Allan started his career as a uniform police officer with the Royal Canadian Mounted Police before moving into the RCMP’s Commercial Crime section. He then ventured into the world of forensic auditing at Deloitte where he acquired considerable international experience, having led assignments across Germany, UK, Mexico, and India.
Transitioning from a global firm like Deloitte, to a federal crown corporation like the Canadian Air Transport Security Authority (CATSA) was a significant shift in his career. At Deloitte, he managed complex fraud and forensic engagements for domestic and international clients and this experience allowed him to effectively navigate CATSA’s multi-faceted and large-scale operations as Chief Audit Executive. Here, he applied his forensic expertise and leadership abilities to CATSA’s unique context. It was at CATSA that he began his journey as a data science graduate student.
An opportunity to blend his newfound data science knowledge with his established career in auditing and risk management arose with the Ontario Lottery and Gaming Corporation (OLG). The role was not just a shift in organizations, but a shift in focus towards a more data-centered approach. At OLG, as Director of Fraud Risk Management, he designed predictive analytics tools to measure risk and detect fraud, marking his first practical venture into the intersection of data science and auditing.
In his current role, Allan serves as the Chief Audit Executive of the Canada Post Group of Companies. In this role he has audit responsibility for a $9B organization of 70,000 employees that operates the largest retail network in Canada with over 6000 locations and a fleet of more than 13,000 vehicles.
He has degrees in Finance and Economics from the University of Ottawa. He is a CPA and CIA and has a master’s Science degree in Predictive Analytics from Northwestern University.
With over 35 years work experience, he is also an active contributor to thought leadership in his field, with published articles and conference presentations in auditing, fraud investigation and data science focusing on relevant topics such as Bias in AI and Auditing Machine Learning Models.