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Balancing 'Quants' with 'Qualts'

I like quants, but they often narrow their focus to only numbers, when more insight is needed from other methods. There has been much written since the financial crisis of 2008 about the over reliance on all the risk models that were supposed to have revealed how much risk firms were taking and to somehow enable them to manage their risk appetite more successfully. That mindset about risk modeling and measurement has taken much heat because so many lost so much: investments, pensions, jobs, houses--even lives.

By Christopher E. Mandel

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There is certainly good reason to pursue innovation in risk measurement and modeling as we have a significant void to fill in the realm of accurate, reliable predictors of the effects of risk, both good and bad. Unfortunately, so many firms think "quants" are the answer to their problems. Perhaps they don't understand the true nature of their problems. I certainly don't subscribe to the theory that quants are necessarily the best qualified leaders in the risk realm. In fact, so many of these fine folks can't manage their way out of a paper bag, while certainly many are quite capable. While I have no one in particular in mind, there has been too much carnage on the field of risk management, when there's so much more to be achieved. Naturally, finance functionaries seem to have this quant bias; insurers are notorious for it. I don't blame the insurers as risk is their business and quantitative measurement is so central to assuring profitability and to controlling variances from the plan. With insurers in particular the worst case related to natural catastrophes is so significant, they can't afford not to put much effort toward reliable quantification. But reliability in the actuarial field is a direct result of the chosen "confidence level." Admittedly, qualitative assessments have confidence limitations built into them by default. In other words, qualitative assessments by their very nature have lower confidence levels, yet can serve a useful purpose. Ultimately, so much value is left on the table when all the chips go in the quant basket without other insights.

Most enterprise risk management initiatives have taken a course that almost always starts with a qualitative: color-oriented, three-by-three or five-by-five risk assessments arranged in a matrix, typically tied to two key elements of likelihood and impact, or alternatively, probability and severity, those heartwarming actuarial semantics. There is value in this approach, if only to give some sense of "directional correctness." But to truly make your case with senior leaders, you need to speak their language. That language is most often replete with financially oriented metrics and assessments, which are actionable in nature.

Other aspects of a financially oriented dialogue include: reliability, especially if you expect resource allocation decisions to be made based on your input; quantification, which is necessary to create meaningful metrics to support risk modeling; scenario analysis and effectively connect to the planning processes; enabling and supporting the development of risk appetite frameworks including tolerances; establishing a common language consistent with key financial terms central to how corporate performance is measured; measuring the outcomes involving risk/reward trade-offs; and enabling correlation and aggregation analysis.

Together with qualitative measures, quantitative measures allow you to engage senior leaders and boards more effectively, giving them something about which they can deliberate.

CHRIS MANDEL is the president of Excellence in Risk Management, LLC, a long term risk management leader and former president of RIMS.

October 15, 2011

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