In recent months, we have witnessed a series of significant events producing large — and mostly uninsured — economic losses. The Equifax data breach exposed personally identifiable information from more than 140 million consumers; there were tens of billions of dollars in flood losses from Hurricanes Harvey and Irma; and the damage costs from long-term power outages and business interruption losses stemming from Hurricane Maria’s devastation in Puerto Rico are still being calculated. All those underscore the low level of insurance penetration for perils like flood, cyber and contingent business interruption even in the U.S., one of the most highly insured economies in the world.
Spurred by the growth of new technologies, the advent of new business models reliant on increasingly complex supply chains and the dynamic forces of climate change, emerging risks such as these have become increasingly important to consumers and businesses around the world. At a recent industry gathering, Mike McGavick, CEO of XL Catlin, asked how the insurance industry can remain relevant to its customers when it has seemed unable to develop insurance products to protect against some of the most critical risks facing policyholders in our modern, connected economy.
It is an important question.
While the insurance industry’s development of new products has typically lagged in the changes in technology and risk environment that drive demand for protection, the wave of new products, business processes and companies from insurtech startups can help insurance industry incumbents to accelerate their response to a changing risk environment. There are three categories of insurtech innovation that will be critical to this evolution: data, analytics platforms and tradable risk.
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Over time, free-market economies have evolved in ways to manage a variety of risks through the use of insurance. But the fundamental nature of emerging risks has challenged the insurance industry’s ability to develop new insurance products and price those products using historical data that actuaries typically rely upon to parameterize their pricing models. Even if such historical data existed, it would have limited predictive value for emerging and changing risks such as cyber because of the dynamic nature of the risk, as hackers constantly develop new methods to evade security and more and more of our intellectual and physical assets become interconnected through the internet. And the forces of climate change are quickly rendering historical data sets obsolete — even for classes of risk like hurricanes that have been considered to be well-understood.
A number of innovative companies, both insurtech startups and a few more established enterprises, are building new platforms and data collection modalities designed to enhance the amount, granularity and quality of underwriting data for a broad range of traditional and emerging classes of risk. Companies like reThought Insurance (US flood insurance MGA), Audeamus Risk (a platform for managing and underwriting operational risk) and both Cyence and Symantec in the cyber risk area are collecting unprecedented amounts of data, including new data elements that can provide real-time indicators of changes in risk profiles in these areas. Other new technologies including sensors, wearables, telematics and social media networks can capture types and quantities of data far beyond what insurers have used to set premium rates and loss reserves. These new datasets can provide insurance and reinsurance companies with more extensive amounts of data and real-time information, allowing a carrier to track and monitor its policyholders with far more timely and actionable information than has previously been available.
Increased quantity and quality of exposure data is a prerequisite to insuring emerging risks, but making sense of this tsunami of data requires other forms of innovation. Developments in artificial intelligence and machine learning provide new tools that can allow insurers and investors to filter vast data sets to isolate the variables with the most predictive value in signaling relationships between exposure and claim activity.
But improvements in data collection and analytics alone are not sufficient to provide the risk-bearing capacity needed to accommodate emerging risks with the sheer volumes of exposure to loss of flood, cyber and contingent business interruption. A new approach is needed to develop vehicles through which the risk burden — and profit potential — can be spread beyond the insurance industry to tap into deeper pools of capital. The capital markets are great for this kind of creativity, as evidenced by the creation and development of asset-backed securities markets over the past 40 years, which brought liquidity to markets for mortgages, credit cards and auto loans.
Since the 1990s, the insurance industry, where reinsurers historically have served as the “lenders of last resort,” has seen the emergence of capital market solutions to manage accumulations of risk. These have taken the form of so-called “alternative capital” products that have enabled hedge and pension funds to assume property reinsurance risk through catastrophe bonds and similar vehicles. In recent years, these products have served to dramatically decrease the cost of capital in the catastrophe reinsurance market while creating a high-yielding investment opportunity whose returns are uncorrelated with equities or interest rates.
At Extraordinary Re we have built a trading platform for insurance risk, initially targeting “extraordinary” risk classes such as cyber and flood. By embedding our trading platform inside a reinsurance company, we bridge the insurance and capital market worlds, enabling insurers to transfer accumulations of risk to institutional investors in the form of tradable reinsurance. This innovation allows investors to assume risk in a liquid market with the ability to control the amount and types of risk and the timeframe over which that risk is carried. That permits the allocation of capital in a more flexible manner than is possible in the insurance industry, which takes a “buy and hold” approach to underwriting risk. It will even become possible for different investors to hold shares of a single reinsurance risk at different points in the lifespan of that risk between policy inception and the date when the last claim is settled. A trading market allows risk to be allocated to the most efficient (and lowest cost) capital provider throughout the term of each risk.
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The creation of this risk-transfer market produces a new source of data that will provide new benchmarks for pricing and valuation, leading to new product development efforts among the insurance companies originating the risk. Such an information feedback loop is particularly valuable for rapidly changing types of risk, where investors’ trading responses to real-time changes in the risk environment (including changes identified using new data sources and analytics) are likely to have far more predictive value than any historical data set.
Only the global capital markets can provide the resources of liquidity and expertise to value and manage emerging risks. If the economic history of capitalism has taught us anything, it’s that a liquid trading market is the best mechanism for allocating capital and pricing risk in a dynamic and changing environment.