Retirement risk assessment system and retirement risk assessment method

Abstract

With existing technologies, factors such as differences in work styles could lead to misjudgments, resulting in a low turnover risk even when there was a high risk, making it impossible to assess turnover risk with adequate accuracy. [Solution] In cases where there are differences in work style, such as "part-time employees," "recruiters," or "editors of employment regulations," and existing technologies for determining employee turnover risk may be insufficient to address these factors, a reassessment of employee turnover risk will be performed for those employees.

Claims

1. A retirement risk determination system comprising a data collection device for collecting data on employees and a determination device for determining the employee's retirement risk, The data acquisition device is The system acquires the employee's operation history data from the virtual PC used by the employee for work, and further acquires personal data about the employee, and provides each of these to the determination device. The retirement risk determination system is characterized in that the determination device performs retirement risk determination by executing machine learning of a retirement risk determination model using the operation history data, determines work styles that may affect the result of the retirement risk determination as exceptions, and re-evaluates the result of the retirement risk determination with a different weighting for employees whose work styles fall under the exceptions listed based on the personal data.

2. The retirement risk determination system according to claim 1, characterized in that the determination device acquires data from the personal data that may affect the result of the retirement risk determination, specifically data on the employee's work style, the employee's department, or the employee's assigned duties.

3. The data acquisition device, The employee's operation history data is obtained from the virtual PC used by the employee for work, and further, personal data about the employee is obtained. The risk assessment device, A method for determining employee turnover risk, characterized by performing machine learning on a turnover risk determination model using the aforementioned operation history data to determine turnover risk, identifying work styles that may affect the result of the turnover risk determination as exceptions, and re-determining the turnover risk determination result for employees whose work styles fall under the exceptions listed based on the personal data, by changing the weighting.

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