An internet financial user loan overdue prediction method based on big data

Abstract

The invention requests to protect an Internet financial user loan overdue prediction method based on big data, which comprises the following steps: 101 preprocessing data according to user behavior, user basic information and credit scoring data preprocessing operations; 102 dividing the data according to a 70-fold cross-validation method; 103 extending the training set according to the countermeasure network; 104 carrying out feature engineering construction operation according to user behavior, user basic information and credit scoring data; 105, establishing four machine learn models, and carrying out that linear regression model fusion operation; 106 predicting whether that user is in breach of contract according to the manual threshold rule set according to the basic information of the user by the established model base. The invention utilizes big data to realize the transformation of the Internet financial risk organization from the traditional 'after-action interception' means to 'pre-identification' to identify high-default users.

Description

technical field [0001] The invention belongs to the technical fields of machine learning, big data processing, deep learning, and artificial intelligence, in particular, a data division method, data expansion, feature construction, model design, artificial rules, etc. of Internet financial user loan overdue prediction data. Background technique [0002] With the rapid development of the Internet, as more and more real economies carry out "Internet +" and the vigorous development of the original Internet industry, a large amount of funds and businesses are realized on the basis of the Internet, and the technology to ensure the flow of these funds and businesses is also As it matures day by day, lending, which is one of the normal financial needs, naturally appears in the network economy. Difficulties of traditional banks: The traditional banking system has been unable to fully solve the needs and difficulties of residents in the field of lending. In 2015, the transaction scal...

AI Technical Summary

Problems solved by technology

[0004] At present, the risk prediction of defaulting users in China adopts the form of manual approval operation, which is inefficient and faces a great risk of default. It is impossible to carry out risk classification management, which affects the ability and flexibility of risk control.

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