The Financial Consequence of Integrity: Using Automated Fraud Detection for Investment

This paper investigates the financial consequence of integrity. We study how portfolio performance is affected by avoiding investing in companies that are more likely to have committed financial statement fraud. Using a fraud detection model built using data analytics, companies are ranked according to a score indicating their likelihood of being fraudulent. Two investment strategies are then formed. The first invests in companies with low fraud scores whereas the other invests in those with high scores. We find that investment performance can be improved, with higher returns and lower risk, by investing in companies less likely to have committed fraud in preference to those more likely. This suggests that the price of integrity is not high. Portfolio performance was not be financially damaged by excluding companies likely to have committed financial statement fraud and, in fact, benefited from doing so.