Business auditing method and device based on machine learning

Abstract

The embodiment of the invention provides a business auditing method and device based on machine learning, and relates to the financial technology field. The method comprises the following steps of training a random forest model by adopting the historical business audit data; enabling the random forest model to learn the auditing behavior of an auditor; then inputting the feature vector of a business applicant into each decision tree in the random forest model; and obtaining a classification result outputted by each decision tree in the random forest model, and then determining an audit result of the business request according to the classification result outputted by each decision tree in the random forest model and the weight corresponding to each decision tree in the random forest model. Compared with an expert model, the random forest model is obtained on the basis of the historical business audit data training besides the experiences of the professional audit personnel, so that the dependence on the human experience is small, the influence of the subjective factors is reduced, and the generalization ability and the universality of the audit model are improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of financial technology (Fintech), in particular to a method and device for business review based on machine learning. Background technique [0002] With the development of computer technology, more and more technical applications (such as: artificial intelligence, cloud computing, blockchain, etc.) in the financial field, the traditional financial industry is gradually transforming into financial technology (Fintech), but due to the Security and real-time requirements also put forward higher requirements for technology. In the financial industry, supply chain loans solve the financing difficulties and guarantee difficulties of upstream and downstream enterprises, and by breaking through the upstream and downstream financing bottlenecks, they can also reduce supply chain financing costs and improve the competitiveness of core enterprises and supporting enterprises. At present, the expe...

AI Technical Summary

Problems solved by technology

At present, the expert model is mainly used to review loans. After collecting the experience of business personnel who have been engaged in loan review for many years, they have been sorted out and summarized into a set of fixed business logic rules. The rule engine is deployed in the review system to realize automatic review. This method relies too much on the experience of business personnel, and the subjective factors are strong

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