Bidirectional matching recommendation method of loan project and lender in network petty loan

Abstract

The invention discloses a bidirectional matching recommendation method of a loan project and a lender in a network petty loan. In the method, a random walking network in which two different recommendation methods are integrated into one body is adopted. On an aspect of the lender, in order to increase a project recommendation accuracy and an effect, an output result of the random walking network is taken as an input of an optimization model which considers a risk and an income, and the optimization model screens a loan project combination at second time. By using the method, a user experience of a network petty loan platform can be improved and efficiency is increased.

Description

technical field [0001] The invention relates to a recommendation system algorithm and the application field of Internet finance, in particular to a two-way matching recommendation method between a borrowing item and a lender in an online micro-loan. Background technique [0002] Online micro-credit is a new type of loan, which usually occurs on a person-to-person (Peer-to-peer, P2P) lending platform. Online microfinance also refers to P2P loans, and the two represent the same concept. Since all service processes in P2P loans are completed online, the operating cost of P2P platforms is lower than that of traditional financial institutions. At the same time, borrowers can raise money at lower interest rates, and lenders can also obtain higher returns. . In recent years, P2P lending platforms have developed rapidly at home and abroad. Representative foreign platforms include Prosper, LendingClub, etc., while domestic platforms include Renrendai and Hongling Venture Capital. ...

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