In order to optimize the administrative process of courts, the Court Administration has embarked on a project that will allow predicting the length of the expected proceedings. As reported, the Court Administration has previously worked on data analysis innovation in collaboration with the University of Latvia and Microsoft Innovation Center.
The Deputy Director of the Court Administration A. Munda emphasized: “The public sector as a whole and each public authority must be aware of technological changes and begin to evaluate machine learning and data analysis technologies in decision making, customer service and process optimization. Already since 2017, the Court Administration uses its business intelligence platform to process information from various government information systems, to provide insight into the work of courts, land registry departments and sworn bailiffs and to make quicker, data-driven decisions using the business intelligence platform MicroStrategy.”
The private sector has been using business intelligence solutions for a while now to boost its competitiveness, so it is only logical that the public sector uses these solutions to optimize the administrative processes, reduce the length of proceedings and increase the satisfaction of the public and its confidence in the justice system.
Based on the characteristics of the proceedings (scope of the claim, indictments, number of participants etc.), it will be possible to predict the duration of the pending litigation, which can be considered both by the participants in the case and the court staff.
The predictions of the duration of proceedings will not contribute contribute to reducing the average duration of proceedings, but also help the parties in planning the approximate duration of proceedings calculated by using a state-of-the- art machine learning model.
The project is implemented under the European Social Fund project “Justice for Development” and is expected to be available to the public by the end of the year.
Vjaceslavs Mitnicuks (Vjačeslavs Mitņičuks)