Borrower Decision Aid for people-to-people lending Lauri Puro a , Jeffrey E. Teich b , Hannele Wallenius a , Jyrki Wallenius c, ⁎ a Aalto University School of Science and Technology, Department of Industrial Engineering and Management, POB 15500, FI-00076 AALTO, Finland b New Mexico State University, Management Department, New Mexico State University, Las Cruces, NM 88003, USA c Aalto University School of Economics, Department of Business Technology, POB 21210, FI-00076 AALTO, Finland abstract article info Article history: Received 14 January 2009 Received in revised form 18 December 2009 Accepted 31 December 2009 Available online 18 January 2010 Keywords: People-to-people lending Decision support Reverse auctions In setting up, and bidding in online auctions, people face difficult strategic decisions. In this study, a Borrower Decision Aid is introduced, which will help formalize the decision making process of the sellers, or borrowers in this case, in one particular P2P loan auction site, Prosper.com. The vast amount of real-life bidding data available in this online auction enables us to build new kinds of tools for decision makers. The Borrower Decision Aid helps the borrower to quantify her strategic options, such as starting interest rate, and the amount of loan requested. We identify which variables concerning the borrower are related to the probability of successfully securing a loan and the final interest rate. © 2010 Elsevier B.V. All rights reserved. 1. Introduction 1.1. Background Prosper.com is the first people-to-people lending marketplace, based on an online reverse auction. In this marketplace, people make applications for loans, called listings, and then other people make bids on these listings. The winning bidders get to fund the loan and the interest rate is determined by the auction — the more competition, the lower the interest rate. In other words, the idea is to link the person in need of money with people willing to lend money without an intermediating bank. Typically a loan is funded with many bidders (lenders), because most lenders only fund $50–$200 per each loan. Lenders bid for these small amounts across many loans to help diversify their risk. Prosper.com was launched publicly in February 2006, and has brokered so far over $150 million worth of loans [5,17,22]. In this study, we focus on the role of the borrower, i.e. the person who sets up the listing for a loan. The borrower has several important strategic decisions to make, which can later determine if she gets the loan funded or not. The purpose of this study is to provide decision support for the borrower when making these important decisions. In the literature there are only a few publications that discuss decision support in auctions (in general). [1,8,15,16,23,25] are some examples. Their angle is different from ours, though. Our study has significant practical importance. Currently, bor- rowers set their listing parameters based on insufficient data, such as the average interest rate. In this study, we introduce a framework to analyze the borrower's strategic decisions in terms of success probabilities and estimated final interest rates. A Borrower Decision Aid (BDA) is described, which enables the borrower to evaluate her strategic options quantitatively. This is a significant practical improvement to the current situation where Prosper.com only provides scant advice on the starting rate and no advice on the amount of the loan. In addition to being practically important, our study is interesting in a theoretical sense as well. Namely, the framework and the methods used in constructing the tool are interesting and could be used with other online auction sites. 1.2. Objectives of the research The main objective of this study is to develop a decision support tool for the borrowers. This tool helps the borrowers evaluate their strategic options in quantitative terms. In more detail, we 1. identify the most important factors that affect the outcome of the auction, that is borrower's chances of getting the loan funded; 2. identify the most important decision variables that the borrower can change in order to influence the outcome of the auction; and 3. develop a framework and methods to compare different strategic options in quantitative terms. We look at all the information available and compare it to empirical data on Prosper.com listings. The identified factors are then divided into those which the borrower can influence and those that are part of the credit report. Both types of variables are needed in this study, but naturally the ones that the borrower can influence are the ones we provide advice on. We examine different methods of Decision Support Systems 49 (2010) 52–60 ⁎ Corresponding author. E-mail address: Jyrki.Wallenius@hse.fi (J. Wallenius). 0167-9236/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.dss.2009.12.009 Contents lists available at ScienceDirect Decision Support Systems journal homepage: www.elsevier.com/locate/dss