Tag Archives: Return on equity

The New Normal (Again)

I expect that next week’s reinsurance jamboree in Monte Carlo will be full of talk of innovative and technology streaming-lining business models (as per this post on AI and insurance). This recent article from the FT is just one example of claims that technology like blockchain can reduce costs by 30%. The article highlights questions about whether insurers are prepared to give up ownership of data, arguably their competitive advantage, if the technology is really to be scaled up in the sector.

As a reminder of the reinsurance sector’s cost issues, as per this post on Lloyds’, the graph below illustrates the trend across Lloyds’, the Aon Benfield Aggregate portfolio, and Munich’s P&C reinsurance business.

click to enlarge

Until the sector gets serious about cutting costs, such as overpaid executives on luxury islands or expensive cities and antiquated business practises such as holding get togethers in places like Monte Carlo, I suspect expenses will remain an issue. In their July review, Willis stated that a “number of traditional carriers are well advanced in their plans to reduce their costs, including difficult decisions around headcount” and that “in addition to cost savings, the more proactively managed carriers are applying far greater rigor in examining the profitability of every line of business they are accepting”. Willis highlighted the potential difficulties for the vastly inefficient MGA business that many have been so actively pursuing. As an example of the type of guff executives will trot out next week, Swiss Re CEO, Christian Mumenthaler, said “we remain convinced that technology will fundamentally change the re/insurance value chain”, likely speaking from some flash office block in one of the most expensive cities in the world!

On market conditions, there was positive developments on reinsurance pricing at the January renewals after the 2017 losses with underlying insurance rates improving, as illustrated by the Marsh composite commercial rate index (example from US below).

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However, commentators have been getting ever more pessimistic as the year progresses, particularly after the mid-year renewals. Deutsche Bank recently called the reinsurance pricing outlook “very bleak”. A.M. Best stated that “the new normal for reinsurers appears to be one with returns that are less impressive and underwriting and fee income becoming a larger contributor to profits” and predicts, assuming a normal large loss level, an 8% ROE for 2018 for the sector. Willis, in their H1 report, puts the sectors ROE at 7.7% for H1 2018. S&P, in the latest report that is part of their Global Highlights series, also expects a ROE return for 2018 around 6% to 8% and estimates that “reinsurers are likely to barely cover their cost of capital in 2018 and 2019”.

S&P does question why “the market values the industry at a premium to book value today (on average at 1.24x at year-end 2017), and at near historical highs, given the challenges” and believes that potential capital returns, M&A and interest rate rises are all behind elevated valuations.  The recent Apollo PE deal for Aspen at 1.12 times book seems a large way off other recent multiples, as per this post, but Aspen has had performance issues. Still its interesting that no other insurer was tempted to have a go at Aspen with the obvious synergies that such a deal could have achieved. There is only a relatively small number of high quality players left for the M&A game and they will not be cheap!

As you are likely aware, I have been vocal on the impact the ILS sector has had in recent years (most recently here and here). With so-called alternative capital (at what size does it stop being alternative!) now at the $95 billion-mark according to Aon, A.M. Best makes the obvious point that “any hope for near-term improvement in the market is directly correlated to the current level of excess capacity in the overall market today, which is being compounded by the continued inflow of alternative capacity”. Insurers and reinsurers are not only increasing their usage of ILS in portfolio optimisation but are also heavily participating in the sector. The recent purchase by Markel of the industry leading and oldest ILS fund Nephila is an interesting development as Markel already had an ILS platform and is generally not prone to overpaying.

I did find this comment from Bob Swarup of Camdor in a recent Clear Path report on ILS particularly telling – “As an asset class matures it inevitably creates its own cycle and beta. At this point you expect fees to decline both as a function of the benefits of scale but also as it becomes more understood, less of it becomes alpha and more of it becomes beta” and “I do feel that the fees are most definitely too high right now and to a large extent this is because people are trying to treat this as an alternative asset class whereas it is large enough now to be part of the general mix”. Given the still relatively small size of the ILS sector, it’s difficult for ILS managers to demonstrate true alpha at scale (unless they are taking crazy leveraged bets!) and therefore pressure on current fees will become a feature.

A.M. Best articulated my views on ILS succinctly as follows: “The uncorrelated nature of the industry to traditional investments does appear to have value—so long as the overall risk-adjusted return remains appropriate”. The graph below from artemis.bm shows the latest differential between returns and expected cost across the portfolio they monitor.

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In terms of the returns from ILS funds, the graph below shows the underlying trend (with 2018 results assuming no abnormal catastrophic activity) of insurance only returns from indices calculated by Lane Financial (here) and Eurekahedge (here). Are recent 5 year average returns of between 500 and 250 basis points excess risk free enough to compensation for the risk of a relatively concentrated portfolio? Some think so. I don’t.

