Tag Archives: insurance linked securities

Befuddled Lloyd’s

Lloyd’s of London always provides a fascinating insight into the London insurance market and beyond into the global specialty insurance market, as this previous post shows. It’s Chairman, Bruce Carnegie-Brown, commented in their 2017 annual report that he expects “2018 to be another challenging year for Lloyd’s and the Corporation continues to refine its strategy to address evolving market conditions”. Given the bulking up of many of its competitors through M&A, Willis recently called it a reinvigoration of the “big balance sheet” reinsurance model, Lloyd’s needs to get busy sharpening its competitive edge. In a blunter message Brown stressed that “the market’s 2017 results are proof, if any were needed, that business as usual is not sustainable”.

A looked at the past 15 years of underwriting results gives an indicator of current market trends since the underwriting quality control unit, called the Franchise Board, was introduced at the end of 2002 after the disastrous 1990’s for the 330-year-old institution.

click to enlarge

The trend of increasing non-CAT loss ratios after years of soft pricing coupled with declining prior year reserve releases is clear to see. That increases the pressure on the insurance sector to control expenses. To that end, Inga Beale, Lloyd’s CEO, is pushing modernisation via the London Market Target Operating Model programme hard, stating that electronic placement will be mandated, on a phased basis, “to speed up the adoption of the market’s modernisation programme, which will digitise processes, reduce unsustainable expense ratios, and make Lloyd’s more attractive to do business with”.

The need to reduce expenses in Lloyd’s is acute given its expense ratio is around 40% compared to around 30% for most of its competitors. Management at Lloyd’s promised to “make it cheaper and easier to write business at Lloyd’s, enabling profitable growth”. Although Lloyd’s has doubled its gross premium volumes over the past 15 years, the results over varying timeframes below, particularly the reducing underwriting margins, show the importance of stressing profitable growth and expense efficiencies for the future.

click to enlarge

A peer comparison of Lloyd’s results over the past 15 years illustrates further the need for the market to modernise, as below. Although the 2017 combined ratio for some of the peer groupings have yet to finalised and published (I will update the graph when they do so), the comparison indicates that Lloyd’s has been doing worse than its reinsurance and Bermudian peers in recent years. It is suspicious to see, along with the big reinsurers and Bermudians, Lloyd’s included Allianz, CNA, and Zurich (and excluded Mapfe) in their competitor group from 2017. If you can’t meet your target, just change the metric behind the target!

click to enlarge

A recent report from Aon Benfield shows the breakdown of the combined ratio for their peer portfolio of specialist insurers and reinsurers from 2006 to 2017, as below.

click to enlargeAon Benfield Aggregate Combined Ratio 2006 to 2017

So, besides strong competitors, increasing loss ratios and heavy expense loads, what does Lloyd’s have to worry about? Well, in common with many, Lloyd’s must contend with structural changes across the industry as a result of, in what Willis calls in their latest report, “the oversupply of capital” from investors in insurance linked securities (ILS) with a lower cost of capital, whereby the 2017 insured losses appears to have had “no impact upon appetite”, according to Willis.

I have posted many times, most recently here, on the impact ILS has had on property catastrophe pricing. The graph of the average multiple of coupon to expected loss on deals monitored by sector expert Artemis again illustrates the pricing trend. I have come up with another angle to tell the story, as per the graph below. I compared the Guy Carpenter rate on line (ROL) index for each year against an index of the annual change in the rolling 10-year average global catastrophe insured loss (which now stands at $66 billion for 2008-2017). Although it is somewhat unfair to compare a relative measure (the GC ROL index) against an absolute measure (change in average insured loss), it makes a point about the downward trend in property catastrophe reinsurance pricing in recent years, particularly when compared to the trend in catastrophic losses. To add potentially to the unfairness, I also included the rising volumes in the ILS sector, in an unsubtle finger point.

click to enlarge

Hilary Weaver, Lloyd’s CRO, recognises the danger and recently commented that “the new UK ILS regulation will, if anything, increase the already abundant supply of insurance capital” and “this is likely to mean that prices remain low for many risks, so we need to remain vigilant to ensure that the prices charged for them are proportionate to the risk”.

The impact extends beyond soft pricing and could impact Lloyd’s risk profile. The loss of high margin (albeit not as high as it once was) and low frequency/high severity business means that Lloyd’s will have to fish in an already crowded pond for less profitable and less volatile business. The combined ratios of Lloyd’s main business lines are shown below illustrating that all, except casualty, have had a rough 2017 amid competitive pressures and large losses.

