Financial data behavior screening work method through cloud platform

Abstract

The invention provides a financial data behavior screening work method through a cloud platform, and the method comprises the following steps: S1, setting a judgment interval of abnormal data after real-time query, verification and extraction, and forming standardized data in the judgment interval; and S2, performing deviation degree analysis on the standardized data, performing screening operation on the abnormal data through a screening model after analysis, and performing feature scoring on the screened abnormal data.

Description

technical field [0001] The invention relates to the field of big data analysis, in particular to a method for screening financial data behavior through a cloud platform. Background technique [0002] In the process of financial data management, due to the increase in the number of transactions, an innumerable amount of transaction history data has been formed. As for how much of the transaction history data is compliant operations or normal transaction behaviors, it is difficult for financial data managers to pass traditional inspections. The method can no longer meet the ever-changing and increasingly complex abnormal transaction behaviors in the current society. Especially in schools, government agencies or large-scale chain enterprises, the total transaction volume and transaction times are even more difficult to count. Traditional computer accumulation methods or statistical principles cannot quickly and accurately obtain transaction behaviors that include transaction ri...

AI Technical Summary

Problems solved by technology

[0002] In the process of financial data management, due to the increase in the number of transactions, an innumerable amount of transaction history data has been formed. As for how many of the transaction history data are compliant operations or normal transaction behaviors, for financial data managers, it is difficult to pass the traditional inspection. The method can no longer meet the ever-changing and increasingly complex abnormal trading behavior in the current society

Especially in schools, government agencies or large chain enterprises, the total amount of transactions and the number of transactions are even more difficult to count. Traditional computer accumulation methods or statistical principles cannot quickly and accurately obtain transaction behaviors that include transaction risks. Existing data screening The method is not accurate, and the control and inspection process of abnormal financial data is not accurate

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