Skip to main content
SpringerLink
Log in

Privacy for Loan Applicants Versus Predictive Power for Loan Providers: Is It Possible to Bridge the Gap?

  • Chapter
  • First Online:
European Data Protection: In Good Health?

Abstract

Loan providers manage risk by assessing applicants’ ability and willingness to re-pay. The loan application is the most visible aspect of credit scoring. To prevent gaming of the process, loan providers do not reveal why they ask for certain information. This lack of transparency leads applicants to perceive some questions as invasive. We investigated this phenomenon in three studies. The first survey revealed that applicants were least comfortable with providing their work phone number, value of other assets, and total number of investments. Ten interviews with loan applicants indicated that loan application forms do not allow them to adequately describe their financial situation. In the second survey 12% of participants reported they had not applied for credit because of the information requested. Results suggest that loan providers should explain why information is requested and how it will be used. Applicants’ satisfaction with credit scoring can be improved by: (1) letting applicants specify how/when they want to be contacted; (2) obtaining informed consent for data sharing with third parties; and (3) making some data items optional.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Credit Action, “Debt statistics”, December 2010.

  2. 2.

    Martin Lewis’ MoneySavingExpert.com, “Credit rating: How it works and how to improve it”. http://www.moneysavingexpert.com/loans/credit-rating-credit-score.

  3. 3.

    Expert interviews were conducted in a previous case study (not yet published).

  4. 4.

    Expert 3, a representative from a credit union.

  5. 5.

    Expert 1, a risk management consultant for a financial services authority.

  6. 6.

    Expert 2, a representative from a peer-to-peer lending company.

  7. 7.

    Expert 1, a risk management consultant for a financial services authority.

  8. 8.

    Expert 2, a representative from a peer-to-peer lending company.

  9. 9.

    “Limesurvey.” http://www.limesurvey.org/.

  10. 10.

    The “e-Rewards” business, subsequently re-branded as “Research Now.” http://www.researchnow.com/.

  11. 11.

    “Fingertips Typing Services.” http://www.fingertipstyping.co.uk/.

  12. 12.

    “UCL Psychology Subject Pool.” http://uclpsychology.sona-systems.com/.

  13. 13.

    “Limesurvey.” http://www.limesurvey.org/.

  14. 14.

    The “e-Rewards” business, subsequently re-branded as Research Now. http://www.researchnow.com/.

  15. 15.

    See Chap. 2.2, note 13. (1) Adams and Sasse, “Privacy in multimedia communications: Protecting users, not just data”, 49–64. (2) Culnan, “How did they get my name? An exploratory investigation of consumer attitudes towards secondary information use”, 341, 363.

  16. 16.

    UK Data Protection Act 1998, c. 29. http://www.legislation.gov.uk/ukpga/1998/29/section/29.

  17. 17.

    See Chap. 2.2, note 14. Friedman, Lin and Miller, “Informed consent by design”, 495–521.

  18. 18.

    See Chap. 6.1, note 26. Kerr, Barrigar, Burkell and Black, “Soft surveillance, hard consent”, 1–14.

  19. 19.

    Expert 4, a university professor with a background in consumer finance statistics research.

  20. 20.

    See Chap. 2.2, note 12. Expert 2, a representative from a peer-to-peer lending company.

References

  • Acquisti, Alessandro. 2009. Nudging privacy: The behavioural economics of personal information. IEEE Security and Privacy 7:82–86. doi:10.1109/MSP.2009.163.

    Article  Google Scholar 

  • Adams, Anne, and Angela Sasse. 2001. Privacy in multimedia communications: Protecting users, not just data. In People and computers XV—interaction without frontiers: Joint Proceedings of HCI 2001 and IHM 2001, ed. Ann Blandford, Jean Vanderdonckt and Phil Gray, 49–64. London: Springer. ISBN-13: 978–1852335151.

    Chapter  Google Scholar 

  • Braun, Virginia, and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3 :77–101. doi:10.1191/1478088706qp063oa.

    Article  Google Scholar 

  • Culnan, Mary J. 1993. How did they get my name? An exploratory investigation of consumer attitudes toward secondary information use. MIS Quarterly 17:341–363. http://www.jstor.org/stable/249775. Accessed 10 Dec 2011.

    Article  Google Scholar 

  • Department for Work and Pensions. 2009. Households below average income (HBAI), 1994/95–2007/08”, ed. Nick Adams, George Johnson, Peter Matejic, Rupesh Vekaria and Julia Whatley, 190. Crown Copyright, 2009. http://research.dwp.gov.uk/asd/hbai/hbai2008/index.php?page=contents. Accessed 10 Dec 2011.