As reinsurance business is commoditised further by ILS, in a prelude to an increase in machine/algorithm underwriting, Lloyd’s business will become less volatile and as a result less profitable. To illustrate, the lower graph below shows Lloyd’s historical weighted average combined ratio, using the 2017 business mix, versus the weighted average combined ratio excluding the reinsurance line. For 2003 to 2017, the result would be an increase in average combined ratio, from 95.8% to 96.5%, and a reduction in volatility, the standard deviation from 9.7% to 7%.

click to enlarge

To write off Lloyd’s however would be a big mistake. In my view, there remains an important role for a specialist marketplace for heterogeneous risks, where diverse underwriting expertise cannot be easily replicated by machines. Lloyd’s has shown its ability in the past to evolve and adapt, unfortunately however usually when it doesn’t have any choice. Hopefully, this legendary 330-year-old institution will get ahead of the game and dictate its own future. It will be interesting to watch.

 

Epilogue – Although this analogy has limitations, it occurs to me that the insurance sector is at a stage of evolution that the betting sector was at about a decade ago (my latest post on the sector is here). Traditional insurers, with over-sized expenses, operate like old traditional betting shops with paper slips and manual operations. The onset of online betting fundamentally changed the way business is transacted and, as a result, the structure of the industry. The upcoming digitalisation of the traditional insurance business will radically change the cost structure of the industry. Lloyd’s should look to the example of Betfair (see an old post on Betfair for more) as a means of digitalising the market platform and radically reducing costs.

Follow-on 28th April – Many thanks to Adam at InsuranceLinked for re-posting this post. A big welcome to new readers, I hope you will stick around and check out some other posts from this blog. I just came across this report from Oliver Wyam on the underwriter of the future that’s worth a read. They state that the “commercial and wholesale insurance marketplaces are undergoing radical change” and they “expect that today’s low-price environment will continue for the foreseeable future, continuing to put major pressure on cost“.

CAT Calls

Following on from a recent post on windstorms in the US, I have taken several loss preliminary estimates recently published by firms (and these are very early estimates and therefore subject to change) and overlaid them against the South-East US probable maximum loss (PML) curves and Atlantic hurricane scenarios previously presented, as below. The range of insured losses for Harvey, Irma and Maria (now referred to as HIM) are from $70 billion to $115 billion, averaging around $90 billion.

click to enlarge

The loss estimates by firm depend heavily upon the risk profile of each. As a generalisation, it could be said that the aggregate US wind losses are averaging around the 1 in 100 loss level.

Given there was over $20 billion of insured losses from H1 and factoring in developing losses such as the Mexico earthquake, the California wildfires and the current windstorm Ophelia hitting Ireland, annual insured losses for 2017 could easily reach $120 billion. The graph below shows the 2016 estimates from Swiss Re and my $120 billion 2017 guesstimate (it goes without saying that much could still happen for the remainder of the year).

click to enlarge

At a $120 billion level of insured loss for 2017, the 10 year average increase from around $55 billion to $65 billion. In a post in early 2016, I estimated that catastrophe pricing was about 25% too low based upon annual average losses of $40 billion per year. We will see whether the 2017 losses are enough to deplete the overcapitalisation in the market and return pricing towards their technical rate. I wouldn’t hold my breath on that as although there may be material aggregate losses in the private collateralised market and other pockets of the retrocession market, the appetite of yield seeking investors will likely remain unabated in the current interest rate environment.

Although the comparison between calendar year ratios and credit defaults is fraught with credibility issues (developed accident year ratios to developed default rates are arguably more comparable), I updated my previous underwriting cycle analysis (here in 2014 and here in 2013). Taking the calendar year net loss ratios of Munich Re and Lloyds of London excluding catastrophe and large losses (H1 results for 2017), I then applied a crude discount measure using historical risk-free rates plus 100 basis points to reflect the time value of money, and called the resulting metric the adjusted loss ratio (adjusted LR). I compared these adjusted LRs for Munich and Lloyds to S&P global bond credit default rates (by year of origin), as per the graph below.

click to enlarge

This shows that the years of relatively benign attritional claims together with the compounding impact of soft pricing over the past years may finally be coming to an end. Time will tell. All in all, it makes for a very interesting period for the market over the next 6 to 12 months.

