The New York Times recently reported that the misapplication of risk models by Financial Engineers, or Quants is the biggest failure accounting for the current financial crisis. “The technology got ahead of our ability to use it in responsible ways”, said Professor Andrew W. Lo, MIT faculty appointments in both Economics and Finance.
The Human failures noted include:
a) Credit Default swaps – “Quants” traditionally did not estimate major risks such as complexity, transparency, liquidity, and leverage
b) Models failed to accurately assess mortgage loan risks. Underwriting systems were largely automated, and systematically missed the massive number of defaults. One University of Chicago study suggested that from 1997-2006, quantitative models systematically underestimated defaults for subprime borrowers.
c) Incentives directed attention away from scrutinizing creditworthiness; when markets were booming, pay was based on trading more sophisticated securities, with more debt on bigger bets.
Industrial/Organizational Psychology to the Rescue?
While Industrial/Organizational Psychologists have had useful models to mitigate some of these risks for decades, traditionally they’re only known to specialists in this nitch profession. Also quantitatively trained in stochastic models of human behavior at work, there are a number of systematic ways Financial Engineers can improve upon their models and make better decisions:
1) Just as traditional “Quant” models miss important financial variables (e.g. Leverage, Complexity, Transparency), they also miss important human drivers of financial outcome variability, including mortgage loan risks. Over 50 years of science on human personality traits has consistently shown that conscientiousness predicts many imprudent behaviors such as taking on too much debt and responsibly paying back loans owed. But when was the last time you saw a personality test when you applied for a mortgage? By including human variables such as conscientiousness and decision making in modeling risk, Financial Engineers can reduce some uncertainty in their models.
2) To what degree are Financial Engineers systematically working in environments that encourage them to think differently about creative ways of estimating and modeling risks? Harvard’s Teresa Amabile who has devoted her 30-year career to studying creativity. Her research suggests that severe deadlines, competition and fear hinder employees from doing their most creative work. Creativity emerges mostly from intrinsic motivation – interesting, challenging and captivating. Her exhaustive, longitudinal work suggests that creating a workplace with positive feelings such as joy enhance creativity; and conversely negative emotions such as anger, sadness, and fear constrain it. Employees such as Financial engineers need and want plenty of hard work to do, with high expectations of performance; but Amabile’s work suggests that setting up an environment that’s going to facilitate their creative ability without “having to deal with a lot of garbage” is essential. Managers can support Financial Engineer creativity by protecting their employee’s availability, making sure they’re feeling good about their work, protecting their resources and helping them avoiding distractions. How many Finance leaders view themselves as service employees, supporting Financial Engineers from doing the complex, day-to-day heavy creative lifting, to get increasingly more useful risk models and mitigation strategies?
3) Some employees outperform others. Most I/O research points to cognitive ability and conscientiousness as two of the most critical predictors of job performance in all jobs ever studied. It’s reasonable to expect that Financial Engineers are relatively strong in cognitive ability, however, in so far as there is still variability left between them, measures of cognitive ability can be a useful way to select better, smarter “Quants”. Similarly, Professor Steven Guastello‘s research suggests Financial Engineers will be more creative if they are nonconforming, imaginitive and abstract thinkers, among other things. While Amabile’s social psychological approach suggests training and organizational development interventions; Guastello’s suggests additional pre-hire selection factors to assess before hiring Financial Engineers, if they need to create better models over time.
The Scientific Leader Blog 