A business risk assessment method, device and computer-readable storage medium

Abstract

The invention discloses a business risk assessment method, device and computer-readable storage medium, which are used to dynamically adjust the risk assessment result according to the real-time status and behavior of the user, and improve the timeliness and accuracy of the risk assessment result. A business risk assessment method, comprising: when receiving a risk assessment request submitted by a business system, obtaining business environment status data, the business environment status data including real-time business environment status data and historical business environment status data; Preprocessing the data; determining the optimal risk control strategy that maximizes the cumulative return parameter according to the preprocessed business environment state data and the current business return function; evaluating the optimal risk control strategy based on the business environment state data and the optimal risk control strategy The current user's risk level.

Description

technical field [0001] The present invention relates to the technical field of data mining, in particular to a business risk assessment method, device and computer-readable storage medium. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] Internet finance refers to an emerging financial model that uses Internet technology and mobile communication technology to realize financial integration, payment and information intermediary services. Data generation, data mining, data security and search engine technology are the strong support for Internet finance. Social networks, e-commerce, third-party payment, search engines, etc. have formed a huge amount of data, cloud computing and behavior analysis theory make big data mining possible, data security technology makes privacy pr...

AI Technical Summary

Problems solved by technology

It can be seen that the existing solution has a slow processing speed and a large processing delay. For the entire network data, it can take a few hours or a few days. When the risk assessment query interface is requested, it cannot provide real-time risk assessment. result

The collected historical data is divided into the user’s performance period and observation period. The data is relatively old. This kind of offline learning based on historical data is not enough to reflect the characteristics of current user behavior, and the prediction accuracy of the model operation results is relatively low.

On the other hand, the parameter configuration of the model will not change for a long time. Generally, after such a model has been running for a year or half a year, after accumulating enough historical data and re-training the optimization model offline, it still cannot perform according to the business environment and real-time behavior of users. Dynamic and flexible configuration, adjust the strategy at any time, the timeliness of the model is poor

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