Large-scale customer analytics methodologies in financial services

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The project seeks to address methodological challenges in Analytics faced by the Canadian financial industry. These challenges arise both from increasing competition from financial institutions outside Canada and from emerging competition from financial service providers in the Information Technology industry. Both sources of competition rely heavily on Analytics: the discipline of improved data-driven decision-making using sophisticated algorithms. To remain competitive, Canadian banks need not only to incorporate best Analytics practices in their operations but must become innovation leaders in financial Analytics.****The main focus of this project is on methodologies that optimize banks' relationships with their customers with the goal of increasing the lifetime value of those relationships. We will develop methods for customer behaviour analysis, price and resource optimization, large-scale stochastic risk models, as well as tools for supporting data and algorithmic infrastructure including Big Data, large-scale optimization and test-and-learn algorithms.** **We anticipate that students and postdoctoral fellows participating in this project will become highly trained researchers capable of moving into academic, governmental or industry positions and making a difference wherever they go. In particular, they will be able to lead research and development in the areas of Analytics and Big Data for the Canadian financial industry.**