Tag Archives: solvency ii

Computer says yes

Amlin reported their Q1 figures today and had some interesting comments on their reinsurance and retrocession spend that was down £50 million on the quarter (from 23% of gross premiums to 18%). Approx £20 million was due to a business line withdrawal with the remainder due to “lower rates and improved cover available on attractive terms”.

Amlin also stated “with the assistance of more sophisticated modelling, we have taken the decision to internalise a proportion of a number of programmes. Given the diversifying nature of many of our insurance classes, this has the effect of increasing mean expected profitability whilst only modestly increasing extreme tail risk.

The use by insurers of their economic capital models for reinsurance/retrocession purchases is a trend that is only going to increase as we enter into the risk based solvency world under Solvency II. Current market conditions have resulted in reinsurers being more open to offering multi-line aggregate coverage which protect against both frequency and severity with generous exposure inclusions.

It will only be a matter of time, in my opinion, before reinsurers underwrite coverage directly based upon a insurer’s own capital model, particularly when such a model has been approved by a firm’s regulator or been given the blessing of a rating agency.

Also in the future I expect that firms will more openly disclose their operating risk profiles. There was a trend a few years ago whereby firms such as Endurance (pre- Charman) and Aspen did include net risk profiles, such as those in the graphs below, in their investor presentations and supplements (despite the bad blood in the current Endurance-Aspen hostile take-over bid, at least it’s one thing they can say they have in common!).

click to enlargeOperating Risk Distributions

Unfortunately, it was a trend that did not catch on and was quickly discontinued by those firms. If insurers and reinsurers are increasingly using their internal capital models in key decision making, investors will need to insist on understanding them in more detail. A first step would be more public disclosure of the results, the assumptions, and their strengths and weaknesses.

Confounding correlation

Nassim Nicholas Taleb, the dark knight or rather the black swan himself, said that “anything that relies on correlation is charlatanism”.  I am currently reading the excellent “The signal and the noise” by Nate Silver. In Chapter 1 of the book he has a nice piece on CDOs as an example of a “catastrophic failure of prediction” where he points to certain CDO AAA tranches which were rated on an assumption of a 0.12% default rate and which eventually resulted in an actual rate of 28%, an error factor of over 200 times!.

Silver cites a simplified CDO example of 5 risks used by his friend Anil Kashyap in the University of Chicago to demonstrate the difference in default rate if the 5 risks are assumed to be totally independent and dependent.  It got me thinking as to how such a simplified example could illustrate the impact of applied correlation assumptions. Correlation between core variables are critical to many financial models and are commonly used in most credit models and will be a core feature in insurance internal models (which under Solvency II will be used to calculate a firms own regulatory solvency requirements).

So I set up a simple model (all of my models are generally so) of 5 risks and looked at the impact of varying correlation from 100% to 0% (i.e. totally dependent to independent) between each risk. The model assumes a 20% probability of default for each risk and the results, based upon 250,000 simulations, are presented in the graph below. What it does show is that even at a high level of correlation (e.g. 90%) the impact is considerable.

click to enlarge5 risk pool with correlations from 100% to 0%

The graph below shows the default probabilities as a percentage of the totally dependent levels (i.e 20% for each of the 5 risks). In effect it shows the level of diversification that will result from varying correlation from 0% to 100%. It underlines how misestimating correlation can confound model results.

click to enlargeDefault probabilities & correlations

ILS Fund versus PropertyCat Reinsurer ROEs

Regular readers will know that I have queried how insurance-linked securities (ILS) funds, currently so popular with pensions funds, can produce a return on equity that is superior to that of a diversified property catastrophe reinsurer given that the reinsurer only has to hold a faction of its aggregate limit issued as risk based capital whereas all of the limits in ILS are collaterised. The recent FT article which contained some interesting commentary from John Seo of Fermat Capital Management got me thinking about this subject again. John Seo referred to the cost advantage of ILS funds and asserted that reinsurers staffed with overpaid executives “can grow again, but only after you lay off two out of three people”. He damned the traditional sector with “these guys have been so uncreative, they have been living off earthquake and hurricane risks that are not that hard to underwrite.

Now, far be it from me to defend the offshore chino loving reinsurance executives with a propensity for large salaries and low taxation. However, I still can’t see that the “excessive” overheads John Seo refers to could offset the capital advantage that a traditional property catastrophe reinsurer would have over ILS collateral requirements.