    Google Scholar 

  • Friedman, Batya, Peyina Lin, and Jessica K. Miller. 2005. Informed consent by design. In Security and usability: Designing secure systems that people can use, ed. Lorrie Cranor and Simson Garfinkel, 495–521. Sebastopol: O’Reilly. ISBN-13: 978–0596008277.

    Google Scholar 

  • Gellman, Robert. 2002. Privacy, consumers, and costs: How the lack of privacy costs consumers and why business studies of privacy costs are biased and incomplete. Digital Media Forum, Ford Foundation. http://epic.org/reports/dmfprivacy.html. Accessed 10 Dec 2011.

    Google Scholar 

  • HM Treasury. 2010. Speech by the Financial Secretary to the Treasury, Mark Hoban MP, at Reform. http://www.hm-treasury.gov.uk/speech_fst_011210.htm. Accessed 10 Dec 2011.

    Google Scholar 

  • Jennett, Charlene, Sacha Brostoff, Miguel Malheiros, and M. Angela Sasse. 2010. Investigating loan applicants’ perceptions of alternative data items and the effect of incentives on disclosure.” Privacy and Usability Methods (PUMP) Workshop, British HCI Conference. http://scone.cs.st-andrews.ac.uk/pump2010/papers/jennett.pdf. Accessed 10 Dec 2011.

    Google Scholar 

  • Johnson, Michael D., Georg Nader, and Claes Fornell. 1996. Expectation of perceived performance, and customer satisfaction for a complex service: The case of bank loans. Journal of Economic Psychology 17 :163–182. doi:10.1016/0167–4870(96)00002–5.

    Article  Google Scholar 

  • Kamleitner, Bernadette, and Erich Kirchler. 2007. Consumer credit use: A process model and literature review. Revue EuropĂ©enne de Psychologie AppliquĂ© 57:267–283. doi:10.1016/j.erap.2006.09.003.

    Article  Google Scholar 

  • Kerr, Ian, Jennifer Barrigar, Jacquelyn Burkell, and Katie Black. 2006. Soft surveillance, hard consent. Personally Yours 6:1–14. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=915407. Accessed 10 Dec 2011.

    Google Scholar 

  • MacCarthy, Mark, and Robert Gellman. 2010. The consumer financial protection bureau needs a privacy office. Privacy & Security Law Report 2010, Bureau of National Affairs Inc. http://explore.georgetown.edu/publications/51958/. Accessed 10 Dec 2011.

    Google Scholar 

  • Mont, Marco Cassasa, Yun Shen, Gina Kounga, and Siani Pearson. 2010. Technical architecture for the first realized case study. EnCoRe Project Deliverable D2.1, version 1.0. http://www.encore-project.info/deliverables_material/D2.1%20EnCoRe%20Architecture%20V1.0.pdf. Accessed 10 Dec 2011.

    Google Scholar 

  • Raab, Charles. 2004. The future of privacy protection. Cyber Trust & Crime Prevention Project. http://www.mendeley.com/research/future-privacy-protection/#. Accessed 10 Dec 2011.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University College London (UCL), Gower Street, WC1E 6BT, London, UK

    Charlene Jennett, Miguel Malheiros, Sacha Brostoff & M. Angela Sasse

Authors
  1. Charlene Jennett
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miguel Malheiros
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sacha Brostoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Angela Sasse
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Charlene Jennett .

Editor information

Editors and Affiliations

  1. Pleinlaan 2, Brussel, 1050, Belgium

    Serge Gutwirth

  2. , TILT, Tilburg University, Warandelaan 2, Tilburg, 5037 AB, Netherlands

    Ronald Leenes

  3. Center for Law, Science, Technology, and Society Studies (LSTS), Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium

    Paul De Hert

  4. Research Centre for Information, Technology & Law, University of Namur, Rempart de la Vierge 5, Namur, 5000, Belgium

    Yves Poullet

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Jennett, C., Malheiros, M., Brostoff, S., Sasse, M.A. (2012). Privacy for Loan Applicants Versus Predictive Power for Loan Providers: Is It Possible to Bridge the Gap?. In: Gutwirth, S., Leenes, R., De Hert, P., Poullet, Y. (eds) European Data Protection: In Good Health?. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2903-2_3

Download citation

Publish with us

Policies and ethics

Search

Navigation