  In Canada, financial advisors and dealers are required by provincial
securities commissions and self-regulatory organizations--charged with direct
regulation over investment dealers and mutual fund dealers--to respectively
collect and maintain Know Your Client (KYC) information, such as their age or
risk tolerance, for investor accounts. With this information, investors, under
their advisor's guidance, make decisions on their investments which are
presumed to be beneficial to their investment goals. Our unique dataset is
provided by a financial investment dealer with over 50,000 accounts for over
23,000 clients. We use a modified behavioural finance recency, frequency,
monetary model for engineering features that quantify investor behaviours, and
machine learning clustering algorithms to find groups of investors that behave
similarly. We show that the KYC information collected does not explain client
behaviours, whereas trade and transaction frequency and volume are most
informative. We believe the results shown herein encourage financial regulators
and advisors to use more advanced metrics to better understand and predict
investor behaviours.
