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Grant: Collaborative Research and Development Grants

Queen's University

$219,167.00

Large-scale customer analytics methodologies in financial services

FY 2020-21

Summary
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.
Program
Collaborative Research and Development Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
507687-2016
Name nom
Kolsarici, Ceren
Department département
Stephen J.R. Smith School of Business, The
Organization id
29
Institution établissement
Queen's University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2016
Award amount
219167
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
141
Committee name en
University/Industry
Committee name fr
Universités/industrie
Area of application code
900
Area of application group en
Commercial services
Area of application group fr
Services commerciaux
Area of application en
Commercial services
Area of application fr
Services commerciaux
Research subject code
1601
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Operations research and management science
Research subject fr
Recherche opérationnelle et science de la gestion
Installment
inst:4 - 4
Partie
1
Nb partie
4
Application title
Large-scale customer analytics methodologies in financial services
Keyword
NSERC
Application summary
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.
Queen's University - $219,167 Grant (2020-21) | Canada Spends