Malheiros, M;
Brostoff, S;
Jennett, C;
Sasse, A;
(2012)
Would You Sell Your Mother's Data? Personal Data Disclosure in a Simulated Credit Card Application.
In:
11th Annual Workshop on the Economics of Information Security.
WEIS: Berlin.
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Abstract
To assess the risk of a loan applicant defaulting, lenders feed applicants‟ data into credit scoring algorithms. They are always looking to improve the effectiveness of their predictions, which means improving the algorithms and/or collecting different data. Research on financial behavior found that elements of a person‟s family history and social ties can be good predictors of financial responsibility and control. Our study investigated how loan applicants applying for a credit card would respond to questions such as “Did any of your loved ones die while you were growing up?” 48 participants were asked to complete a new type of credit card application form containing such requests as part of a “Consumer Acceptance Test” of a credit card with lower interest rates, but only available to “financially responsible customers.” This was a double-blind study – the experimenters processing participants were told exactly the same. We found that: (1) more sensitive items are disclosed less often - e.g. friends‟ names and contact had only a 69% answer rate; (2) privacy fundamentalists are 5.6 times less likely to disclose data; and (3) providing a justification for a question has no effect on its answer rate. Discrepancies between acceptability and disclosure were observed – e.g. 43% provided names and contact of friends, having said they found the question unacceptable. We conclude that collecting data items not traditionally seen as relevant could be made acceptable if lenders can credibly establish relevance, and assure applicants they will be assessed fairly. More research needs to be done on how to best communicate these qualities.
| Type: | Proceedings paper |
|---|---|
| Title: | Would You Sell Your Mother's Data? Personal Data Disclosure in a Simulated Credit Card Application. |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.informatik.uni-trier.de/~ley/db/conf/we... |
| Language: | English |
| Additional information: | The data provided by DBLP on its webpages as well as the XML files available at our website are released under the Open Data Commons Attribution License (ODC-BY 1.0). You are free to copy, distribute, use, modify, transform, build upon, and produce derived works from our data as long as you attribute any public use of the data, or works produced from the data, in the manner specified in the license. Read the full ODC-BY 1.0 license text for the exact terms that apply. The ODC-BY 1.0 license is courtesy of the Open Knowledge Foundation. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1349987 |
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