Risk assessment method and device, computer equipment and storage medium

Abstract

The invention relates to a risk assessment method and device, computer equipment and a storage medium. The method comprises the steps of obtaining current position information of a to-be-evaluated user, and determining a regional grid and a density clustering grid which take the current position information as a center; acquiring historical user behavior tracks associated with the regional grids and the density clustering grids; and determining a risk assessment result of the to-be-assessed user based on the historical user behavior track associated with the regional grid and the density clustering grid and the risk level data. According to the historical user behavior track and risk level data of the regional grid and the density clustering grid near the position of the user, the active area of the gang fraudulent user is accurately identified, the hidden fraudulent gang is found, and the associated risk case is quickly identified, so that the risk assessment result of the user is obtained, and the identification effect is better.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular, to a risk assessment method, apparatus, computer equipment and storage medium. Background technique [0002] In recent years, the rapid development of Internet finance and the emergence of fraudulent methods have brought huge economic losses to financial enterprises and customers, seriously restricting the healthy development of the financial industry. [0003] However, the current anti-fraud management mainly adopts expert rules technically, and partly adopts traditional logistic regression algorithm for modeling. When the model obtained in this way is applied to actual risk assessment, it is insufficient in terms of control coverage and identification accuracy; Such anti-fraud management methods have poor recognition effect and high false rejection rate. SUMMARY OF THE INVENTION [0004] Based on this, it is necessary to provide a risk assessment method, appara...

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Problems solved by technology

[0003] However, the current anti-fraud management mainly adopts expert rules technically, and some models are modeled by traditional logistic regression algorithms. When the model obtained in this way is applied to actual risk assessment, it has shortcomings in terms of control coverage and recognition accuracy; Such an anti-fraud management method has poor recognition effect and high false rejection rate

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