Forecasting for Default Recovery

The proposed project aims to harness the power of Artificial Intelligence (AI) and machine learning to develop a predictive model that assists in predicting delinquency in financial contexts. By integrating AI and predictive modelling approaches, the project seeks to enhance the accuracy, efficiency, and interpretability of delinquency predictions within the residential mortgages space. The focus will be on creating robust predictive models using advanced ML and AI techniques, including gradient boosting machines like XGBoost, survival analysis models for time-to-event predictions, and stochastic processes to model transitions between delinquency categories.

Faculty Supervisor:

Gerhard Trippen

Student:

Partner:

Home Trust Co.

Discipline:

Business

Sector:

Finance and Insurance

University:

University of Toronto

Program: