INFORMATION
- Research Name Analytics Aided Case Management
- Client Softura
- Category PRACTICUM PROJECTS
- RESEARCH YEAR 2019
Project overview
The purpose of this project is to explore the machine learning capabilities on legal industry data and predict the amount of days to reach different milestones in the foreclosure process. The team was provided Softura’s data from 2014-2018, which consists of 36,000 cases, and contains many predictors such as loan type, property type, courts, and locality.
The Three Milestones are:
- Complaint Filed: Law firm initiates the foreclosure case and mails the complaint to the court. The court acknowledges the complaint and registers it.
- Service Complete: The process of delivering legal documentation to a defendant, with the defendants acknowledging the receipt of these notices.
- Judgement Entered: The court issued judgement after documents are reviewed by both the law firm and the defendants.
The algorithms used in this project are Gradient Boosting Regressor, Random forest Regressor and Artificial Neural networks
Student team
Anupama Roopaimoole, Domenic Leo, Jing Tang, Shathabdi Varma Pericherla, and Zachary Yaldo
