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Identity Theft and Consumer Payment Choice: Does Security Really Matter?

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An Erratum to this article was published on 06 June 2015

Abstract

Security is a critical aspect of electronic payment systems. In recent years, the phenomenon of identity theft has gained widespread media coverage and has grown to be a major concern for payment providers and consumers alike. How identity theft has affected consumer’s payment choice is still an open research question. We use the 2009 Survey of Consumer Payment Choice (SCPC) to study the effect of identity theft incidents on adoption and usage patterns for nine different payment instruments in the U.S. Our results suggest that certain types of identity theft incidents affect positively the probability of adopting money orders, credit cards, stored value cards, bank account number payments and online banking bill payments. As for payment usage, we find that particular types of identity theft incidents have a positive and statistically significant effect on the use of cash, money orders and credit cards and a negative and statistically significant effect on the use of checks and online banking bill payments. These results are robust across different types of transaction, after controlling for various socio-demographic characteristics and perceptions toward payment methods.

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Notes

  1. Most Americans are concerned about payment fraud and this concern supersedes that of terrorism, computer and health viruses and personal safety (Eisenstein 2008; Federal Trade Commission 2008; Unisys 2009).

  2. For example, the AARP Public Policy Institute found that 24 percent of its survey’s respondents always pay restaurant bills with cash rather than a debit or credit card because they are worried about their card being misused (Mayer 2006). See also Acoca (2008), Arango and Taylor (2009), Benton et al. (2007), Bolt and Chakravorti (2008), He et al. (2008), and Jonker (2007).

  3. See section 2.2 for greater detail.

  4. Our findings add to recent research that analyzes the impact of media reports (i.e., newspaper announcements on debit card fraud) on debit card usage (Kosse 2013a).

  5. Arango and Taylor (2009) also highlight the importance for policy makers of improved understanding of the effects of security on payment choice.

  6. See Appendix Table 6 for a description of each payment instrument.

  7. See Section 4.1 for a detailed definition of payment instrument characteristics.

  8. It should be note that consumer’s assessment of security could be influenced by previous identity theft incidents. We examine this important issue in Section 4.

  9. Listerman and Romesberg (2009) report that it takes an identity theft victim an average of 58 to 231 hours of personal time to deal with all of the correcting and legal issues. Moreover, in many cases, it takes years to restore the damage done to an individual’s credit ruined through fraud (Barker et al. 2008).

  10. A report from the Federal Trade Commission showed that credit card fraud was the most common form of identity theft (Finklea 2012).

  11. The survey doesn’t include assessments of characteristics for money orders (MO) and traveler’s checks (TC). Therefore, both adoption and usage models for these payment instruments don’t include perceptions as covariates.

  12. Similar results were obtained using raw absolute self-reported assessment of payment characteristics (security, acceptance, cost, and convenience) on a scale of 1–5. In addition, we tested for differences between the vector of shares (percentage of consumers who have been victims of identity theft) within each of the five categories of security and results remain the same (results are available upon request).

  13. We thank an anonymous referee for pointing this out.

  14. The definition of adoption in the 2009 SCPC varies across payment instruments. See Appendix Table 6 for details.

  15. See Appendix Table 7 for definitions of transaction types.

  16. As is usual in Heckman selection models, exclusion restrictions are needed. Therefore, X i1 has been excluded from the usage equation (second step) for an adequate identification of the model.

  17. This is one important improvement of the 2009 SCPC with respect to previous editions where perceptions of payment characteristics (e.g., security) were only available for payment adopters but not for non-adopters.

  18. See Section 2 and Fig. 3 for additional details.

  19. We do not estimate cash adoption since the average adoption rate of cash in our sample is 99.8 %. Cash usage results were estimated via OLS. Nevertheless, similar results were obtained using the Heckman two-step procedure.

  20. In response to a helpful suggestion from the referee, we run a set of regressions of each type of identity theft on consumer observables and control variables (number of payments and types of payments). Preliminary results suggest that the occurrence of identity theft incidents is mainly related to the state of residence and socio-demographics characteristics of consumers. However, no clear common patterns were observed and results vary depending on the covariates included in the model. This is indeed a new area to explore and too big to handle here and therefore the need of further research in this area is needed.

