To Catch a Thief: What We Can Learn From Online Dating

As I woke on a recent morning, the first thing I heard on the radio was a story about Florian Homm, a flamboyant German financier who had been on the run for five years for allegedly stealing over $200M from his Absolute Capital Hedge Fund.

Mr. Homm was arrested in a sting operation at none other than the Uffizi Gallery in Florence. While the story was fascinating on its own merits, I found it more so because I know Florian. We worked together at Fidelity Investments years ago when he assisted me on the mutual fund I was managing at the time.

Florian’s story made me consider whether he had the same tendencies and desires in the late 1980’s as he had in later years when, according to the SEC, he defrauded clients and violated numerous SEC regulations. And, if that were true: Was it possible for managers to identify those behaviors or characteristics that might morph over time into illicit and immoral behavior? Every few months, we seem to hear about another con-man (very few women in this profession) who has been apprehended. For every one who is caught, how many remain undetected?

Florian left Fidelity long before he developed his alleged scheme or his extravagant lifestyle –the luxury homes in multiple countries, airplanes, and household staff galore – which, along with his imposing 6’6″ frame and double Harvard degrees, pro-basketball credentials in the German league, helped lure wealthy clients. During the time we worked together, he was self-confident, intelligent, determined and ambitious, all qualities I could recognize in the vast majority of young research analysts hired at Fidelity Investments or almost any other financial service institution today. In fact, one could say that we expect strong academic credentials, some aggressiveness, and self-confidence bordering on arrogance from all MBA candidates in order to succeed in

today’s competitive environment, regardless of the pursuit. Therefore, no particular warning went up or should have, in Florian’s case.

If all the young driven interns share the same discernible characteristics, how can we possibly single out the young Bernie Madoff? Enter online dating. Although I have never used such a service myself (don’t worry, honey), I have talked to friends about how one builds a profile through responding to a lengthy questionnaire detailing likes/dislikes, values, habits and style. Even if the answers are not totally honest, the profile paints a helpful picture to possible matches. Match.com has close to twenty years of data and by cross referencing marriage notices sent to them by clients, from Facebook and traditional media, software engineers can determine, with some statistical precision, those combined traits that resulted in successful pairings among its clients — Assuming we define marriage as the ultimate goal of online dating!

The same analysis of historic databases might work to identify future con-artists. Predictive models power consumer web-based service providers, such as Netflix, iTunes, and Amazon, which suggest songs, books, and movies for you, based on your past selections. Many Fortune 500 and large investment companies use assessment tests, such as TriMetrix to measure the performance and personal competencies, values, and stress levels to help decide whether the applicant would be a fit for the firm and in what capacity. Over 80 factors are scored to match the candidate with the needs of the job and weed out those whose qualities would be either inappropriate or insufficient.

As with online dating, over 20 years of data is available for data miners to evaluate. If online dating services can determine which profiles are most likely to marry, these personality tests when cross referenced against criminal indictments, arrests and convictions, must be able to tell us something useful about the mindset of future scoundrels. Like users searching for the perfect date, companies may well be missing crucial clues that could be predictors of rogue behavior. If Match.com can find me my true love, can’t reams of assessment data also be used to improve the hiring process?

Back testing past assessment scores and expected job competence against actual performance is a useful implement that could fine tune the hiring process. However, it is important to acknowledge that this tool is only one element of the screening process, that it is still necessary to avoid impulsive judgment that could negatively impact lives, and to apply a respectful approach to privacy and individual uniqueness.

Beyond looking for ways to better screen applicants and employees, companies need internal safeguards such as limiting access to assets of the firm or clients, building the best possible security around accounting systems, and controlling the extent of discretion and authority given to inexperienced employees, especially when tempted by large personal gain. Most important is human oversight, supervision, and guidance.

The good news is that it’s very difficult to pull off a large scale Ponzi scheme, requiring years of careful planning, as well as the gravitas and charisma needed to lure unsuspecting clients. Although criminals seem to find ways to breach the rules and systems set up to stop them, we should continue to consider novel ways to prevent predatory practices, utilizing all the available data already being collected.