Risk Limits and Controlling

A New York Times Magazine article on Jamie Dimon, now CEO of JP Morgan Chase Bank, tells that he once set a risk limit for Travelers…

  • Losses from a once in a hundred year storm could not exceed a quarter’s earnings.

For the quantifiable risks that banks and insurers have aplenty, that is exactly how a risk limit needs to read.  It must state a frequency (once in a hundred or 1%) and a severity (one quarter’s earnings).

That sort of simple clarity seems to escape most financial firms.  Probably that is because they have little experience with the frequency part of that statement.

Think of this analogy.  You are sitting there in an office building deciding what to set as the speed limit for a new transportation system.  That system has newly designed roads and vehicles.  You do not know the tolerances of either the roads or the vehicles.  You have been a passenger on test runs, but during that test, you were not shown the speeds that the vehicle was going.

Toyota Motor Triathlon Race Car 2007
What might make sense in that situation, would be for the person being asked to make the decisions on speed limits to be told what speed that they had been going on the long straight-aways, on the gradual curves, the sharp curves and how long it took to stop the vehicle at various speeds.  In addition, more trips, more experience, should be undertaken and the speed of the vehicle should be noted under various weather conditions as well as types of roads.

Polls often reveal that the most common shortfall of ERM development is in the area of Risk Tolerance and Risk Appetite.  In many cases, that shortfall is due to the inexperience of management and boards with the frequency information.

There is no shortcut to getting that experience.  But there are simple exercizes that can be undertaken to look at prior experiences and tell the story of just how fast the firm was going and how severe the weather was.

The best such exercize is to look backwards in time over the recent past as well as to famously adverse periods in the more remote past.  For each of those situations, the backwards looking frequency can be assigned.  This is done by looking at the current risk model and determining the frequency that is aligned with the level of gains losses that were experienced in general.  That frequency is analogous to the weather.  Then the risk analyst can look at the firm’s own gain or loss experience and the frequency that the model could attribute to that size gain or loss.

Once a firm has some comfort with frequency, they can write a real risk appetite statement.

And after that, they can go through an exercize each year of deciding what frequency to assign to the experience of the year’s gains and losses.

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Explore posts in the same categories: Control Cycle, Risk Limits, Risk Management System, Risk Treatment

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