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Whether reinsurers and specialty insurers will be able to maintain superior (albeit just above CoC) recent returns over ILS, as illustrated in this post, through arbitrating lower return ILS capital or whether their bloated costs structures will catch them out will be a fascinating game to watch over the coming years. I found a section of a recent S&P report, part of their Global Highlights series, on cat exposures in the sector, amusing. It stated that in 2017 “the reinsurance industry recorded an aggregate loss that was assessed as likely to be incurred less than once in 20 years” whilst “this was the third time this had happened in less than 20 years“.

So, all in all, the story is depressingly familiar for the sector. The new normal, as so many commentators have recently called it, amounts to overcapacity, weak pricing power, bloated cost structures, and optimistic valuations. Let’s see if anybody has anything new or interesting to say in Monte Carlo next week.

As always, let’s hope there is minimal human damage from any hurricanes such as the developing Hurricane Florence or other catastrophic events in 2018.

Tails of VaR

In an opinion piece in the FT in 2008, Alan Greenspan stated that any risk model is “an abstraction from the full detail of the real world”. He talked about never being able to anticipate discontinuities in financial markets, unknown unknowns if you like. It is therefore depressing to see articles talk about the “VaR shock” that resulted in the Swissie from the decision of the Swiss National Bank (SNB) to lift the cap on its FX rate on the 15th of January (examples here from the Economist and here in the FTAlphaVille). If traders and banks are parameterising their models from periods of unrepresentative low volatility or from periods when artificial central bank caps are in place, then I worry that they are not even adequately considering known unknowns, let alone unknown unknowns. Have we learned nothing?

Of course, anybody with a brain knows (that excludes traders and bankers then!) of the weaknesses in the value-at-risk measure so beloved in modern risk management (see Nassim Taleb and Barry Schachter quotes from the mid 1990s on Quotes page). I tend to agree with David Einhorn when, in 2008, he compared the metric as being like “an airbag that works all the time, except when you have a car accident“.  A piece in the New York Times by Joe Nocera from 2009 is worth a read to remind oneself of the sad topic.

This brings me to the insurance sector. European insurance regulation is moving rapidly towards risk based capital with VaR and T-VaR at its heart. Solvency II calibrates capital at 99.5% VaR whilst the Swiss Solvency Test is at 99% T-VaR (which is approximately equal to 99.5%VaR). The specialty insurance and reinsurance sector is currently going through a frenzy of deals due to pricing and over-capitalisation pressures. The recently announced Partner/AXIS deal follows hot on the heels of XL/Catlin and RenRe/Platinum merger announcements. Indeed, it’s beginning to look like the closing hours of a swinger’s party with a grab for the bowl of keys! Despite the trend being unattractive to investors, it highlights the need to take out capacity and overhead expenses for the sector.

I have posted previously on the impact of reduced pricing on risk profiles, shifting and fattening distributions. The graphic below is the result of an exercise in trying to reflect where I think the market is going for some businesses in the market today. Taking previously published distributions (as per this post), I estimated a “base” profile (I prefer them with profits and losses left to right) of a phantom specialty re/insurer. To illustrate the impact of the current market conditions, I then fattened the tail to account for the dilution of terms and conditions (effectively reducing risk adjusted premia further without having a visible impact on profits in a low loss environment). I also added risks outside of the 99.5%VaR/99%T-VaR regulatory levels whilst increasing the profit profile to reflect an increase in risk appetite to reflect pressures to maintain target profits. This resulted in a decrease in expected profit of approx. 20% and an increase in the 99.5%VaR and 99.5%T-VaR of 45% and 50% respectively. The impact on ROEs (being expected profit divided by capital at 99.5%VaR or T-VaR) shows that a headline 15% can quickly deteriorate to a 7-8% due to loosening of T&Cs and the addition of some tail risk.

click to enlargeTails of VaR

For what it is worth, T-VaR (despite its shortfalls) is my preferred metric over VaR given its relative superior measurement of tail risk and the 99.5%T-VaR is where I would prefer to analyse firms to take account of accumulating downside risks.

The above exercise reflects where I suspect the market is headed through 2015 and into 2016 (more risky profiles, lower operating ROEs). As Solvency II will come in from 2016, introducing the deeply flawed VaR metric at this stage in the market may prove to be inappropriate timing, especially if too much reliance is placed upon VaR models by investors and regulators. The “full detail of the real world” today and in the future is where the focus of such stakeholders should be, with much less emphasis on what the models, calibrated on what came before, say.

Munich’s Underwriting Cycle

Munich Re had a good set of results last week with a 12.5% return on equity on a profit of €3.3 billion (with the reinsurance business contributing €2.8 billion of the profit). A €1 billion share buyback was also announced contributing to the ongoing shareholder friendly actions by industry players. Munich is targeting €3 billion for 2014 but warned of challenges ahead including “the lingering low-interest-rate environment, increasing competition in reinsurance, and changes in demand from clients in primary insurance”.

Torsten Jeworrek, Munich Re’s Reinsurance CEO, cited tailor-made solutions as a strength for Munich highlighting “multi-year treaties (occasionally incorporating cross-line and cross-regional covers), retroactive reinsurance solutions, transactions for capital relief, comprehensive consultation on capital management, and the insurance of complex liability, credit and large industrial risks”.

Whilst looking through the 2013 report, I noticed historical calendar year combined ratios (COR) for the P&C business (reinsurance & primary) including and excluding catastrophes. I dug up these figures going back to 1991 as per the graph below. A small amount of adjustment was needed, particularly in relation to the 24.3% and 17.1% of deterioration for 2001 and 2002 relating to 9/11 losses (which I included as catastrophes in the CaT ratio for those years). As with a previous post on underwriting cycles, I then “normalised” the COR excluding catastrophes for the changes in interest rates using a crude discount measure based upon the US risk free rate for each calendar year plus 150 bps over 2.5 years. That may be conservative, particularly for the 1990s where equities were a bigger part of European’s asset portfolio. I then added the (undiscounted) CaT ratio to the discounted figures to give an idea of the historical underwriting cycle.

click to enlargeMunich Underwriting Cycle

The “normalised” average discounted COR (excluding CaT) since 1991 is 87% and the average over the past 10 years is 83%. The standard deviation for the series since 1991 is 6% and for the last 10 years 4% indicating a less volatile period in recent years in core ratios excluding catastrophes.

The average CaT ratio since 1991 is 7% versus 9% over the past 10 years. The standard deviation for the CaT ratio since 1991 is 8% and for the last 10 years 9% indicating a more volatile period in recent years in CaT ratios.

Adding the discounted CORs and the (undiscounted) CaT ratios, the average since 1991 and over the past 10 years is 95% and 92% respectively (with standard deviation of 11% and 9% respectively).

As Munich is the largest global reinsurer, the ratios (reinsurance & primary split approx 80%:20%) above represent a reasonable cross section of industry and give an average operating return of 5% to 8% depending upon the time period selected. Assuming a 0.5% risk free return today, that translates into a rough risk adjusted return as per the Sharpe ratio of 0.44 and 0.80 for the period to 1991 and over the past 10 years respectively. Although the analysis is crude and only considers operating results, these figures are not exactly earth-shattering (even if you think the future will be more like the last 10 years rather than the longer term averages!).

Such results perhaps explain the growing trend of hedge funds using reinsurance vehicles as “float” generators. If the return on assets over risk free is increased from the 150 bps assumed to 300 bps in the analysis above, the Sharpe ratios increase to more acceptable 0.73 and 1.13 respectively. And that ignores the tax benefits amongst other items!

As an aside, I again (as per this post) compared the underlying discounted COR (excluding catastrophes) from Munich against a credit index of global corporate defaults (by originating year as a percentage of the 1991 to 2013 average) in the graph below. As a proxy for the economic & business cycles, it illustrates an obvious connection.

click to enlargeMunich Underwriting & Credit Cycle

Insurance ROEs earned the hard way

Munich kicked off the year end reporting season for insurers this week with a pre-announcement of results that beat their guidance. For non-life reinsurance, low large and catastrophe losses plus 5% of prior year releases mean that the 92% combined ratio is only 1% higher than 2012 for Munich Re despite the weak pricing market.

I am expecting to see strong non-life results across the market as it looks like attritional loss ratios for 2013 are lower than average which, with low catastrophe losses, should make for low combined ratios in 2013.

For specialty nonlife insurers and reinsurers, I would expect combined ratios to come in the mid to high eighties on average with ROEs in the low to mid teens. The relatively low investment returns are hurting ROEs which in the past would of given high teens or low twenties for such underwriting ratios.

The business models of the European composite reinsurers are not as sensitive to combined ratio with the life side providing more stable earnings. I would expect most of the large composite reinsurers to come in in the low 90s or high 80s (Munich’s figure was 92%) whilst giving ROEs similar to their non-life specialty brothers in the low to mid teens.

The graph below illustrates that todays combined ratios don’t mean the high ROEs they once did (2013 figures are as at Q3).

click to enlargeInsurance ROEs and Combined Ratios 2004 to 2013


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.