Personal finance credit evaluation method based on big data

Abstract

The invention relates to a personal finance credit evaluation method based on big data. The personal finance credit evaluation method based on the big data comprises the following steps of (a) verifying a personal mobile communication tool of an evaluation object; (b) acquiring mobile communication data of the evaluation object and social contact and economic activity data in a mobile communication channel in a specific time bucket and removing privacy data; (c) calculating space activity features and economic activity features of the evaluation object in the specific time bucket in batches by using Hadoop big data and performing structuralization and visualization treatment on the data; and (d) combining structuralized data and a credit evaluation system and calculating personal credit integrals of the object. The personal finance credit evaluation method based on the big data has the advantages that the reliability of personal finance credit evaluation is improved; and the cost of finance credit evaluation is reduced, and micro-credit finance services can be provided for individuals.

Description

【Technical field】 [0001] The invention relates to the technical field of Internet financial credit, in particular, a method for evaluating personal financial credit based on big data. 【Background technique】 [0002] At present, with the development of my country's financial industry, the coverage of financial services is gradually expanding. For users who have borrowed money in banks or applied for personal credit cards in commercial banks, the central bank has saved their credit records, such as loan amount, frequency, whether they are repaid on time, and credit card consumption overdraft repayment, etc. Commercial banks can call out credit records for a fee, but for financial service objects who have not applied for credit cards and have no loan records, their relevant credit information is lacking. With the development of the financial industry, especially the rapid popularization of Internet finance, how to grant credit to groups without credit records has become a majo...

AI Technical Summary

Problems solved by technology

[0005] In the actual operation process, the above method has the following defects: 1. The customer may falsify the information submitted to the financial service institution, and it is difficult for the financial service provider to determine its authenticity; 2. After the customer enjoys the financial service, the relevant property, etc. Risk of sale and transfer; 3. On-site inspection of the authenticity and repayment ability of financial service objects, the accuracy is higher than that of simple personal data submission, but it requires very high manpower and communication costs, and complicated verification procedures may make customers Abandoning cooperation and on-site inspections due to too many troubles will also be restricted by space. Financial service providers cannot conduct on-site inspections of customers who are far away in space, which limits the scope of services of financial service institutions.

Specifically, it includes: financial industry practitioners usually have a relatively high time cost, and the cost of on-site inspections is relatively high

Microfinance and Internet financial institutions, such as p2p online lending companies, whose main business is small-amount financial services, have meager profits on a single loan and cannot afford the cost of on-site inspections. Moreover, on-site inspections cannot guarantee the absolute authenticity of information

On-site credit inspection will also increase the burden on customers, and customers of microfinance loans may not be able to accept this extra time and energy expenditure

More importantly, Internet financial service organizations serve customers all over the country, so it is impossible to go to all parts of the country to investigate the credit evaluation of service customers; 4. Too simple and not scientific enough

The number of times a customer’s credit record is inquired mainly reflects the urgency of the customer’s demand for funds and the number of attempts. It does not necessarily mean that the customer’s qualifications are poor. Although some other customers are trying financial services for the first time (without the experience of being inquired about credit records) , but their own qualifications may not meet the requirements of the financial service institution

Simply judging the quality of customers based on the number of credit inquiries may miss high-quality customers and accept low-quality customers