The perils of the ineffective use of ratings in insurance - The Litmus view

It is commonly argued that a major driver of the financial crisis was an over-reliance on ratings; that the blind acceptance of rating agency views by investors and bankers proved to be unhealthy.

It would seem that a similar pattern exists in the insurance markets - ratings trigger clauses are now commonplace, there are many sectors where having a rating is a fundamental passport to trade, and the discussion of the quality of the carrier’s ‘paper’ starts (and usually ends) with a question about ratings.

Yet ratings do not feature to any great extent on major training agendas and an understanding of what they mean features pretty low down in most people’s minds.

Clearly part of this is down to human nature – they seem easy to understand, don’t they?  ‘A’ is good and ‘B’ is bad, surely – a nice and convenient way to distil the whole financial health question into a binary decision. 

‘The Litmus View’ is that ‘financial health’ can never be that simple, and a little more knowledge about ratings in the market could only be positive.  We would contend that anyone using ratings extensively would probably need to be able to demonstrate, in the act of delivering their duty of care to their clients and/or shareholders, a sufficient knowledge and understanding of ratings to justify their use of them.

Let’s just consider what the rating is trying to interpret and convey:

  • It’s conveying the future likelihood that the insurer will be around to pay claims – not just today or next week but in the medium term

By using:

  • Historical financial and management information provided by the insurer about its performance and wealth
  • Consideration of the position of that insurer in a macro and micro sense, from the general economic environment to their specific role in the market and their ability to compete

The analysts are looking at information today that was compiled by the client and its auditor at some point in time in the past (such that the real picture will have already changed – for better or worse).  From this they are trying to determine what is most likely to be the case at a point in the future.

Therefore our first key message is that a ‘rating’ is simply an opinion based on current and historic information about the most likely future outcome, i.e. it’s a forecast, similar to an economic forecast.

Given that this is the case, the analysis looks at the ‘fundamentals’ of the insurer – the key characteristics that will enable it to survive and succeed in the marketplace.  Capital is important but isn’t enough on its own, it’s what the insurer does with that capital that will determine where it is.

Insurer financial strength ratings (‘FSRs’) are specific to ‘policyholder credit risk’ – the possibility that the insurer will fail to meet its obligations to the policyholder; outside the insurance sector other types of rating are more common (for example those focused on the obligations of paying interest on bonds).

A key point to remember here is the ‘seniority’ of the policyholder; in the event of the failure of the insurer, after certain tax obligations, the policyholder would be first in the queue for anything that’s owed.  Debt investors would follow depending on the seniority (or ‘subordination’) of the debt, with equity investors last.  So FSRs are rated higher than debt to reflect a remoter likelihood of ‘default’ (the definition of insurer ‘default’ is an important one which we address later).

In the financial markets, the majority of defaults are due to missing interest payments on debt instruments and there’s a very rich body of data around historical instances of default.  The markets translate this historical data into a ‘risk metric’ which is often used as a proxy for future probability of default at different rating levels.

However, it’s difficult to determine when an insurer has actually defaulted as the insurance regulators tend to intervene before the policyholders have been impacted.

As rating agencies are rating to the probability of the insurer failing to meet ‘policyholder obligations’ they need their own definitions and indeed AM Best uses the term ‘impairment’ rather than default, with an impairment defined as:

“The first official regulatory action, whereby the insurers:

  • Ability to conduct normal insurance operations is adversely affected;
  • Capital and surplus have been deemed inadequate to meet legal requirements and/or
  • General financial condition has triggered regulatory concern”

S&P’s default definition for insurers isn’t dramatically different:

  • “The insurer’s financial security may be so undermined such that the supervisor assumes control
  • It may embark on a coercive claims commutation programme;
  • It may fail to meet policy guarantees, remove bonuses previously declared, or fail to declare bonuses that policyholders reasonably expect based on policy terms or public statements
  • It may fail to meet a senior or subordinated debt obligation”

The Litmus View is that this probably represents the biggest gap in the re/insurance market’s common understanding of ratings and re/insurer failure, the common perception being that an insurer has ‘failed’ if it moves into run-off; however many insurers move into solvent, orderly run-off and continue to meet their obligations to policyholders. 

