No Room for Woolly Thinking in the Re/Insurance Industry

analyticsI recently presented a paper on risk perception to the UK’s Parliamentary & Scientific Committee. Below is a snapshot of my speech, but you can access the full paper, “Risky Business: Risk and Reward Assessment in Business Decision Making,” here.

As a young maths graduate in 1980 I looked around for a career that would offer general business experience but with an element of mathematics. General insurance seemed ideal, “the risk business.” It was a big mistake. I found myself in a woolly thinking, bloated bureaucracy where insurance rates came out of a dusty book that looked as if it had been handed to Moses on Mount Sinai; in truth parts probably dated back over 50 years.

By 1985 I had moved to the reinsurance market, the insurance of insurance companies, which I thought must offer a more rigorous analysis of risk – the amounts of cover bought were in the hundreds of millions, the premiums huge, the risks very uncertain. I was wrong. The market worked on shared knowledge and used simple rating algorithms.

David Simmons presentation "Risky Business: Risk and Award Assessment in Business Decision Making"

Read David Simmons' paper: "Risky Business"

But quickly things would change and that change would be profound. The market now is unrecognizable from the one I joined. Twenty–five years ago I was the only mathematician working for a London market reinsurance broker developing risk analysis systems. Now Willis Re alone has over four hundred analytical staff, approaching 20% of the overall personnel total.

Risk Rules

Risk is now embedded in the decision-making processes of all UK insurers, from the smallest to the largest. Directors of insurance companies are now expected to have a broad understanding of the risk models used in their business: their assumptions, strengths and limitations, and the relationship between risk and reward is considered before every major decision is made. The cultural change has been enormous.

Developing technology has been the catalyst behind much of this change. It has not only allowed the gathering of data, but has also made it easily accessible and made processor-heavy stochastic modelling available on the desktop. Rather than modelling a best estimate or worst case, software made it possible to attempt to model all possible outcomes of loss-causing events, which opened the door to new pricing and decision-making algorithms.

Technology Isn’t Necessarily a Good Thing for Everyone…

The insurance industry has become far, far more technical. Insurers are stronger, better capitalized, more fit for purpose. Regulators are more efficient and better informed. More internationally competitive insurers, brokers and consultants benefit the UK economy and create UK jobs.

But greater risk analysis means that some lose. Insurers can more readily identify poor risks, and premiums, say for those in a flood plain with poor flood protection, may increase. Some countries such as France nationalize some areas of risk to ensure “solidarity,” with the same flood premium regardless of whether you live at the top of a mountain or the bottom of a valley; but appropriate risk pricing encourages appropriate risk behavior and the lack of availability of insurance, for example, for those planning to build on a flood plain, will surely concentrate minds.

“The Computer Says No”

Whilst the insurance industry’s adoption of probabilistic decision-making tools has certainly brought more objectivity to decision making. it must be emphasised that all models are hugely assumption-dependent. Resist the temptation to say “the computer says no”! Insurance company executives cannot hide behind experts. They need to judge the advice they are given, and make a decision; it is their decision, they are responsible. Models advise, they do not decide.

The real value of a risk/return approach derives from the transparency, understanding and challenge which should flow from the risk quantification process. Objectives should be clearly stated and options compared to these objectives. All assumptions behind a decision can be seen, discussed, challenged and stressed. Stakeholders can understand how and why decisions have been made. In this brave new world there can be no more hiding behind woolly assessments and woolly thinking.

About David Simmons

David is a Managing Director in the Willis Re Analytics team in London. He focuses on Enterprise Risk Management, i…
Categories: Analytics, Europe, Reinsurance | Tags: , ,

One Response to No Room for Woolly Thinking in the Re/Insurance Industry

  1. Lyndsay says:

    This is a great reminder from a reinsurance veteran that the computer model doesn’t know as much as an experienced professional. A well trained underwriter will take the advice of a model, but make a decision based on their own intelligence and judgment. Thanks for the reminder, David!

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