Privacy in Online Social Lending

Online social lending is the Web 2.0’s response to classical bank loans. Borrowers publish credit applications on websites which match them with private investors. We point to a conflict between economic interests and privacy goals in online social lending, empirically analyze the effect of data disclosure on credit conditions, and outline directions towards efficient yet privacy-friendly alternative credit markets. “There is no practice more dangerous than that of borrowing money,” said George Washington in 1797. For sure he has not accounted for the privacy risks of 21 century online social lending, the topic of this paper. Online social lending, also known as peer-to-peer lending, has grown rapidly after the launch of the first commercial platform, UK-based Zopa.com, in 2005. Drawing on concepts of (offline) micro-finance, the idea of social lending is to provide a marketplace for unsecured personal loans: an online platform lets borrowers advertise credit projects to individual lenders, who decide in which project they invest. Credit risk is shared in project-specific pools of lenders; each member funds a small share of the financed amount. As compensation for taking risk, interest is paid to the lenders, whereas platform operators typically charge fixed (i. e., riskfree) fees. The exact market mechanism differs between platforms and has very recently been subject to research in mechanism design (Chen, Ghosh, and Lambert 2009). Independent of the specific mechanism, matching borrowers’ demand with lenders’ supply online sidesteps the traditional role of banks as intermediaries in credit markets. Obviously, this technology-driven paradigm shift in organizing credit markets has a string of economic and social consequences. This paper covers only a small part, namely the role of personal data and the impact of social lending on borrowers’ informational privacy. Borrowers’ privacy is affected since credit applications entail personal data being irrevocably disclosed on the Internet. We will briefly revisit the role of information in credit markets from a privacy protection point of view and contrast it with empirical results from data collected on Smava.de, the largest German social lending platform. To the best of our knowledge, this is the first attempt to study social lending from a privacy angle. AAAI Spring Symposium on Intelligent Information Privacy Management, Stanford University, Palo Alto, CA, March 2010 Background and Research Question Adequate and coherent privacy regulation requires deep understanding of how the distribution of personal data (i. e., knowledge about individuals’ attributes) in a society affects social welfare. It is unlikely that in the near future, a single unified model will be ripe enough to guide policy makers. Therefore it is advisable to break the large problem into smaller, more tractable sector-specific ones. Credit markets form a particularly relevant sector for at least three reasons: first, they are core to modern economies’ allocation of capital; second, credit markets are driven by information and thus exhibit a clear link to questions of privacy regulation; and third, advances in technology are about to change the shape of credit markets substantially, as witnessed by the uptake of online social lending over the past couple of years. A welcome side-aspect is the availability of empirical data. Personal Information in Credit Markets Aside from traditional functions of financial intermediaries in credit markets, such as size, risk, and maturity transformation, modern economic theory recognizes that information is crucial to prevent market failure (Stiglitz 1981). At the same time, useful information almost always consists of personal data of borrowers. While privacy activists were already concerned about the use of such information by hopefully trustworthy institutions, such as banks and credit bureaus (Jentsch 2007), the privacy problem exacerbates when credit-relevant personal data is disclosed to every potential lender. For current platforms, this means all Internet users. Borrowers’ personal data may influence lenders’ credit decisions by several mechanisms: • Most importantly, information asymmetries (Akerlof 1970) preclude lenders from distinguishing between good and bad risks. Detailed information on borrowers and their envisaged projects helps to assess the likelihood of timely debt service and to adjust credit conditions accordingly. This improves the overall allocation of capital. • Knowing personal details of creditors, including their identity, facilitates contract monitoring and legal recourse in case of default. The mere possibility to do so can prevent moral hazard over the payback period. • This feedback channel exists also indirectly through joint liability and social sanctions (Besley and Coate 1995).