In the interim, let’s hope for minimal human damage from the current California wildfires and windstorm Ophelia.

The Big Wind

With four US hurricanes and one earthquake in current times, mother nature is reminding us homo-sapiens of her power and her unpredictability. As the massive Hurricane Irma is about to hit Florida, we all hope that the loss of life and damage to people’s lives will be minimal and that the coming days will prove humane. Forgive me if it comes across as insensitive to be posting now on the likely impact of such events on the insurance industry.

For the insurance sector, these events, and particularly Hurricane Irma which is now forecast to move up the west coast of Florida at strength (rather the more destruction path of up the middle of Florida given the maximum forces at the top right-hand side of a hurricane like this one), may be a test on the predictive powers of its models which are so critical to pricing, particularly in the insurance linked securities (ILS) market.

Many commentators, including me (here, here and here are recent examples), have expressed worries in recent years about current market conditions in the specialty insurance, reinsurance and ILS sectors. On Wednesday, Willis Re reported that they estimate their subset of firms analysed are only earning a 3.7% ROE if losses are normalised and reserve releases dried up. David Rule of the Prudential Regulatory Authority in the UK recently stated that London market insurers “appear to be incorporating a more benign view of future losses into their technical pricing”, terms and conditions continued to loosen, reliance on untested new coverages such as cyber insurance is increasing and that insurers “may be too sanguine about catastrophe risks, such as significant weather events”.

With the reinsurance and specialty insurance sectors struggling to meet their cost of capital and pricing terms and conditions being so weak for so long (see this post on the impact of soft pricing on risk profiles), if Hurricane Irma impacts Florida as predicted (i.e. on Saturday) it has the potential to be a capital event for the catastrophe insurance sector rather than just an earnings event. On Friday, Lex in the FT reported that the South-East US makes up 60% of the exposures of the catastrophe insurance market.

The models utilised in the sector are more variable in their output as events get bigger in their impact (e.g. the higher the return period). A 2013 post on the variation in loss estimates from a selected portfolio of standard insurance coverage by the Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) illustrates the point and one of the graphs from that post is reproduced below.

click to enlarge

Based upon the most recent South-East US probable maximum losses (PML) and Atlantic hurricane scenarios from a group of 12 specialty insurers and reinsurers I selected, the graph below shows the net losses by return periods as a percentage of each firm’s net tangible assets. This graph does not consider the impact of hybrid or subordinate debt that may absorb losses before the firm’s capital. I have extrapolated many of these curves based upon industry data on US South-East exceedance curves and judgement on firm’s exposures (and for that reason I anonymised the firms).

click to enlarge

The results of my analysis confirm that specialty insurers and reinsurers, in aggregate, have reduced their South-East US exposures in recent years when I compare average figures to S&P 2014 data (by about 15% for the 1 in 100 return period). Expressed as a net loss ratio, the average for a 1 in 100  and a 1 in 250 return period respectively is 15% and 22%. These figures do look low for events with characteristics of these return periods (the average net loss ratio of the 12 firms from catastrophic events in 2005 and 2011 was 22% and 25% respectively) so it will be fascinating to see what the actual figures are, depending upon how Hurricane Irma pans out. Many firms are utilising their experience and risk management prowess to transfer risks through collaterised reinsurance and retrocession (i.e. reinsurance of reinsurers) to naïve capital market ILS investors.

If the models are correct and maximum losses are around the 1 in 100 return period estimates for Hurricane Irma, well capitalized and managed catastrophe exposed insurers should trade through recent and current events. We will see if the models pass this test. For example, demand surge (whereby labour and building costs increase following a catastrophic event due to overwhelming demand and fixed supply) is a common feature of widespread windstorm damage and is a feature in models (it is one of those inputs that underwriters can play with in soft markets!). Well here’s a thought – could Trump’s immigration policy be a factor in the level of demand surge in Florida and Texas?

