Investment Recommendation System for Low-Liquidity Online Peer to Peer Lending (P2PL) Marketplaces

Abstract

Online P2PL systems allow lending and borrowing between peers without the need for intermediaries such as banks. Convenience and high rate of returns have made P2PL systems very popular. Recommendation systems have been developed to help lenders make wise investment decisions, lowering the chances of overall default. However, P2PL marketplace suffers from low financial liquidity, i.e., loans of different grades are not always available for investment. Moreover, P2PL investments are long term (usually a few years), hence, incorrect investment cannot be liquidated easily. Overall, the state-of-the-art recommendation systems do not account for the low market liquidity and hence, can lead to unwise investment decisions. In this paper we remedy this shortcoming by building a recommendation framework that builds an investment portfolio, which results in the highest return and the lowest risk along with a statistical measure of the number of days required for the amount to be completely funded. Our recommendation system predicts the grade and number of loans that will appear in the future when constructing the investment portfolio. Experimental results show that our recommendation engine outperforms the current state-of-the-art techniques. Our recommendation system can increase the probability of achieving the highest return with the lowest risk by ~ 69%.

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