Information problems and their solutions in peer-to-peer lending

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School of Business | Bachelor's thesis
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Date

2025

Department

Taloustieteen laitos

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Mcode

Degree programme

Taloustiede

Language

en

Pages

27 + 4

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Abstract

The aim of this literature review is to study information problems in online markets and investigate to what degree they can be reduced. The online market setting used throughout this thesis is online P2P lending, an online platform for small unsecured P2P loans. I start with a brief overview of P2P lending, its emergence, and the basic function of the platforms. I briefly present the theory of asymmetric information by Akerlof (1970), Rothschild and Stiglitz (1976), and Stiglitz and Weiss (1981). When it comes to mechanisms of reducing them, my focus is on soft information, which contrasts with the traditional sole dependence on hard information. I present empirical works that utilized data from one of the biggest P2P lending sites, Prosper. Their focus is on testing how well soft information, for instance social network information, can reduce the information problems. I find that soft information is valuable, but its applicability produces mixed results. Finally, I discuss the role of big data and machine learning as a new, more applicable avenue for utilizing soft information. They seem to promise good results but need future empirical research.

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Thesis advisor

Huttunen, Kristiina

Keywords

P2P lending, information asymmetry, soft information, social networks

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https://urn.fi/URN:NBN:fi:aalto-202510268581

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[kand] Kauppakorkeakoulu / BIZ