I understood the concept of ILS structures that provided blocks of capacity at higher layers, backed by high quality assets, which could (and did until recently) command a higher price than the traditional market. Purchasers of collaterised coverage could justify paying a premium over traditional coverage by way of large limits on offer and a lower counterparty credit risk (whilst lowering concentration risk to the market leading reinsurers). This made perfect sense to me and provided a complementary, yet different, product to that offered by traditional reinsurers. However, we are now in a situation whereby such collaterised reinsurance providers may be moving to compete directly with traditional coverage on price and attachment.

To satisfy my unease around the inconsistency in equity returns, I decided to do some simple testing. I set up a model of a reasonably diversified portfolio of 8 peak catastrophic risks (4 US and 4 international wind and quake peak perils). The portfolio broadly reflects the market and is split 60:40 US:International by exposure and 70:30 by premium. Using aggregate exceedance probability (EP) curves for each of the main 8 perils based off extrapolated industry losses as a percentage of limits offered across standard return periods, the model is set up to test differing risk premiums (i.e. ROL) for each of the 8 perils in the portfolio and their returns.  For the sake of simplicity, zero correlations were assumed between the 8 perils.

The first main assumption in the model is the level of risk based capital needed by the property catastrophe reinsurer to compete against the ILS fund. Reviewing some of the Bermudian property catastrophe players, equity (common & preferred) varies between 280% and 340% of risk premiums (net of retrocessions). Where debt is also included, ratios of up to 400% of net written premiums can be seen. However, the objective is to test different premium levels and therefore setting capital levels as a function of premiums distorts the results. As reinsurer’s capital levels are now commonly assessed on the basis of stressed economic scenarios (e.g. PMLs as % of capital), I did some modelling and concluded that a reasonable capital assumption for the reinsurer to be accepted is the level required at a 99.99th percentile or a 1 in 10,000 return period (the graph below shows the distribution assumed). As the graph below illustrates, this equates to a net combined ratio (net includes all expenses) of the reinsurer of approximately 450% for the average risk premium assumed in the base scenario (the combined ratio at the 99.99th level will change as the average portfolio risk premium changes).

click to enlargePropCAT Reinsurer Combined Ratio Distribution

So with the limit profile of the portfolio is set to broadly match the market, risk premiums per peril were also set according to market rates such that the average risk premium from the portfolio was 700 bps in a base scenario (again broadly where I understand the property catastrophe market is currently at).

Reviewing some of the actual figures from property catastrophe reinsurer’s published accounts, the next important assumption is that the reinsurer’s costs are made up of 10% acquisition costs and 20% overhead (the overhead assumption is a bit above the actual rates seen by I am going high to reinforce Mr Seo’s point about greedy reinsurance executives!) thereby reducing risk premiums by 30%. For the ILS fund, the model assumes a combined acquisition and overhead cost of just 10% (this may also be too light as many ILS funds are now sourcing some of their business through brokers and many reinsurance fund managers share the greedy habits of the traditional market!).

The results below show the average simulated returns for a reinsurer and an ILS fund writing the same portfolio with the expense levels as detailed above (i.e 30% versus 10%), and with different capital levels (reinsurer at 99.99th percentile and the ILS fund with capital equal to the limits issued). It’s important to stress that the figures below do not included investment income so historical operating ROEs from property catastrophe reinsurers are not directly comparable.

click to enlargePropCAT Reinsurer & ILS Fund ROE Comparison

So, the conclusion of the analysis re-enforces my initial argument that the costs savings cannot compensate for the leveraged nature of a reinsurer’s business model compared to the ILS fully funded model. However, this is a simplistic comparison. Why would a purchaser not go with a fully funded ILS provider if the product on offer was exactly the same as that of a reinsurer? As outlined above, both risk providers serve different needs and, as yet, are not full on competitors (although this may be the direction of the changes underway in the market currently).

Also, many ILS funds likely do use some form of leverage in their business model whether by way of debt or retrocession facilities. And competition from the ILS market is making the traditional market look at its overhead and how it can become more cost efficient. So it is likely that both business models will adapt and converge (indeed, many reinsurers are now also ILS managers).

Notwithstanding these issues, I can’t help conclude that (for some reason) our pension funds are the losers here by preferring the lower returns of an ILS fund sold to them by investment bankers than the higher returns on offer from simply owning the equity of a reinsurer (admittedly without the same operational risk profile). Innovative or just cheap risk premia? Go figure.

