Information matching model and multi-angle tracking algorithm for loan loss-linking customers based on the family mobile social-contact big data network

Abstract

This article focuses on the tracking problem of loan loss-linking customers based on the family mobile social-contact big data network. By defining suspected loan loss-linking customer and family member intimacy, a mobile social-contact big data network of the loan loss-linking customers’ family members is constructed, and similarity of mobile phone usage habits, contact similarity, and contact point similarity in the mobile social-contact big data network are defined and studied accordingly. Then, the similarity matching degrees of mobile phone usage habits, contact locations, and contacts between suspected loan loss-linking customers and loan loss-linking customers are analyzed from the perspective of similarity. This establishes an information matching model of loan loss-linking customers, and proposes the multi-angle tracking algorithm of loan loss-linking customers, allowing information matching and multi-angle tracking for loan loss-linking customers, and applies the model and the algorithm to the loan data of a bank in China. The empirical results show that the proposed model and algorithm can track loan loss-linking customers, and the algorithm exhibits rapid convergence. This study has important significance and practical value for financial institutions to track loan loss-linking customers and recover funds.