud? Evidence from consumer protection cases. Journal of Consumer Policy, 44(1), 43–72. https://doi.org/10.1007/s10603-020-09466-w
Saunders, L., Pizor, A., & Twomey, T. (2009). Desperate homeowners: Loan mod scammers step in when loan services refuse to provide relief. National Consumer Law Center. Retrieved from https://www.nclc.org/images/pdf/pr-reports/report-loan-mod-scams-2009.pdf
Shao, J., Du, W., Lin, T., Li, X., Li, J., & Lei, H. (2019). Credulity rather than general trust may increase vulnerability to fraud in older adults: A moderated mediation model. Journal of Elder Abuse & Neglect. https://doi.org/10.1080/08946566.2018.1564105
Survey and Research Center for China Household Finance. (2017). China Household Finance Survey 2017.
The National Center for Victims of Crime, & Investor Education Foundation. (2018). Taking action: An advocate’s guide to assisting victims of financial fraud. Retrieved from https://www.saveandinvest.org/sites/saveandinvest/files/Taking-Action-An-Advocates-Guide-to-Assisting-Victims-of-Financial-Fraud.pdf
Titus, R. M., Heinzelmann, F., & Boyle, J. M. (1995). Victimization of persons by fraud. Crime & Delinquency, 41(1), 54–72. https://doi.org/10.1177/0011128795041001004
Van Wyk, J., & Benson, M. L. (1997). Fraud victimization: Risky business or just bad luck? American Journal of Criminal Justice, 21(2), 163–179. https://doi.org/10.1007/BF02887448
Xing, T., Sun, F., Wang, K., Zhao, J., Wu, M., & Wu, J. (2020). Vulnerability to fraud among Chinese older adults: Do personality traits and loneliness matter? Journal of Elder Abuse & Neglect, 32(1), 46–59. https://doi.org/10.1080/08946566.2020.1731042
Zhang, L., Sharpe, R. V., Li, S., & Darity, W. A., Jr. (2016). Wage differentials between urban and rural-urban migrant workers in China. China Economic Review, 41, 222–233. https://doi.org/10.1016/j.chieco.2016.10.004
Funding
N.A.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Ethical approval
This study uses second data and is considered exempt by the University of Utah Institution Review Board.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Rights and permissions
About this article
Cite this article
Fan, J.X., Yu, Z. Prevalence and Risk Factors of Consumer Financial Fraud in China. J Fam Econ Iss 43, 384–396 (2022). https://doi.org/10.1007/s10834-021-09793-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10834-021-09793-1