2. Insufficient backup data. The SEC will seek to verify that you have maintained adequate backup data to support your HBP claims.
3. Cherry-picking time periods. Many firms violate the SEC marketing rules when they cherry-pick a specific time period that makes their HBP look better.
4. Misleading disclosures. Hidden or confusing HBP disclosure will draw the SEC’s enforcement interest.
5. Retrospective model changes. Firms can’t keep tinkering with their models to improve the HBP results.
6. Using incorrect historical market inputs. The SEC can verify market data from past time periods, so make sure to use the correct numbers.
7. Applying different models. The SEC has raised red flags when HBP differs significantly from audited or live performance information applying the same models.
8. Using the wrong model rules. Firms have gone astray by applying different model rules to the back-tested data they use to manage real accounts.
9. Investments didn’t exist. The SEC will call out HBP that includes investments that were not available at the time.
10. Faulty algorithm. Faulty programming can result in inflated performance numbers.
Hortz: What do you consider the key Risks for fund boards?
Bruce: Thinking that AI funds can be governed the same as quant funds. AI requires an understanding of a different set of complexities which can cause the computer to come up with the wrong answer. A famous example is an AI that was built to distinguish a dog from a wolf. It was provided a set of training images and was then able to very accurately identify the difference. Only when different photos were tested did it start to fail. The researchers realized that the AI was choosing “wolf” if it there was snow in the background since all the training photos of wolves were in snow. Boards need to be sure that the investing AI is not finding snow.