Financial information processing method and system

Abstract

The invention provides a financial information processing method. The financial information processing method comprises steps that the financial data is acquired and stored, and the acquired financial data is extracted; the acquired financial data is pre-processed, including cleansing, association and classification; the pre-processed financial data is processed, including desensitization protection, grading processing and packaging storage, risk analysis on the financial data respectively after pre-processing and after processing is carried out; a risk analysis result is outputted and displayed. The invention further provides a financial information processing system. Through the method and the system, repayment capability, repayment willingness and post-loan risk of a loan user can be accurately determined.

Description

technical field [0001] The invention relates to the field of Internet financial big data, in particular to a financial information processing method and system. Background technique [0002] With the popularization of Internet technology, more and more enterprises and individuals start their own businesses through loans to realize the value of life. The institutions that lend money are basically professional financial institutions. What financial institutions hope is that more and more people will take out loans. With the increase in the number and types of loans, these loan data will become huge and complicated big data, which requires effective Proper management of these data will not cause financial institutions to fall into chaos, thereby avoiding unnecessary economic losses. [0003] The following disadvantages exist in the existing financial post-loan risk management: [0004] (1) Most of the human experience is required, and many managers lack experience [0005] T...

AI Technical Summary

Problems solved by technology

[0005] There are still many fresh graduates in the team of customer managers who lack work experience, and it is difficult to judge which customers have repayment risks; while some of the experienced old credit managers are in risk identification, information feedback, and risk disposal capabilities. Slightly insufficient

Most customer managers judge the situation of risky customers based on experience, and it is difficult to make a correct judgment on the risks they will encounter

[0006] (2) Low management efficiency

The basis for judging user risk is slightly less, the dimensions are not rich enough, and the support of external data is lacking, so it is impossible to more comprehensively portray the portrait of loan users

[0010] Due to the above factors, the managers' judgment on the repayment ability and willingness of loan users is not accurate enough, and it is difficult to detect the risk increase after the loan, which makes it difficult for many loans to be recovered

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