Identifying SMEs’ Barriers to Electronic Payment Adoption

During the past two decades in Canada, use of electronic payment has steadily increased. However, despite the downward trend in the volume, the value of cheques has steadily increased, with the five-year average volume growth increasing by about 2% due in large part to their common presence in the business-to-business space. These trends indicate that even with emerging of EFT payment instruments and online transfer options as substitutes for cheque, there are yet some barriers to electronic payment adoption specially for small and medium businesses.

Automated Risk Identification in Modular and Offsite Construction

Modular and offsite construction, where a module of project or complete house is manufactured in a factory, requires a large upfront capital (working capital) investment in order to procure materials in advance of manufacturing and to deliver modules on time and on schedule. Thus, modular fabricators need to receive deposit and progress payment before the assembly process. In the eyes of a bank, a prefab house is “just materials”.

Development of Persona Models for Banking Customers

In this research we will identify current types of customer, taking into account people who prefer to use a variety of platforms and different preferences in terms of how actively they manage their money. . We will carry out focus groups and interpret the results of a survey in terms of their implications for a set of factors that differentiate between banking customers. Using the factor scores obtained in a survey we will segment into meaningful groups (personas).

GIS-based Wildfire Catastrophic Risk Economic Capital Modelling

Models used for Wildfire catastrophe insurance as of today are not considering substantial information, such as geographic information and environmental constraints. The objective of the project is to establish a theoretical framework and an empirical process to enhance Aviva Canada’s current Wildfire Economic Capital (EC) model, to be able to determine the amount of capital needed to be allocated to ensure the company remains solvent, in case of occurrence of risks.

Global Dynamic Financial CGE Model

This project aims to develop a dynamic financial computable general equilibrium model (CGE) with interaction between real and financial side of the world economy. It seeks to understand how monetary policy changes such as interest rate changes, QE measures, and exchange rate changes affect the real economy by applying the financial dynamic CGE model. This project collaborates with the partner organization--the Infinite-Sum Modeling Inc.—to build a CGE-FDI database and to develop the financial CGE model. 

Business Data Analytics: Warranties, Recommendations, and Fleet Management

Using mathematical models we draw verifiable conclusions from a rental-fleet dataset. These conclusions help rental-fleet operators increase revenue, decrease cost, or improve other aspects of their business. We not only identify what models to build, but also implement them using rental-fleet data. Some example questions that we help rental-fleet operations answer are: 1) what warranties should they offer to their customers or purchase for their equipment? 2) what actions should the rental-fleet operator take to improve its performance in self-identified areas?

Optimization of Savings and Retirement for Canadians

There are numerous financial goals that most Canadians face. Retirement, funding post high school education, managing debt, purchasing appropriate amounts of insurance and saving for lump sum purchases. Each of these goals has various accounts and savings vehicles associated with them. The research projects we are proposing will help Canadians define their own financial situation, focus on their goals in the optimal order, and best utilize savings vehicles and government benefits to best meet their goals. Glencairn Financial Inc.

Assessing the Impact of Customer Service Strategies on Loyalty

This project evaluates the impact of customer service on customer retention and churn. In the first phase, we build a statistical model to examine drivers of customer loyalty. In the second phase, we work with customer service to evaluate the effectiveness of new customer service strategies. This project will enable the company to better predict customer retention and churn by using appropriate metrics. In addition, the company can understand the impact of alternative customer service strategies on customer loyalty and can choose the most effective one for implementation.

Assessing statistical bias in credit markets, an application to SMEs

This research project aims to evaluate whether members of minority groups or women face higher barriers to access credit in the small and medium-sized enterprises credit market. The intern will analyze loan-level data provided by the business partner to evaluate whether these biases are detectable in the portfolio of SME loans of the business partner. Discrimination in credit allocation prevents efficient credit allocation, besides being demeaning for the individual subject to discrimination.

Time series clustering and classification

Financial indicators of an individual firm may be in the form of time series, vectors, or even richer data, such as text or images. The purpose of this work is to explore and develop methods for dealing with such data, and in particular perform the clustering/classification of such data into similar groups. In the project the intern will develop the tools that will allow to determine whether a client should be issued a loan or not.

Pages