Personal data is increasingly conceived as a tradable asset Markets for personal information are emerging and new ways of valuating individuals’ data are being proposed At the same time, legal obligations over protection of personal data and individuals’ concerns over its privacy persist This article outlines some of the economic, technical, social, and ethical issues associated with personal data markets, focusing on the privacy challenges they raise

The Challenges of Personal Data Markets and Privacy

The term online peer-to-peer lending (P2P) describes the loan origination process between private individuals on online platforms were financial institutions operate only as intermediates required by law Initialized by groups in online social networks, first commercial online P2P lending platforms started in 2005 Thus online P2P lending is a relatively young research field This paper gives a brief overview of the P2P lending market and reviews the research on the determinants of P2P lending We distinguish between financial and demographic characteristics of the borrower, as well as social characteristics like friends and group affiliation The reviewed literature gives insights on how the determinants affect the borrowers’ likelihood of successful funding, the final interest rate that has to be paid as well as the relationship of the borrowers’ characteristics and lending success

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Online Peer-to-Peer Lending - A Literature Review

P2P lending is an emerging Internet-based application where individuals can directly borrow money from each other. The past decade has witnessed the rapid development and prevalence of online P2P lending platforms, examples of which include Prosper, LendingClub, and Kiva. Meanwhile, extensive research has been done that mainly focuses on the studies of platform mechanisms and transaction data. In this article, we provide a comprehensive survey on the research about P2P lending, which, to the best of our knowledge, is the first focused effort in this field. Specifically, we first provide a systematic taxonomy for P2P lending by summarizing different types of mainstream platforms and comparing their working mechanisms in detail. Then, we review and organize the recent advances on P2P lending from various perspectives (e.g., economics and sociology perspective, and data-driven perspective). Finally, we propose our opinions on the prospects of P2P lending and suggest some future research directions in this field. Meanwhile, throughout this paper, some analysis on real-world data collected from Prosper and Kiva are also conducted.

P2P Lending Survey: Platforms, Recent Advances and Prospects

We analyze empirical data of Germany's largest online social lending platform Smava.de to exemplarily study the contribution of unstructured, ambiguous, or unverified information to trust building in online communities. After controlling for the influence of hard information, we find that textual statements that appeal to social behavior actually affect trust building. However, the evidence is less clear for voluntarily disclosed personal data. Lenders generally seem to give more weight to hard information so that disclosing personal data promises little benefit while potentially exposing borrowers to privacy risks.

The role of soft information in trust building: evidence from online social lending

The Web form is the primary method of collecting personal data from individuals on the Web Privacy concerns, time spent, and typing effort act as a major deterrent to completing Web forms Yet consumers regularly provide more data than required In a field experiment, we recruited 1,500 Web users to complete a form asking for ten items of identity and profile information of varying levels of sensitivity We manipulated the number of mandatory fields (none vs two) and the compensation for participation ($025 vs $050) to quantify the extent of over-disclosure, the motives behind it, and the resulting costs and privacy invasion We benchmarked the efficiency of compulsion and incentives in soliciting data against voluntary disclosure aloneWe observed a high prevalence of deliberate and unpaid over-disclosure of data Participants regularly completed more form fields than required, or provided more details than requested Through careful experimental design, we verified that participants understood that additional data disclosure was voluntary, and the information provided was considered sensitive In our experiment, we found that making some fields mandatory jeopardised voluntary disclosure for the remaining optional fields Conversely, monetary incentives for disclosing those same fields yielded positive spillover by increasing revelation ratios for other optional fields We discuss the implications for commercial website operators, regulators, privacy-enhancing browser standards, and further experimental research in privacy economics

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The Privacy Economics of Voluntary Over-disclosure in Web Forms

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 st 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.

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Rainer B

Papers

Privacy in Online Social Lending