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Employee operation risk prediction method based on logistic regression

A logistic regression and risk prediction technology, applied in the field of employee operational risk prediction based on logistic regression, to reduce losses, reduce labor costs, and avoid distraction

Active Publication Date: 2021-02-26
泸州银行股份有限公司 +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention aims to provide a method for predicting employee operational risk based on logistic regression to solve the above-mentioned problems of manual investigation and supervision of employee operational risk

Method used

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  • Employee operation risk prediction method based on logistic regression
  • Employee operation risk prediction method based on logistic regression
  • Employee operation risk prediction method based on logistic regression

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Experimental program
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Embodiment

[0046] Such as figure 1 As shown, this embodiment proposes a method for predicting employee operational risks based on logistic regression, including the following steps:

[0047] S1, collect operational risk point list data and employee information data;

[0048] The employee information data includes personal information data and work behavior data. The main system sources of data collection include operational risk system, OA system, and various business systems, such as: financial management system, counter system, credit system, etc. The collected data As the basis for subsequent analysis, it helps to improve the prediction accuracy. In this embodiment, the employee information data includes the following collection ranges:

[0049] a. Basic information, including: gender, age, education level, department, position, number of times of leave, length of leave, length of time off, etc.;

[0050] b. Work information, including: work content, work behavior: login in each sy...

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Abstract

The invention provides an employee operation risk prediction method based on logistic regression. The employee operation risk prediction method comprises the steps of S1, collecting operation risk point list data and employee information data; S2, classifying risk points in the operation risk point list data; S3, extracting operation risk events and employee information data of various risk pointsto form an operation risk data set; S4, labeling the staff according to the occurrence condition of the operation risk event; S5, performing data preprocessing on employee information data in each type of risk point operation risk data set; S6, based on employee tags, establishing a logistic regression model for each type of risk points; S7, training a corresponding logistic regression model by using employee information data in each type of risk point operation risk data set after data preprocessing; and S8, the trained logistic regression model being utilized to calculate the probability ofoccurrence of various operation risk events of the employees. According to the invention, employee information data is collected, employee behaviors are monitored, manual on-site inspection is not needed, and the labor cost is reduced.

Description

technical field [0001] The invention relates to the field of prevention and control of operational risk in financial institutions and banking industry, in particular to a method for predicting employee operational risk based on logistic regression. Background technique [0002] At present, financial institutions and the banking industry's investigation of employees' operational risk behaviors is mostly limited to manual investigation and supervision, which requires a lot of manpower and material resources. The scope of investigation and supervision is often limited to individual departments or branches, and cannot cover the entire institution or bank. There are drawbacks in the bank's internal control mechanism and supervisory mechanism. The management and control of operational risk emphasizes post-event investigation rather than pre-prevention. Many incidents are investigated in detail after the risk occurs, ignoring the early prevention work, making the institution miss t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/04G06N20/00G06Q40/02
CPCG06Q10/0635G06Q10/04G06N20/00G06Q40/02
Inventor 向阳李锦松颜科琦陈继春黄文邬小峰岳雨蒂程云黄奕乐张欣华崔文军李威曾浩王承林
Owner 泸州银行股份有限公司
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