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- W3200709621 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." @default.
- W3200709621 created "2021-09-27" @default.
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- W3200709621 date "2022-01-01" @default.
- W3200709621 modified "2023-09-29" @default.
- W3200709621 title "Information matching model and multi-angle tracking algorithm for loan loss-linking customers based on the family mobile social-contact big data network" @default.
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- W3200709621 doi "https://doi.org/10.1016/j.ipm.2021.102742" @default.
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