Not all insurers’ internal models are equal

Solvency II is a worn out subject for many in the insurance industry. After over 10 years of in depth discussions and testing, the current target date of 01/01/2016 remains uncertain until the vexed issue of how long term guarantees in life business is resolved.

The aim of the proposed Solvency II framework is to ensure that (re)insurers are financially sound and can withstand adverse events in order to protect policy holders and the stability of the financial system as a whole. Somewhere along the long road to where we are now, the solvency capital requirement (SCR) in Solvency II to achieve that aim was set at an amount of economic capital corresponding to a ruin probability of 0.5% (Value at Risk or VaR of 99.5%) and a one year time horizon.

Many global reinsurers and insurers now publish outputs from their internal models in annual reports and investor presentations, most of which are set at one year 99.5% VaR or an equivalent level. Lloyds’ of London however is somewhat different. Although the whole Lloyds’ market is subject to the one year Solvency II calibration on an aggregate basis, each of the Syndicates operating in Lloyds’ have a solvency requirement based upon a 99.5% VaR on a “to ultimate” basis. In effect, Syndicates must hold additional capital to that mandated under Solvency II to take into account the variability in their results on an ultimate basis. I recently came across an interesting presentation from Lloyds’ on the difference in the SCR requirement between a one year and an ultimate basis (which requires on average a third more capital!), as the exhibit below reproducing a slide from the presentation shows.

click to enlarge

SCR one year ultimate basis

Although this aspect of Lloyds’ of London capital requirements has not been directly referenced in recent reports, their conservative approach does reflect the way the market is now run and could likely be a factor behind recent press speculation on a possible upgrade for the market to AA. Such an upgrade would be a massive competitive plus for Lloyds’.

Insurance & capital market convergence hype is getting boring

As the horde of middle aged (still mainly male) executives pack up their chinos and casual shirts, the overriding theme coming from this year’s Monte Carlo Renez-Vous seems to be impact of the new ILS capacity or “convergence capital” on the reinsurance and specialty insurance sector. The event, described in a Financial Times article as “the kind of public display of wealth most bankers try to eschew”, is where executives start the January 1 renewal discussions with clients in quick meetings crammed together in the luxury location.

The relentless chatter about the new capital will likely leave many bored senseless of the subject. Many may now hope that, just like previous hot discussion topics that were worn out (Solvency II anybody?), the topic fades into the background as the reality of the office huts them next week.

The more traditional industry hands warned of the perils of the new capacity on underwriting discipline. John Nelson of Lloyds highlighted that “some of the structures being used could undermine some of the qualities of the insurance model”. Tad Montross of GenRe cautioned that “bankers looking to replace lost fee income” are pushing ILS as the latest asset class but that the hype will die down when “the inability to model extreme weather events accurately is better understood”. Amer Ahmed of Allianz Re predicted the influx “bears the danger that certain risks get covered at inadequate rates”. Torsten Jeworrek of Munich Re said that “our research shows that ILS use the cheapest model in the market” (assumingly in a side swipe at AIR).

Other traditional reinsurers with an existing foothold in the ILS camp were more circumspect. Michel Lies of Swiss Re commented that “we take the inflow of alternative capital seriously but we are not alarmed by it”.

Brokers and other interested service providers were the loudest cheerleaders. Increasing the size of the pie for everybody, igniting coverage innovative in the traditional sector, and cheap retrocession capacity were some of the advantages cited. My favourite piece of new risk management speak came from Aon Benfield’s Bryon Ehrhart in the statement “reinsurers will innovate their capital structures to turn headwinds from alternative capital sources into tailwinds”. In other words, as Tokio Millennium Re’s CEO Tatsuhiko Hoshina said, the new capital offers an opportunity to leverage increasingly diverse sources of retrocessional capacity. An arbitrage market (as a previous post concluded)?

All of this talk reminds me of the last time that “convergence” was a buzz word in the sector in the 1990s. For my sins, I was an active participant in the market then. Would the paragraph below from an article on insurance and capital market convergence by Graciela Chichilnisky of Columbia University in June 1996 sound out of place today?