The ILS sector is another matter however in my view due to the rapid growth of the private and unregulated collateralised reinsurance and retrocession markets to satisfy the demand for product supply from ILS funds and yield seeking investors. The prevalence of aggregate covers and increased expected loss attachments in the private ILS market resembles features of previous soft and overheated retrocession markets (generally before a crash) in bygone years. I have expressed my concerns on this market many times (more recently here). Hurricane Irma has the potential to really test underwriting standards across the ILS sector. The graph below from Lane Financial LLC on the historical pricing of US military insurer USAA’s senior catastrophe bonds again illustrates how the market has taken on more risk for less risk adjusted premium (exposures include retired military personnel living in Florida).

click to enlarge

The events in the coming days may tell us, to paraphrase Mr Buffet, who has been swimming naked or as Lex put it on Friday, “this weekend may be a moment when the search for uncorrelated returns bumps hard into acts of God”.

Hopefully, all parts of the catastrophe insurance sector will prove their worth by speedily indemnifying peoples’ material losses (nothing can indemnify the loss of life). After all, that’s its function and economic utility to society. Longer term, recent events may also lead to more debate and real action been taken to ensure that the insurance sector, in all its guises, can have an increased economic function and relevance in an increasingly uncertain world, in insuring perils such as floods for example (and avoiding the ridiculous political interference in risk transfer markets that has made the financial impact of flooding from Hurricane Harvey in Texas so severe).

Notwithstanding the insurance sector, our thoughts must be with the people who will suffer from nature’s recent wrath and our prayers are with all of those negatively affected now and in the future.

ILS illuminations

Insurance linked securities (ILS) are now well established in the insurance industry. ILS as an asset class offer, according to its many fans, the benefits of diversification and low correlation to other asset classes whilst offering a stable and attractive risk/reward return. The impact of the new capital on the traditional market has been profound and wide ranging (and a much posted upon topic in this blog – here, here & here for example).

ILS fund managers maintained an “aggressive posture” on price at the recent April renewals according to Willis Re as ILS capacity continues to demonstrate its cost of capital advantage. ILS fund managers are also looking to diversify, moving beyond pure short tail risks and looking at new previously uninsured or underinsured exposures, as well as looking to move their capital along the value-chain by sourcing primary risk more directly and in bulk.

An industry stalwart, John Kavanagh of Willis Re, commented that “with results on many diversifying non-catastrophe classes now marginal, there is greater pressure on reinsurers to address the pricing in these classes” and that “many reinsurers remain prepared to let their top line revenue growth stall and are opting to return excess capital to their shareholders”. The softening reinsurance market cycle is now in its fifth year and S&P estimates that “even assuming continued favourable prior-year reserve releases and benign natural catastrophe losses, we anticipate that reinsurers will barely cover their cost of capital over the next two years”.

Rather than fight the new capital on price, some traditional (re)insurers are, according to Brandan Holmes of Moody’s, “deploying third-party capital in their own capital structures in an effort to lower their blended cost of capital” and are deriving, according to Aon Benfield, “significant benefits from their ability to leverage alternative capital”. One can only fight cheap capital for so long, at some stage you just arbitrage against it (sound familiar!).

A.M. Best recently stated that “more collateralised reinsurance programs covering nonpeak exposures are ceded to the capital markets”. The precipitous growth in the private transacted collateralised reinsurance subsector can be seen in the graph from Aon below.

click to enlarge

Nick Frankland of Guy Carpenter commented that “the capital landscape is ever-changing” and that “such capital diversity also elevates the position of the broker”. Some argue that the all-powerful role of the dominant brokers is exacerbating market softness. These brokers would counterargue that they are simply fulfilling their role in an efficient market, matching buyers and sellers. As Frankland puts it, brokers are “in the strongest position to provide access to all forms of capital and so secure the more beneficial rates and terms and conditions”. Dominic Christian of Aon Benfield commented last year that “to some extent alternative sources of capital are already, and have already uberized insurance and reinsurance, by bringing increased sources of supply”.

Perhaps alone amongst industry participants, Weston Hicks of Alleghany, has questioned the golden goose of cheap ILS capital stating that “some new business models that separate the underwriting decision from the capital provider/risk bearer are, in our view, problematic because of a misalignment of incentives”. Such concerns are batted aside as old fashioned in this new world of endless possibilities. Frighteningly, John Seo of ILS fund manager Fermat Capital, suggests that “for every dollar of money that you see in the market right now, I think there is roughly 10 dollars on the sidelines waiting to come in if the market hardens”.

