Borrower-lender Information Fusion for P2P Lending: A Nonparametric Approach

Abstract

As known to us, tremendous efforts have been made to exploit information from borrower's credit for loan evaluation in P2P lending, but seldom researches have explored information from investors and borrowers. To this end, we propose an integrated loan evaluation model that exploits and fuses multi-source information from both the borrower and the investor for improving investment decisions in P2P lending. First, based on the borrower's credit, we build a kernel-based credit risk model to quantitatively evaluate each loan. Second, we build an investor composition model that exploits information from the investor's investment behavior for loan evaluation. Then, based on the above two quantitative models and correlation, we define a multi-kernel weight and develop an integrated loan assessment model that can evaluate a loan with both the return and risk. Furthermore, based on the integrated information loan evaluation model, we formalize the investment decisions in P2P lending as a portfolio optimization problem with boundary constraints to help investor make better investment decisions. To validate the proposed model, we perform extensive experiments on the realworld data from the world's largest P2P lending marketplace. Experimental results reveal that the integrated loan evaluation model can significantly enhance investment performance beyond the existing model in P2P market and other baseline models.

Credit Risk Assessment of e-Commerce Supply Chain Finance of SMEs Based on Dynamic Reward and Punishment Perspective

“…ere should be a reasonable and comprehensive index system and appropriate methods for credit evaluation. Previous scholars mainly conducted the following studies in terms of the index system building and credit evaluation methods selecting: In terms of index system building, some scholars built is suitable for the supply chain under the background of the financing of small microenterprise credit evaluation index system [2][3][4][5][6][7][8]. Different from the traditional credit rating, the establishment of a credit risk evaluation system from different perspectives in the supply chain financial environment provides new ideas for the credit rating of SMEs [9].…”

Design of a Blockchain-Based e-Portfolio Evaluation System to Assess the Education and Teaching Process

“…In the Internet era, e-Portfolio evaluation can truthfully assess the education and teaching process through information technology. This technique has broad application prospects, by virtue of several advantages: diverse evaluation subjects, emphasis on process evaluation, support to individualized development, and integration between teaching and evaluation [1][2][3][4].…”

Research on Default Prediction for Credit Card Users Based on XGBoost-LSTM Model

“…With the widespread application of artificial intelligence technology, scholars are increasingly applying machines to research on default prediction [2][3][4][5][6][7][8]. Butaru et al [9] collected customer credit card data from multiple banks.…”