“The future of the industry lies with those firms which implement such innovation. The companies that adapt successfully will be the ones that survive. In 10 years, these organizations will draw the map of a completely restructured reinsurance industry”

The current market dynamics are driven by low risk premia in capital markets bringing investors into competition with the insurance sector through ILS and collaterised structures. In the 1990s, capital inflows after Hurricane Andrew into reinsurers, such as the “class of 1992”, led to overcapacity in the market which resulted in a brutal and undisciplined soft market in the late 1990s.

Some (re)insurers sought to diversify their business base by embracing innovation in transaction structures and/or by looking at expanding the risks they covered beyond traditional P&C exposures. Some entered head first into “finite” type multi-line multi-year programmes that assumed structuring could protect against poor underwriting. An over-reliance on the developing insurance models used to price such transactions, particularly in relation to assumed correlations between exposures, left some blind to basic underwriting disciplines (Sound familiar, CDOs?). Others tested (unsuccessfully) the limits of risk transfer and legality by providing limited or no risk coverage to distressed insurers (e.g. FAI & HIH in Australia) or by providing reserve protection that distorted regulatory requirements (e.g. AIG & Cologne Re) by way of back to back contracts and murky disclosures.

Others, such as the company I worked for, looked to cover financial risks on the basis that mixing insurance and financial risks would allow regulatory capital arbitrage benefits through increased diversification (and may even offer an inflation & asset price hedge). Some well known examples* of the financial risks assumed by different (re)insurers at that time include the Hollywood Funding pool guarantee, the BAe aircraft leasing income coverage, Rolls Royce residual asset guarantees, dual trigger contingent equity puts, Toyota motor residual value protection, and mezzanine corporate debt credit enhancement  coverage.

Many of these “innovations” ended badly for the industry. Innovation in itself should never be dismissed as it is a feature of the world we live in. In this sector however, innovation at the expense of good underwriting is a nasty combination that the experience in the 1990s must surely teach us.

Bringing this back to today, I recently discussed the ILS market with a well informed and active market participant. He confirmed that some of the ILS funds have experienced reinsurance professionals with the skills to question the information in the broker pack and who do their own modelling and underwriting of the underlying risks. He also confirmed however that there is many funds (some with well known sponsors and hungry mandates) that, in the words of Kevin O’Donnell of RenRe, rely “on a single point” from a single model provided by to them by an “expert” 3rd party.

This conversation got me to thinking again about the comment from Edward Noonan of Validus that “the ILS guys aren’t undisciplined; it’s just that they’ve got a lower cost of capital.” Why should an ILS fund have a lower cost of capital to a pure property catastrophe reinsurer? There is the operational risk of a reinsurer to consider. However there is also operational risk involved with an ILS fund given items such as multiple collateral arrangements and other contracted 3rd party service provided functions to consider. Expenses shouldn’t be a major differing factor between the two models. The only item that may justify a difference is liquidity, particularly as capital market investors are so focussed on a fast exit. However, should this be material given the exit option of simply selling the equity in many of the quoted property catastrophe reinsurers?

I am not convinced that the ILS funds should have a material cost of capital advantage. Maybe the quoted reinsurers should simply revise their shareholder return strategies to be more competitive with the yields offered by the ILS funds. Indeed, traditional reinsurers in this space may argue that they are able to offer more attractive yields to a fully collaterised provider, all other things being equal, given their more leveraged business model.

*As a complete aside, an article this week in the Financial Times on the anniversary of the Lehman Brothers collapse and the financial crisis highlighted the role of poor lending practices as a primary cause of significant number of the bank failures. This article reminded me of a “convergence” product I helped design back in the late 1990s. Following changes in accounting rules, many banks were not allowed to continue to hold general loan loss provisions against their portfolio. These provisions (akin to an IBNR type bulk reserve) had been held in addition to specific loan provision (akin to case reserves). I designed an insurance structure for banks to pay premiums previously set aside as general provisions for coverage on massive deterioration in their loan provisions. After an initial risk period in which the insurer could lose money (which was required to demonstrate an effective risk transfer), the policy would act as a fully funded coverage similar to a collaterised reinsurance. In effect the banks could pay some of the profits in good years (assuming the initial risk period was set over the good years!) for protection in the bad years. The attachment of the coverage was designed in a way similar to the old continuous ratcheting retention reinsurance aggregate coverage popular at the time amongst some German reinsurers. After numerous discussions, no banks were interested in a cover that offered them an opportunity to use profits in the good times to buy protection for a rainy day. They didn’t think they needed it. Funny that.