Design And Implementation Of Trial Risk Management System For The Whole Process Of The Case

With the comprehensive development of our economy and society,my country’s judicial system and the operation mechanism of judicial power are also constantly improving.The trial system of people’s court has gradually become an important part of China’s socialist judicial system.The people’s court system has made important contributions to solving social conflicts at the grassroots level and promoting social governance.Due to the characteristics of court trial management such as large amount,wide area,long line and many points,there are many blind spots and loopholes in the process of trial management in the traditional trial mode.The emergence of the trial risk management system has changed this situation.However,the existing trial risk management system has problems such as single definition of risk points,simple risk screening methods,and ungraded early warning.In order to better solve these problems,the people’s courts must rely on informatization to establish more effective trial risk prevention and control measures,and strive to achieve standardization and justice in trials.This is to meet the needs of the socialist judicial system in the new era,and is of great significance to the promotion of judicial justice.Based on the existing problems of the court’s trial risk prevention and control system,this thesis builds a trial risk management system oriented to the whole process of the case,and solves the defect that risk identification and investigation in traditional judicial trials rely on manual screening or simple system judgment.The system realizes the automatic investigation of case trial risks and the intelligent push of risk early warning,which minimizes the possibility of risk occurrence and provides strong scientific and technological support for the court to establish an efficient risk prevention and control mechanism.The main functions of this system include risk point management,risk point identification and investigation,risk early warning management,risk reporting and disposal,risk statistical analysis and system management.In order to better identify the risks in each stage of the trial,two screening methods based on rules and deep learning algorithms are designed for the identification and screening of risk points,so as to realize the screening of cases in different stages of the trial.It is helpful for judges to timely discover the risks that have occurred or potential risks that may occur in the future,and effectively improve the quality of case handling.For risk cases,the system realizes case-level early warning based on the risk hazard level.The system can report and dispose of high-risk or high-public opinion risk cases,which effectively improves the timeliness of risk disposal.This system uses the Spring MVC framework for research and development,adopts the B/S structure design and implementation,and the front-end framework uses Bootstrap for research and development.The rule-based risk identification and troubleshooting tasks are designed and implemented in Java.The identification and investigation of risk points based on deep learning is implemented using Python.This thesis focuses on the design and implementation of the extraction of key technical case elements based on the inconsistency between the judgment document and the basic information of the case based on the irregular risk point.The system designed and developed in this thesis is an important guarantee for timely discovery of risks in the trial process and emergency measures,and plays an important role in risk prevention and control in the judicial process.It will help to improve the intelligent service level of the court,enhance the society’s trust in the judicial system,and play an important role in the process of national legal system construction.