Actuarial pricing, capital modelling and reserving

Pricing Squad


Issue 22 -- February 2018

Welcome to Pricing Squad

Pricing Squad is the newsletter for fellow pricing practitioners and actuaries in general insurance.

Today's issue is about cool software and about monetary policy.


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Monetary policy and insurance cycle

We live in times of centrally administered low interest rates. Cheap money does this:

  1. Stimulates spending in the economy. That's the stated Keynesian goal of low interest rate policy.
  2. Inflates prices in some industries. Think about housing in the UK.
  3. Redistributes wealth - those who access credit first get to buy assets before price bubbles form. Financial brokers and property developers win this zero-sum game.

But cheap money stimulates the economy unevenly. Risky segments of the economy get more boost than low-risk segments, as explained by Tyler Coven's book "Risk and Business Cycles". Error prone marginal entrepreneurs (underwriters) obtain capital which would not have been available to them in ordinary circumstances. The GIRO 2009 paper explains how Winner's Curse exacerbates such activity. The party stops when enough underwriters blink and voluntarily limit capacity.

An earlier Austrian Business Cycle Theory gave a similar explanation of business cycles but it focused on time horizon of various investments instead of their total riskiness. This theory applies not just to insurance, but to the entire economy.

Can we test this Tyler-Austrian theory based on what we know about the insurance market?

If the theory is true then we should observe 1) a soft insurance market in today's low interest rates world - which in 2018 we certainly do; and 2) the market being softest for the most risky and most long-tail lines of insurance.

Indeed the market has historically behaved exactly this way. For example long tail liability lines let underwriters get away with underpricing the longest. Academic literature has documented it also, see "Underwriting cycles in property and liability insurance: an empirical analysis of industry and byline data" by Patterson or "Cycles and Crises in Property / Casualty Insurance: Causes and Implications for Public Policy" by Cummins.

The same effect is predicted to continue in 2018 with the most risky, most long-tailed lines softening the most, see the chart in this Willis Towers Watson report.

It seems that the Tyler-Austrian theory is working fine.

That is all for today. Thank you for reading!


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