Hawkeye anti-fraud big data risk control evaluation system

Abstract

The invention discloses an eagle-eye anti-fraud big data risk control evaluation system, comprising original data, knowledge map, user portrait, risk control model and risk control product. The invention is characterized in that: the original data is a basic data warehouse; The knowledge map is a data governance platform; The user portrait includes a feature platform; The wind control model comprises a model platform, wherein the model platform comprises policy rules, a score card and data mining; The wind control product comprises a wind control platform. The invention solves the problem thatthe traditional wind control relies on a small amount of strong characteristic data, and the risk assessment can not be comprehensively and reasonably carried out for all users, and the erroneous killing rate is very high. Traditional risk control data processing technology is backward, and can not realize large amount of data cleaning, analysis and modeling and risk assessment in the current Internet information age; Traditional risk control policy is lack of rapid iteration and early warning mechanism, which can not quickly adjust the risk control strategy according to the market risk changes, so as to avoid the risk on-line in time.

Description

technical field [0001] The invention relates to the technical field of risk control evaluation, in particular to an eagle eye anti-fraud big data risk control evaluation system. Background technique [0002] Internet finance is developing rapidly in recent years, but the domestic credit reporting system is not perfect. As of June 2016, the central bank’s credit reporting covered 880 million people, of which only 380 million had credit data, accounting for 29% of the total population. Based on the calculation of this data, nearly 1.2 billion people in China have no credit data. However, most domestic banks or financial institutions still use traditional technology for risk control. Traditional banks and financial institutions rely on a small amount of strong characteristic data such as: personal information, income, education, work, car production, real estate, personal credit records and other information for risk pricing analysis, but most people do not have the traditional...

AI Technical Summary

Problems solved by technology

[0006] 1. Traditional risk control relies on a small amount of strong characteristic data, such as: personal information, income, education, work, car production, real estate, personal credit records and other information for risk pricing analysis, and cannot comprehensively and reasonably conduct risk assessments for all users. high rate

[0007] 2. The traditional risk control data processing technology is backward, unable to meet the current Internet information age, large data volume cleaning processing, analysis modeling and risk assessment, etc.

[0008] 3. The rapid iteration of traditional risk control policies and the lack of early warning mechanisms make it impossible to quickly provide real-time early warnings and adjust risk control strategies based on market risk changes, so as to avoid risks and reduce losses in a timely manner

[0009] To sum up, the risk control technology of traditional financial institutions is difficult to meet the risk assessment of customers' financial needs in the current Internet era. Although banks and institutions are constantly trying to iterate and update risk control technology, due to the limitations of their own state-owned enterprises , it is difficult to complete the leading and implementation of new technologies

At present, traditional risk control technology cannot accurately evaluate most Internet customers, and the evaluation data that can be relied on is limited, loopholes occur frequently, and the rapid iteration of risk control and early warning mechanisms are seriously lacking.

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