Big data risk control refers to big data risk control, which refers to the use of big data to establish models for risk control and risk early warning. Big data risk control is more scientific and effective by collecting various indicators of a large number of enterprises or individuals for data modeling.

Big data refers to a collection of data that cannot be captured, managed and processed by conventional software tools within a certain time range. It is a massive, high-growth and diversified information asset, which needs a new processing mode to have stronger decision-making, insight and discovery, and process optimization ability.

Big data risk control is mainly through establishing a data risk model, screening massive data, extracting useful data for enterprises, and then analyzing and judging risks.

Extended data:

Problems that can be solved by big data risk control;

1, effectively improving the efficiency and effectiveness of the audit;

The introduction of big data risk control technology means analysis, through multi-dimensional information analysis, screening, cross-validation, summary, can form a comprehensive portrait of the applicant's data, assist the audit decision, and improve the efficiency and effectiveness of the audit. ?

2. Effectively reduce information asymmetry:

The introduction of big data risk control technology means analysis, through multi-dimensional information analysis, screening, cross-validation, summary, can form a comprehensive portrait of the applicant's data, assist the audit decision, and improve the efficiency and effectiveness of the audit. ?

3. Effective post-loan testing:

Multi-dimensional dynamic events (such as insurance risk, frequent multi-head lending, overdue addition of the same type of platform, etc.). Analysis through big data technology to achieve timely warning.

Reference source: Baidu Encyclopedia-Big Data Risk Control