Statistical machine learning methods applied to ATB data for debt collection optimization, small business lending decision modelling, and open banking initiatives

The intern will research new modelling technology to determine if the new models can make a significant improvement in servicing customers for loan approvals, debt collections, and open banking. The intern will work closely with the partner to understand the banking process and opportunity. The partner organization will receive several benefits from working with the innovative and knowledgeable intern including cross-training of techniques through collaboration, enhanced model accuracy, and enabling the partner to test new techniques. The partner regularly hires former interns to open roles based on their experience on several projects and their proven performance in completing projects efficiently and innovatively.

Faculty Supervisor:

Bei Jiang

Student:

Lisa Shulman

Partner:

ATB Financial

Discipline:

Statistics / Actuarial sciences

Sector:

Finance, insurance and business

University:

University of Alberta