  21. Marginal effects reported in Table 5 were rounded to two decimal places. However, simulated effects reported in Figs. 4, 5, 6a and 6b are computed using 10 decimal digits of accuracy and they may seem slightly different due to rounding.

  22. More detailed data about different types of payment instruments (e.g., if they have enhanced security options) could contribute to a better understanding of the positive effect observed on the adoption of these instruments.

  23. While some consumers are protected from direct losses arising from different forms of payment fraud (not exclusive related to identity theft incidents), the costs to victims can be substantial and affect their preferences towards specific payment instruments. Furletti and Smith (2005a, 2005b) examine in detail the federal and state laws that protect consumers in case of debit and credit fraud as well as the relevant association, network, and bank policies that may apply.

  24. There may be some loss of information from annualizing the number of transactions, but simulations based on average marginal effects could still provide an approximation of the effect of identity theft incidents on payment usage.

  25. We compute all simulated effects using 10 decimal digits of accuracy. For this reason, the figure computed in this example (230.54 transactions) is slightly different to the figure reported in Fig. 5 (234.09 transactions).

  26. Unfortunately, since we are estimating the adoption and usage equations for each payment instrument independently, our model is not able to capture explicitly substitution patterns between payments methods after an identity theft shock. The estimation of a system of simultaneous equations for all payment instruments could provide a way to deal with this issue but it would require a significant amount of data beyond those used in this study.

  27. As we mentioned before, unfortunately our model is not able to capture the complexity of the relationships and substitution patterns across payment instruments. However, we acknowledge that this aspect is an important area for future research.

  28. Appendix Table 8 shows the regression results obtained in the second step of our selection models. It only reports the key variables of interest associated with identity theft incidents. Covariates remain the same as the previous Section, but they are not reported to save space. Results are available upon request from the authors.

References

  • AARP (2007) Consumer payment study. American association of retired persons. February 2007

  • Acoca B (2008) Online identity theft. OECD Obs 268:12–13

    Google Scholar 

  • Alvarez F, Lippi F (2009) Financial innovation and the transactions demand for cash. Econometrica 77(2):363–402

    Article  Google Scholar 

  • Anderson KB, Durbin E, Salinger MA (2008) Identity theft. J Econ Perspect 22(2):171–192

    Article  Google Scholar 

  • Arango C, Hogg D, Lee A (2012) Why is cash (still) so entrenched? Insights from the bank of Canada’s 2009 methods-of-payment survey: bank of canada discussion paper no. 2012–2

  • Arango C, Taylor V (2009) The role of convenience and risk in consumers’ means of payment. Bank of Canada discussion paper no. 2009–8

  • Attanasio O, Guiso L, Jappelli T (2002) The demand for money, financial innovation and the welfare cost of inflation: an analysis with households’ data. J Polit Econ 2(110):317–351

    Article  Google Scholar 

  • Barker KJ, D’Amato J, Sheridon P (2008) Credit card fraud: awareness and prevention. J Finance Crime 15(4):398–410

    Article  Google Scholar 

  • Benton M, Blair K, Crowe M, Schuh S (2007) The Boston Fed study of consumer behavior and payment choice: a survey of federal reserve system employees. Federal reserve bank of Boston, public policy discussion paper: 07–1

  • Bolt W, Chakravorti S (2008) Consumer choice and merchant acceptance of payment media. Federal reserve bank of Chicago, working paper series: WP-08-11

  • Bolton LE, Cohen JB, Bloom PN (2006) Does marketing products as remedies create “Get out of jail free cards”? J Consum Res 33(1):71–81

    Article  Google Scholar 

  • Borzekowski R, Kiser KE, Ahmed S (2008) Consumers’ use of debit cards: patterns, preferences, and price response. J Money Credit Bank 40(1):149–172

    Article  Google Scholar 

  • Burns P, Stanley A (2002) Fraud management in the credit card industry. Federal reserve bank of Philadelphia. Payment cards center discussion paper no. 02–05

  • Carbó-Valverde S, Liñares-Zegarra JM (2011) How effective are rewards programs in promoting payment card usage? Empirical evidence. J Bank Financ 35(12):3275–3291

    Article  Google Scholar 

  • Cameron, A C, Trivedi, PK (2005) Microeconometrics: methods and applications. Cambridge University Press