As an indicator of current ILS pricing, the historical market spread over expected losses in the public CAT bond market can be seen in the exhibit below with data sourced from Lane Financial. It is interesting to note that the average expected loss is increasing indicating CAT bonds are moving down the risk towers towards more working layer coverages.

click to enlarge

In a previous post, I argued that returns from an ILS fund index, with the net returns judgementally adjusted to get to comparable figures gross of management fees, were diverging against those from a pure CAT bond index. I argued that this divergence may illustrate that the ILS funds with exposure to the private collateralised reinsurance sector may be taking on higher risk exposures to pump returns (or may be passing risks amongst themselves in an embryonic spiral) and that ILS investors should be careful they understand the detail behind the risk profiles of the ILS funds they invest in.

Well, the final 2016 figures, as per the graph below, show that the returns in my analysis have in fact converged rather than diverged. On the face of it, this rubbishes my argument and I have to take that criticism on. Stubbornly, I could counter-argue that the ILS data used in the comparison may not reflect the returns of ILS funds with large exposure to collateralised reinsurance deals. Absent actual catastrophic events testing the range of current fund models, better data sources are needed to argue the point further.

click to enlarge

In their annual review of 2016, Lane Financial have an interesting piece on reducing transparency across both the public and private ILS sector. They characterise the private collateralised reinsurance sector as akin to a dark pool compared to the public CAT bond market which they likened to a lit exchange. Decreased transparency across the ILS sector “should send up warning flags” for all market participants as it makes calculating Net Asset Valuations (NAV) with monthly or quarterly frequency more difficult. They argue that the increased use of a relatively smaller public CAT bond market for pricing points across the ILS sector, the less credible is the overall valuation. This is another way of expressing my concern that the collateralised reinsurance market could be destabilising as it is hidden (and unregulated).

In the past, as per this post, I have questioned how the fully funded ILS market can claim to have a lower cost of capital against rated reinsurers who only have to hold capital against a percentage of their exposed limit, akin to fractional banking (see this post for more on that topic). The response is always down to the uncorrelated nature of ILS to other asset classes and therefore its attraction to investors such as pension funds who can apply a low cost of capital to the investment due to its uncorrelated and diversifying portfolio benefits. Market sponsors of ILS often use graphs such as the one below from the latest Swiss Re report to extoll the benefits of the asset class.

click to enlarge

A similar exhibit, this time from a Lombard Odier brochure, from 2016 shows ILS in an even more favourable light!

click to enlarge

As anybody who has looked through any fund marketing metrics knows, performance comparisons with other investment strategies are fraught with bias and generally postdictive. The period over which the comparison is made and the exact indices chosen (look at the differing equity indices used in the comparisons above) can make material differences. Also, the size and liquidity of a market is important, a point which may negate any reliance on ILS returns prior to 2007 for example.

I thought an interesting exercise would be to compare actual historical ILS returns, as represented by the Swiss Re Global Cat Bond Total Return Index, against total returns (i.e. share price annual change plus dividends paid in year) from equity investment in reinsurers across different time periods. The most applicable business model for comparison would be pure property catastrophe reinsurers but unfortunately there are not many of them left.

I have chosen RenRe (RNR) and Validus (VR), from 2007, as representatives of the pure property cat business model, although both have diversified their portfolios away from pure short tail business in recent years. I also selected three of the biggest European reinsurers – Munch Re, Swiss Re and Hannover Re – all of which are large diverse composite reinsurers. Finally, I constructed a US$ portfolio using equal shares of each of the five firms mentioned above (RenRe represents 40% of the portfolio until 2007 when Validus went public) with the € and CHF shares converted at each year end into dollars.

The construction of any such portfolio is postdictive and likely suffers from multiple biases. Selecting successful firms like RenRe and Validus could validly be criticised under survival bias. To counter such criticism, I would point out that the inclusion of the European reinsurers is a considerable historic drag on returns given their diverse composite footprint (and associated correlation to the market) and the exclusion of any specialist CAT firm that has been bought out in recent years, generally at a good premium, also drags down returns.