So from the rating agency perspective, just because the insurer is no longer writing business doesn’t mean that it has defaulted; hence you see insurers that are perceived to have failed in the market still carrying secure-range ratings.

Despite this different definition of default for insurance ratings, an ‘A’ is still an ‘A’ – ratings are relative indicators across all the rated universe, whether banks, telecoms, universities, or insurers.  So that the body of default data statistics still tells us something about what ratings mean (as well as how the rating agencies have performed).

In essence, this tells us that from the point when they were originally rated ‘AAA’, usually just under 1% of ‘AAA’ entities had defaulted within 15 years – so a AAA default within a 15 year period has the equivalent of a 1-in-100 year occurrence probability.  This rises to once every 38 years for ‘A’ and once every 14 years for ‘BBB’ (just over 7%).  If we look at a much shorter time-frame – say 2 years from the original rating, the AAA default rate is 0.03%, or a greater than 1-in-300 years probability.  Even for BBB the 2-year default rate is just 0.63%.

Another interesting observation is that it takes an average of roughly 8 years from its original rating for a BBB to default, suggesting that, in normal circumstance and on average, we might expect a BBB rated insurer to be able to meet its obligations on short-tail business.

It’s also worth comparing the S&P default rates with the AM Best impairment rates (these statistics are available from the rating agencies themselves) – which brings us to the next Litmus View, which is –

Not all ratings are equivalent, especially when you consider that AM Best has fewer rating categories than S&P.  It is possible to compare the rating scales, but the worst thing you could do is simply count down from the top, you would soon run out of categories on the Best scale.

Finally we should consider the ‘outlooks’ published by the agencies, either ‘positive’, ‘stable’, or ‘negative’. 

If we at first understand that ratings are medium-term indicators that aim to forecast some distance into the future (18 months to 3 years, depending on the agency) then they have to have ‘buffers’ in order to show stability, otherwise they would go up and down like share prices or CDS spreads (the cost of buying insurance against the risk that a borrower defaults).

To indicate the upwards or downwards pressure on the rating, the underlying trend, if you like, then the agencies publish outlooks.  For S&P, a positive outlook indicates “at least a one-in-three likelihood of resulting in a rating action over the intermediate term (usually up to two years)”, which begs the question “is it better to deal with a BBB+ with a positive outlook or an A- with a negative outlook?”

We would contend that it’s at least as important to be aware of the outlook and to be making your own decision as to how to act, and that if you read the words the agencies use then they can be very powerful indicators.  

The Litmus View is therefore that outlooks are highly important, particularly in stressed situations – it’s unwise to ignore them.

One final word of caution, not all carriers in a rated group have a rating, or the rating of the subsidiary may well be different from the parent.  So take care which entity you’re doing business with.



Peter Hughes's picture

Peter is a Managing Partner of Litmus Analysis a specialist ratings advisory, consultancy, training and online application provider focused on the insurance industry.

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Very interesting and insightful article. Thanks Peter but, surely, THE concern should be acknowledging or eradicating the inherent flaws in the Rating Agency process? What is the value of an"opinion" that can see a AAA rated organisation collapse overnight? Does this not suggest that predictions about a non-linear world, made by linear computer models, that are based upon probabilities, statistical correlations and assumptions, using metrics that fail to reflect the interpendencies and interactions of the processes that underpin a company's activities are 'unreliable'? Mind you this questions could be applied to insurance risk rating! Perhaps we should have a chat about how we might apply a rigorous measurement of RESILIENCE...rather than relying on a methodology that, essentially, attempts to predict the unpredictable. After all, if the focus is upon 'probable' events, without preparing for the possible and plausible ones what is the likelihood of creating and sustaining a culture of prevention within insurers' and the firms that make up their books? Hopefully food for thought.
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