  • Cheney J (2006) Supply-and demand-side developments influencing growth in the debit market. Federal reserve bank of Philadelphia. Payment cards center discussion paper no. 06–11

  • Cheney J (2010) Heartland payment systems: lessons learned from a data breach. Federal reserve bank of Philadelphia. Payment cards center discussion paper no. 10–1

  • Ching AT, Hayashi F (2010) Payment card rewards programs and consumer payment choice. J Bank Financ 34(8):1773–1787

    Article  Google Scholar 

  • Conkey C (2007) Assessing identity-theft costs. The wall street journal—Eastern edition Vol. 250

  • Copes H, Kerley KR, Huff R, Kane J (2010) Differentiating identity theft: an exploratory study of victims using a national victimization survey. J Crime Justice 38(5):1045–1052

    Article  Google Scholar 

  • Crooks T (2004) Fear of ID theft may do more harm than the crime. Am Banker 169(102):10

    Google Scholar 

  • Douglass DB (2009) An examination of the fraud liability shift in consumer card-based payment systems. Econ Perspect 33(1):43–49

    Google Scholar 

  • Eisenstein EM (2008) Identity theft: an exploratory study with implications for marketers. J Bus Res 61(11):1160–1172

    Article  Google Scholar 

  • Federal Trade Commission (2008) Consumer fraud and identity theft complaint data. Federal trade commission. January–December 2007

  • Finklea KM (2010) Identity theft: Trends and issues. Congressional research service - prepared for members and committees of congress congressional research service, February 2010

  • Finklea KM (2012) Identity theft: trends and issues. Congressional research service - prepared for members and committees of congress congressional research service, February 2012

  • Foster K, Meijer E, Schuh S, Zabek M (2011) The 2009 survey of consumer payment choice. Federal reserve bank of Boston, public policy discussion paper no. 11–1

  • Furletti M, Smith S (2005a) The laws, regulations, and industry practices that protect consumers who use electronic payment systems: ACH e-checks and prepaid cards. Federal reserve bank of Philadelphia, payment cards center discussion paper no. 05–04

  • Furletti M, Smith S (2005b) The laws, regulations, and industry practices that protect consumers who use electronic payment systems: Credit and debit cards. Federal reserve bank of Philadelphia, payment cards center discussion paper no. 05–01

  • Hayashi F, Klee E (2003) Technology adoption and consumer payments: evidence from survey data. Rev Netw Econ 2(2):175–190

    Article  Google Scholar 

  • He P, Huang L, Wright R (2008) Money, banking, and monetary policy. J Monet Econ 55(6):1013–1024

    Article  Google Scholar 

  • Humphrey DB, Pulley LB, Vesala JM (1996) Cash, paper, and electronic payments: a cross-country analysis. J Money Credit Bank 28(4):914–939

    Article  Google Scholar 

  • Javelin Strategy & Research (2010) The 2010 identity fraud survey report. California

  • Jonker N (2007) Payment instruments as perceived by consumers—results from a household survey. De Economist 155(3):271–303

    Article  Google Scholar 

  • Kahn CM, McAndrews J, Roberds W (2005) Money is privacy. Int Econ Rev 46(2):377–399

    Article  Google Scholar 

  • Kahn CM, Roberds W (2008) Credit and identity theft. J Monet Econ 55(2):251–264

    Article  Google Scholar 

  • Kahn CM, Roberds W (2009) Why pay? An introduction to payments economics. J Financ Intermed 18(1):1–23

    Article  Google Scholar 

  • Klee E (2008) How people pay: evidence from grocery store data. J Monet Econ 55(3):526–541

    Article  Google Scholar 

  • Kosse A (2013a) Do newspaper articles on card fraud affect debit card usage? J Bank Financ 37(12):5382–5391

    Article  Google Scholar 

  • Kosse A (2013b) The safety of cash and debit cards: a study on the perception and behaviour of Dutch consumers. Int J Cent Bank 9(4):77–98

    Google Scholar 

  • Linnhoff S, Langenderfer J (2004) Identity theft legislation: the fair and accurate credit transactions act of 2003 and the road not taken. J Consum Aff 38(2):204–216

    Article  Google Scholar 

  • Listerman RA, Romesberg J (2009) Are we safe yet? Strat Financ 91(1):27–33

    Google Scholar 

  • Mayer RN (2006) Defending your financial privacy: the benefits and limits of self-help. AARP public policy institute. Working paper no 2006–06

  • Mooney CZ, Duval RD (1993) Bootstrapping: A nonparametric approach to statistical inference. Sage, Newbury Park

    Book  Google Scholar 

  • Newman GR, McNally MM (2005) Identity theft literature review. Department of Justice, National Institute of Justice. NCJRS Report No. 210459, page 14

  • Pagan A (1984) Econometric issues in the analysis of regressions with generated regressors. Int Econ Rev 25:183–209

    Article  Google Scholar 

  • Roberds W, Schreft SL (2009a) Data security, privacy, and identity theft: the economics behind the policy debates. Econ Perspect 33(1):22–30

    Google Scholar 

  • Roberds W, Schreft SL (2009b) Data breaches and identity theft. J Monet Econ 56(7):918–929

    Article  Google Scholar 

  • Rysman M (2009) Consumer payment choice: measurement topics. In: The changing retail payments landscape: What role for central banks? An international payment policy conference sponsored by the federal reserve bank of Kansas City, Federal reserve of Kansas City, 2009. pp 61–81

  • Schreft SL (2007) Risks of identity theft: can the market protect the payment system? Econ Rev Fed Reserv Bank Kansas City 92(4):5–40

    Google Scholar 

  • Schuh S, Stavins J (2010) Why are (some) consumers (finally) writing fewer checks? The role of payment characteristics. J Bank Financ 34(8):1745–1758

    Article  Google Scholar 

  • Schultz E (2005) Are credit card providers doing enough to stop identity theft? Comput Sec 24(6):435–436

    Google Scholar 

  • Sproule S, Archer N (2010) Measuring identity theft and identity fraud. Int J Bus Govern Ethics 5(1):51–63

    Article  Google Scholar 

  • Sullivan RJ (2008) Can smart cards reduce payments fraud and identity theft? Econ Rev Fed Reserv Bank Kansas City 93(3):35–62

    Google Scholar 

  • Sullivan RJ (2010) The changing nature of U.S. card payment fraud: industry and public policy options. Econ Rev Fed Reserv Bank Kansas City 95(2):101–133

    Google Scholar 

  • Unisys (2009) UNISYS security indexTM report: United States. Lieberman Research Group. March—Wave 4

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Acknowledgments

Jose Liñares thanks financial support from the Spanish Ministry of Science (EX2009-0908). We would like to thank the Editors, Haluk Ünal and David Musto, and an anonymous referee for useful comments and suggestions. We also thank participants in seminars at the Bank of Canada, the Federal Reserve Bank of Atlanta, the Computer Laboratory Security Group (University of Cambridge), the Essex Finance Centre (EFiC) and the participants of the 2014 Finest Summer Workshop for helpful comments and suggestions. We also thank participants in the RES Annual Meeting 2012 in London and the 1st Conference for Responsible Banking and Finance held at University of St Andrews.

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Authors and Affiliations

  1. Department of Finance, College of Business, University of Illinois, 340 Wohlers Hall, 1206 South Sixth Street, Champaign, IL, 61820, USA

    Charles M. Kahn

  2. Essex Business School, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    José M. Liñares-Zegarra

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  1. Charles M. Kahn
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  2. José M. Liñares-Zegarra
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Correspondence to José M. Liñares-Zegarra.

Appendix

Appendix

Table 6 Definitions of payment instruments and payment adoption based on the 2009 SCPC
Full size table
Table 7 Definitions of transaction types
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Table 8 The impact of identity theft incidents on payment usage by type of transaction. Panels A, B and C below include second-step estimations (usage models) from a two-step Heckman Model. The dependent variable in usage models is the share of total payments made with that payment type. Estimated coefficients from first step regressions (adoption equations) are the same as those reported in Table 5. Robust z-statistics in parentheses based on bootstrapped standard errors clustered at the respondent’s state of residence level
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Kahn, C.M., Liñares-Zegarra, J.M. Identity Theft and Consumer Payment Choice: Does Security Really Matter?. J Financ Serv Res 50, 121–159 (2016). https://doi.org/10.1007/s10693-015-0218-x

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