What if it’s a perfect storm? Stronger evidence that insurers should account for co-occurring weather hazards

John Hillier, Tom Perkins, Ryan Li, Hannah Bloomfield, Josie Lau, Stefan Claus, Paul Harrington, Shane Latchman and David Humphry

In 2022 a sequence of storms (Dudley, Eunice and Franklin) inflicted a variety of hazards on the UK and across Northwest Europe, resulting in £2.5–4.2 billion in insured losses. They dramatically illustrate the potential risk of a ‘perfect storm’ involving correlated hazards that co-occur and combine to exacerbate the total impact. Recent scientific research reinforces the evidence that extreme winds and inland flooding systematically co-occur. By better modelling how this relationship might raise insurers’ capital risk we can more firmly argue that insurers’ model assumptions should account for key dependencies between perils. This will ensure that insurers continue to accurately assess and manage risks in line with their risk appetite, and that capital for solvency purposes remains appropriate.

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How does house price indexation affect the valuation of equity release mortgages?

Craig Turnbull

Equity Release Mortgages (ERMs) are different from traditional mortgages. Both mortgages provide an upfront cash lump sum. But traditional mortgages are tied to an immediate home purchase that is repaid over a set period, while equity release mortgages are tied to a share of a future home sale. In this blog post, I examine some of the challenges with valuing equity release mortgages. Specifically, I focus on the approaches used to estimate the current home value – a key input to the mortgage valuation – which typically involves applying a simple house price index return to the most recent house survey valuation or transaction price. I show this widespread approach may understate equity release mortgage risks and overstate portfolio values.

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How competitive are UK insurance markets?

Fraser Drew, David Humphry, Michael Straughan and Eleanor Watson

For most of us buying insurance nowadays, price comparison websites offer plenty of choice. But how much competition in insurance markets is there? There are very few studies that address this question (see here for a summary), unlike for banking where there is a wide literature. We take an exploratory approach to address the question, applying benchmarks used in competition research to a unique set of reporting data across multiple UK insurance regulatory regimes, with the hope of stimulating further work. We find competition generally works well in UK life and non-life insurance markets, despite increases in life market concentration over the past 25 years. However, competition regulators have found practices in specific markets that harm consumers.

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US Hurricane Clustering: A New Reality?

Alex Ntelekos, Dimitris Papachristou and Juan Duan

The 2017 Atlantic hurricane season was the fifth most active in 168 years. It was also one of only six seasons to see multiple Cat 5 hurricanes (Irma & Maria). These two hurricanes, followed similar tracks and, together with Hurricane Harvey, occurred close together. This situation can hinder relief efforts. For insurers it may also lead to resource strain, disputes and unhedged risks, if insurers do not have enough ‘sideways’ reinsurance cover. Our post asks whether three major hurricanes occurring in the US in close succession really was exceptional or, as our analysis of recent data suggests, it might happen more often in future. Is the insurance industry underestimating the likely ‘clustering’ of major hurricanes?

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Completing Correlation Matrices

Dan Georgescu and Nicholas J. Higham

Correlation matrices arise in many applications to model the dependence between variables. Where there is incomplete or missing information for the variables, this may lead to missing values in the correlation matrix itself, and the problem of how to complete the matrix. We show that some of these practical problems can be solved explicitly, via simple formulae, and we explain how to use mathematical tools to solve the more general problem where explicit solutions may not exist. “Simple” is, of course, a relative term, and the underlying matrix algebra and optimization necessarily makes this article more mathematically sophisticated than the typical Bank Underground post.

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Insurance companies: amplifiers or the white knights of financial markets?

Graeme Douglas, Nicholas Vause and Joseph Noss

Risky asset prices plummeted following the collapse of Lehman Brothers in 2008. Whilst driven partly by deteriorations in fundamental news, these falls were amplified by ‘flighty’ investors that sold at the first signs of trouble. Conventional wisdom dictates that life insurers, with their long-term investment horizons, are better placed than most to ‘lean against the wind’ by looking through short-term fluctuations in asset prices. They could thereby stabilise prices when others are selling. But the structure of regulations can greatly influence insurers’ investment incentives. Using our model of insurers’ asset allocations, we find that new ‘Solvency II’ regulations reduce UK life insurers’ willingness to act as the white knights of financial markets, particularly in the face of falling interest rates.

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Driverless Cars: Insurers Cannot be Asleep at the Wheel

Neha Jain, James O’Reilly & Nicholas Silk

In 2020 Google plans to launch a self-driving car which has already driven nearly one million miles without causing an accident; it doesn’t get tired and irritable, swerve into lamp posts or require a driving test. The in-built chauffeur comes in the form of a rotating LIDAR laser taking 1.3 million recordings per second, and it’s a better driver than you. By eliminating the element of human blunders, driverless cars are forecast to reduce motor accidents by up to 90% in the US according to McKinsey. That might imply a substantial impact on the insurance industry, with liability potentially shifting to car manufacturers. Such developments would pose challenging questions for the PRA in regulating UK insurance firms.

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