Post-loan risk monitoring method, device, equipment and computer readable storage medium

Abstract

The invention relates to the technical field of financial science and technology, and discloses a post-loan risk monitoring method, a device, equipment and a computer readable storage medium. The post-loan risk monitoring method comprises the steps of obtaining first attribute data of a to-be-monitored enterprise; constructing a first feature vector according to the first attribute data, and inputting the first feature vector into a pre-trained risk scoring model to obtain a first risk score of the to-be-monitored enterprise; and inputting the first attribute data and the first risk score intoa pre-trained decision tree model to obtain a risk level, so as to monitor the to-be-monitored enterprise based on the risk level. According to the method, the timeliness and accuracy of post-loan risk monitoring can be improved.

Description

technical field [0001] The present invention relates to the technical field of financial technology (Fintech), in particular to a post-loan risk monitoring method, device, equipment and computer-readable storage medium. Background technique [0002] With the development of computer technology, more and more technologies are applied in the financial field, and the traditional financial industry is gradually transforming into Fintech. However, due to the security and real-time requirements of the financial industry, higher requirements are placed on technology. requirements. [0003] In the post-loan risk monitoring of enterprises, risk analysis is usually performed manually on the enterprise's risk monitoring data. However, the mode of manual analysis has certain requirements on the number of staff and professional ability, resulting in high labor costs, and the speed of manual analysis is slow and inefficient, which indirectly leads to low frequency of investigations, mostl...

AI Technical Summary

Problems solved by technology

However, the mode of manual analysis has certain requirements on the number of staff and professional ability, resulting in high labor costs, and the speed of manual analysis is slow and inefficient, which indirectly leads to low frequency of investigations, mostly once every six months or Once a year, which leads to poor timeliness of risk monitoring; in addition, due to the strong subjectivity of manual analysis, it is difficult to unify the standards, and the uniqueness of risk monitoring data is relatively single, resulting in poor accuracy of risk analysis results

Images