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.
|Publication status||Published - 2018|
|Event||9th Australasian Actuarial Education and Research Symposium: Actuarial Science and Data Analytics - Macquarie University City Campus, Sydney, Australia|
Duration: 5 Dec 2018 → 6 Dec 2018
|Conference||9th Australasian Actuarial Education and Research Symposium|
|Period||5/12/18 → 6/12/18|
|Other||First hosted in 2008 at Macquarie University, AAERS is a key actuarial conference in Australia bringing together researchers, practitioners, teachers and students engaged in actuarial science, with an emphasis on topical and important developments shaping the future of the profession.|
The theme for this year’s event is Actuarial Science and Data Analytics reflecting that the analysis of big data sets is an increasingly important tool for actuaries practising in both traditional and non-traditional areas.
A key objective of the symposium is to explore and strengthen links between actuarial science and data analytics following the formal introduction of data analytics to the actuarial education program in Australia. This also supports the proposal by the Actuaries Institute for a new syllabus including Core Data and Statistical Analysis in future Part II and Part III course structures.