Fraud Detection with AI

And even the predictive risk of the exposure to financial crimes.

How AI Can Help with the Detection of Financial Crimes
Paige Dickie develops artificial intelligence (AI) and digital strategy for Canada’s banking sector at the Vector Institute for Artificial Intelligence in Toronto. She began her career in management consulting — much to the disappointment of her father, an engineer — because she had earned advanced engineering degrees in biomedical and mechanical engineering. Dickie initially worked at McKinsey, the global consulting firm, helping multinational financial institutions across a range of fields from data strategy and digital transformation to setting up innovation centers. She recently joined Vector to lead what she describes as “an exciting project with Canada’s banking industry. It’s an industry-wide, sector-wide, country-wide initiative where we have three different work streams — a consortium work stream, a regulatory work stream, and a research-based work stream.”

Knowledge@Wharton interviewed Dickie at a recent conference on artificial intelligence and machine learning in the financial industry, organized in New York City by the SWIFT Institute in collaboration with Cornell’s SC Johnson College of Business.

According to Dickie, AI can have a significant impact in data-rich domains where prediction and pattern recognition play an important role. For instance, in areas such as risk assessment and fraud detection in the banking sector, AI can identify aberrations by analyzing past behaviors. But, of course, there are also concerns around issues such as fairness, interpretability, security and privacy.

An edited transcript of the conversation follows.  ... "