The comparison over the past 15 years, see graph below, shows that Munich and Swiss struggle to get over their losses from 2002 and 2003 and during the financial crisis. Hannover is the clear winner amongst the Europeans. The strong performance of Hannover, RenRe and Validus mean that the US$ portfolio matches the CAT bond performance after the first 10 years, albeit on a more volatile basis, before moving ahead on a cumulative basis in the last 5 years. The 15-year cumulative return is 217% for the CAT bond index and 377% return for the US$ equity portfolio.

click to enlarge

The comparison over the past 10 years, see graph below, is intriguing. Except for Validus, the CAT bond index beats all other firms and the US$ portfolio for non-volatile returns hands down in the first 5 years. Hannover, Validus and the portfolio each make a strong comeback in the most recent 5 years. The 10-year cumulative return is 125% for the CAT bond index and 189% return for the US$ equity portfolio.

click to enlarge

The comparison over the past 5 years, see graph below, shows that all firms and the portfolio handily beats the CAT bond index. Due to an absence in large loss activity over the recent past and much more shareholder friendly actions by all reinsurers, the equity returns have been steady and non-volatile. The 5-year cumulative return is 46% for the CAT bond index and 122% return for the US$ equity portfolio.

click to enlarge

Overall then, ILS may offer less volatile and uncorrelated returns but I would personally prefer the, often lumpier, historical equity returns from a selected portfolio of top reinsurers in my pension pot (we all could have both in our pension funds!). Then again, the influx of new capital into ILS has put the future viability of the traditional reinsurance business models into question so future equity returns from the sector may not be too rosy.

At the end of the day, the bottom line is whether current market risk premia is adequate, irrespective of being supplied by ILS fund managers or traditional reinsurers. Based upon what I see, I have grave misgivings about current market pricing and therefore have no financial exposure, ILS or equity or otherwise, to the market at present.

Additional Comment, 29th April 2017: The ILS website Artemis.bm had an interesting piece on comments from Torsten Jeworrek of Munich Re during their March conference call. The applicable comment is as follows:

“And now I give you another example, which is not innovation per se or not digitalization, but you know that more and more alternative capital came into the insurance industry over the last years; hedge funds, pension refunds, participating particularly in the cat business and as a trend that not all of the limits they provide, cat limits are fully collateralized anymore. That means there are 10 scenarios; hurricane, earthquake, [indiscernible], and so on; which are put together, but not 10 times the limit is collateralized, let’s say only 4 times, 5 times.

That means these hedge funds and pension funds so to speak in the future if they don’t have to provide full 100% collateralized for all the limits they provide, they need a certain credit risk for the buyer. The more they entertain, the more there’s a likelihood that this reinsurance can also fail. The question is how far will that go and this kind of not fully collateralized reinsurance, will that be then accepted as a reinsurance by the regulator or will that be penalized at a certain time otherwise we don’t have level playing field anymore, which means the traditional reinsurer who was strongly monitored and regulated and also reported as really expensive and a burden for our industry and for us and on the other hand, you have very lean pension and hedge funds who even don’t have to provide the same amount of capital for the same risk.”

Pimping the Peers (Part 2)

In the last post on this topic, I highlighted how new technologies, broadly under the fintech tag, had the potential to disrupt the banking sector, primarily by means of automating processes rather than any major reinventing of business models (although I did end that post with a bit of a rant about innovation and human behaviour). Blockchain is the hot topic that seems to be cropping up everywhere (I’ll leave that for another time). This post is about insurance and new technology, or in the jargon, insurtech.

The traditional business model in the insurance industry is not reacting well to a world of low or negative interest rates. For the life insurance sector, the duration mismatch between their liabilities and their assets is having a perverse impact as interest rates have fallen. Savings returns for aging populations have been sacrificed in Central Bank’s attempt to stimulate economic growth.

In addition, the traditional distribution channel for selling life insurer’s products, and the old adage is that these products are sold rather than bought, has relied too heavily on aging tied agents whose focus is on the wealthy client that can generate more fees than the middle class. The industry is generally at a loss on how to sell products in a low interest world to the mass market and to the new tech savvy generation. As a result, the industry and others are throwing money at a rash of new start-ups in insurance, as the exhibit on some of the current hyped firms focusing on life insurance below illustrates.

click to enlargelife-insurance-big-data

As the exhibit illustrates, the focus of these new start-ups is weighted towards technologies around product development, distribution, and underwriting. Some will likely succeed in trying to differentiate further the existing clientele of life insurers (e.g. real time health data). Many will be gobbled up or disappear. Differing attitudes between those aged under 34 and the older generation towards online distribution channels can be clearly seen in the survey results in the exhibit below.

click to enlargeattitudes-to-life-insurance-distribution-channels

With longevity and low interest rates the dominant challenges for life insurers today, automation of processes will assist in cutting expenses in the provision of products (mainly to the existing customer base) but will not likely meaningfully address the twin elephants in the room.  Citigroup reckons that in 20 of the largest OECD countries the unfunded government liability for pensions is around $78 trillion which compares to approximately $50 trillion in GDP for all OECD countries in 2015. I look forward to conversing with a robo-advisor in the near future on what products it recommends for that problem!

