Enhancing Compliance of Financial Service Industry Through Understanding and Predicting Employees’ Conduct Risk

Conduct risk management is a topic of great importance to financial service firms. Misconduct from staff members in financial institutions can result in substantial costs. However, compared to other types of risk faced by financial institutions (e.g. credit risk, market risk, liquidity risk), conduct risk and the related reputational risk have been understudied. One of the main reasons for the limited research in this area is the lack of data available assessing employees’ misconduct. The proposed project aims to address this research gap by ultimately researching and building a conduct risk model relating to staff in the financial service sector. First, the current project will develop an framework of conduct risk of financial service these employees. The conduct risk model will identify subcategories of conduct risk, and will also identify individual-level antecedents of the different subcategories of conduct risk. In the second phase of the current project, the model will be tested by using the data collected through the partner organization’s dataplatform that contains the regulatory system registration information of financial institutions’ employees (e.g. financial advisors, investment managers). In the final phase of this project, the intern and the data scientist of the partner organization will work on building

Faculty Supervisor:

Greg Sears

Student:

Yu Han

Partner:

VigilantCS

Discipline:

Business

Sector:

University:

Carleton University

Program: