Firms have been telling us that they need better benchmarking data on some of the most material capital modelling assumptions.

In response to this, we have just completed our 2021 London Market capital benchmarking survey, and summarise some of the key highlights below. 

Our survey focuses on some of the most important capital modelling assumptions, on a class-by-class basis, as follows:

• Premium and reserve risk volatility
• 1-year risk recognition
• Key aspects of correlation

The 23 firms that took part covered a wide range of classes, as well as a good spread of smaller/larger firms and a mix of specialist underwriters and highly diversified books. 

Here are a few key highlights:

• Volatility of premium risk by class: For premium risk, most classes were modelled using a CoV of over 35% by more than half of the respondents. The exceptions to this were Motor, Property Binder, General Property and A&H where the CoVs were typically lower. 
• Volatility of reserve risk by class: For reserve risk, the typical range was 15% to 35% which was used by more than half of the respondents. The only exception was the Casualty FI & PI class which was typically modelled as more volatile.
• One-year risk recognition: this is typically a difficult assumption to set. For Property D&F and General Casualty business there was reasonable consensus on the appropriate assumptions, but in other classes there was a surprisingly wide range of views.
• Correlations: we asked about correlations in three areas
  1. Between lines of business (LoBs) for reserve risk
  2. Between LoB for premium risk
  3. Between premium risk and reserve risk for the same LoB.
• Most firms set standard “low”, “medium” and “high” correlation assumptions and use these across all three areas of correlation. For “medium” correlation, the most typical assumption is around 25%.
• Some firms take a slightly more nuanced approach – most commonly, this involves using a narrower range of low/medium/high correlations between premium and reserve risk for the same LoB compared to either premium risk or reserve risk alone. This makes sense given that, for a single class of business, premium risk and reserve risk have many common drivers, eg similar policy wordings and the fact that the business is underwritten and managed by the same people. 
• Volatility vs premium volume: one of the interesting features was what wasn’t there. We were interested in whether larger books were typically more stable than smaller books as volatility of individual risks diversifies away. Surprisingly, there was little evidence for this across most classes. A possible justification is that the London Market is a subscription market, meaning that smaller books often involve smaller shares of a similar number of individual risks.  However, we’re not sure this fully explains the observed data and we were left wondering whether firms are doing enough to reflect the volatility of their smaller portfolios.  

The value of benchmarking

It’s always been our view that benchmarks should be used as a tool to help corroborate, rather than lead, thinking when setting capital modelling assumptions. Each business is unique and there may be good reasons why you need to vary materially from benchmarks in order to reflect your risk profile appropriately.

Nonetheless you will want to be able to explain such variances clearly to your stakeholders, with appropriate rationale. 

Please get in touch with us if you would like to find out more, or would like to be included in future surveys. We’d also love to hear from you if you have feedback on any areas that you’d like us to cover in our future benchmarking research.