Urgent collection method based on credit score and urgent collection device thereof

Abstract

The invention discloses an urgent collection method based on the credit score and an urgent collection device thereof. The urgent collection method comprises the steps of collecting urgent collection object credit information, processing the collected credit information, establishing a credit risk scoring model, predicting the overdue debt collection probability and performing the targeted urgent collection strategy. The risk level can be automatically judged according to the urgent collection score result so that the urgent collection strategy of the client can be reasonably determined, the urgent collection effect can be enhanced and the bad debt loss can be reduced. Data mining acts as the analysis technology so that the modeling time can be saved and the data support can be provided for the urgent collection industry. Besides, user information can also be updated in real time, the urgent collection risk score can be more accurately predicted, the most appropriate urgent collection strategy can be performed and the urgent collection task efficiency can be enhanced.

Description

Technical field [0001] The invention relates to the field of collection of financial non-performing assets, in particular to a collection method and device based on credit score. Background technique [0002] In recent years, the consumer finance, microfinance, P2P and other lending industries have continued to develop, but the domestic credit investigation system still has many defects, which has led to a high rate of overdue bad debts. The most common collection of overdue arrears often results in differences in collection effects due to different collection strategies adopted. For example, there may be more aggressive collection methods for low-risk and high-value customers due to accidental forgetting and other reasons, but no effective collection methods for high-risk and low-value customers. [0003] Existing collection methods usually have the following shortcomings: different overdue products, different credit scoring standards, lack of unified collection, maintenance, and...

AI Technical Summary

Problems solved by technology

The most common collection of overdue debts often results in differences in collection effects due to the different collection strategies adopted.

For example: It may happen that a relatively aggressive collection method is adopted for low-risk high-amount customers caused by accidental forgetting, but no effective collection method is adopted for high-risk low-amount customers

[0003] Existing collection methods usually have the following defects: different overdue products, different credit scoring standards, lack of unified collection, maintenance and analysis of data; fewer dimensions of analysis features, and a long cycle for obtaining information, which affects the accuracy of predictions

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