Supervision method suitable for vehicle loan cooperation mechanism

Abstract

The invention provides a supervision method suitable for a vehicle loan cooperation mechanism. The method comprises the following steps: constructing an artificial neural network model used for realizing supervision data analysis; evaluating and optimizing the artificial neural network model; and using the artificial neural network model to manage and control the data of the car loan cooperation mechanism, wherein the features of the artificial neural network model comprise an operation risk, a core risk, a compensation risk, a process risk, a moral risk, an association risk and a business risk. The beneficial effects of the invention are that the supervision method suitable for the car loan cooperation mechanism is provided, and the method employs an artificial intelligence mode to efficiently and accurately solve the risk assessment of the cooperation mechanism.

Description

technical field [0001] This application relates to the supervision method of financial institutions, specifically, to a supervision method applicable to car loan cooperative institutions. Background technique [0002] Many aspects of financial enterprise management can apply big data technology, such as financial product research and development, customer relationship maintenance, performance evaluation, marketing, etc., but the application of risk management is still the most important. With the development of scientific and technological information and the massive growth of data, a large amount of structured and unstructured data information exists in the internal and external environment of banks, which provides a certain data basis for the application of big data technology in risk management. [0003] Cooperative institutions are defined as the business cooperation between relevant intermediary institutions and capital parties in the vehicle consumer loan financial sce...

AI Technical Summary

Problems solved by technology

[0004] In the monitoring and management of cooperative institutions by the funder in the vehicle consumption loan scenario, it is generally more common to use internal data for analysis and control, and the analysis is performed in the form of traditional report file export, but the analysis has fewer dimensions and timeliness Low and the evaluation methods are mostly based on personal experience, very subjective, and the factors considered are not comprehensive

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