Insurance itself is hundreds of years old and although the wonderfully namely bottomry (the earliest form of marine hull insurance) or ancient burial societies are early examples, non-life insurance really took off with mass markets after the great fire of London in 1666.

The most hyped example of insurtech in the non-life sector is the impact of technologies on the motor business like drive-less cars and car telematics. This paper from Swiss Re shows that the impact over the next 20 years of such advances on motor premia could be dramatic.

Much of the focus from insurtech innovation is on reducing expenses, an item that the industry is not light on. The graph below shows examples of the level of acquisition and overhead expenses in the non-life sector across different jurisdictions.

click to enlargenonlife-expense-ratios

A recent report from Aon Benfield went further and looked at expenses across the value chain in the US P&C insurance sector, as below. Aon Benfield estimated overall expenses make up approximately half of gross risk premium, much of which represents juicy disruption targets for new technology in the insurtech world.

click to enlargeexpenses-across-the-value-chain

Insurance itself is based upon the law of large numbers and serves a socially useful function in reducing economic volatility by transferring risks from businesses and consumers. In 1906, Alfred Manes defined insurance as “an economic institution resting on the principle of mutuality, established for the purpose of supplying a fund, the need for which arises from a chance occurrence whose probability can be estimated”.

One of the issues identified with the current non-life insurance sector is the so-called protection gap. This is in effect where insurers’ risk management practises have got incredibly adapt at identifying and excluding those risks most likely to result in a claim. Although good for profits, it does bring the social usefulness of the transference of only the pristine risks into question (for everybody else). The graph below from Swiss Re illustrates the point by showing economic and insured losses from natural catastrophe events as a % of GDP.

click to enlargeinsurance-protection-gap-uninsured-vrs-insured-losses

It’s in the context of low investment returns and competitive underwriting markets (in themselves being driven by low risk premia across asset classes) that a new technology driven approach to the mutual insurance model is being used to attack expense and protection gap issues.

Mutuals represent the original business model for many insurers (back to burial schemes and the great fire of 1666) and still represent approximately a third of the sector in the US and Europe today. Peer to peer insurers are what some are calling the new technology driven mutuals. In fact, most of the successful P2P models to date, firms like Guevara, Friendsurance, and Inspeer are really intermediaries who pool consumers together for group discounts or self-financing of high deductibles.

Lemonade, which launched in New York this week, is a peer to peer platform which issues its own insurance policies and seeks to address the protection gap issue by offering broader coverage. The firm has been heavily reinsured by some big names in insurance like Berkshire Hathaway and Lloyd’s. It offers a fee based model, whereby the policyholders pay claims through mutualisation (assumingly by pools determined by pre-defined criteria). Daniel Schreiber, CEO and co-founder of Lemonade says that the firm will be ”the only insurer that doesn’t make money by denying claims”. Dan Ariely, a big deal in the world of Behavioral Economics, has been named as Chief Behavioral Officer, presumably in an effort to assist in constructing pools of well behaved policyholders.

The graphic below tries to illustrate how the business model is evolving (or should that be repeating?). Technology offers policyholders the opportunity to join with others to pool risk, hitherto a process that was confined to associations amongst professional groups or groups bound by location. Whether technology offers the same opportunity to underwrite risks profitably (or at least not at a loss) but with a larger reach remains to be seen.

click to enlargeinsurance-business-models

It does occur to me that it may be successful in addressing areas of dislocation in the industry, such as shortfalls in coverage for flood insurance, where a common risk and mitigant can be identified and addressed in the terms of the respective pool taking the risks on.

For specialty re/insurers, we have already seen a bifurcation between the capital providers/risk takers and the risk portfolio managers in the ILS arena. Newer technology driven mutual based insurers also offer the industry a separation of the management of risk pools and the risk capital provided to underwrite them. I wish them well in their attempts at updating this most ancient of businesses and I repeat what I said in part 1 of this post – don’t let the sweet scent of shiny new technology distract you from the smell of the risk…..