Commercial insurance in the United States in 2015 is a buyer’s market. Led by commercial property, rates are decreasing in all lines, and the softening cycle that began in early 2014 is expected to continue into 2016. This is certainly good news for customers, who can anticipate a moderate price environment.
But are these conditions a sign of a larger, more permanent shift? In recent years, much has been said about whether market cycles are becoming a thing of the past. The thinking is that improvements in data, analytics and technology and the influx of alternative capital will make the insurance market more efficient. As a result, pricing cycles will become shallower in magnitude and shorter in duration, perhaps eventually leveling off altogether. While this idea is solid in theory, the reality is that we are still far away from a perfectly efficient market. In fact, in many cases, the current double-digit rate decreases are tied to market forces and not actual account performance. Paradoxically, some of the developments that will ultimately lead to an efficient market are actually creating a level of volatility that is perpetuating traditional market cycles.
A Strong Year
Last year was a strong year for the property/casualty industry. While some of the performance was the result of relatively minimal catastrophe losses, performance was good in almost all segments. According to A.M. Best, the industry posted a combined ratio of 97.2% in 2014. This was the second consecutive year of a sub-100% combined ratio and only the second time since 1990 that the industry posted consecutive combined ratios below 100%. The trend is expected to continue, with asset management firm Conning predicting that 2015 will be a third year of sub-100% combined ratio.
As a result of this underwriting performance, policyholder surplus grew to a record $674 billion, an increase of more than 50% since 2009. This level of surplus is well in excess of what is needed to keep the market in equilibrium—estimates of excess capacity in the industry range from $50 billion to $120 billion dollars. Premium to surplus dropped to a record low of 0.73 to 1. While this figure points to industry strength and claims-paying ability, it also highlights a low use of that capital to underwrite risk. In the current low interest rate environment, insurers are struggling to generate an adequate investment return on their swelling portfolios. This creates pressure to write more risk in order to generate an acceptable return on capital. Industry return on surplus in 2014 was a respectable 9.5%, but down 10.7% from 2013.
This excess capacity has led to price reductions across almost all lines in the first quarter of 2015. According to the Council of Insurance Agents and Brokers, rates decreased an average of 2.3% in the first quarter. Many risks saw larger reductions. By most reports, large risks saw more downward pricing than small ones. Overall, the decline was led by property rates, which frequently saw double-digit declines. Large layered programs were frequently over-lined by up to 100%, putting significant downward pressure on pricing and causing more liberalization of terms. According to a Marsh report, the only area that has consistently witnessed upward pricing pressure in 2015 is cyberliability, due to increased demand, limited empirical data with which to build credible pricing models and some high-profile claims.
Clearly, market cycles are alive and well. But while the industry is moving to more effectively differentiate by geography, line of business, customer size and profile, high-quality risks can generally experience a positive result at renewal regardless of the underlying account pricing fundamentals. This is because the forces that will ultimately create an efficient market—data analytics, emerging risk identification and alternative capital—still have limitations. In some cases, these forces are even having the opposite effect, creating more market disruption than efficiency.
Data, Technology and Analytics
An efficient market is one in which perfect information allows underwriters to make accurate predictions on risk. When an underwriter can accurately predict both the magnitude and timing of a prospective loss, then the market will always gravitate toward equilibrium around the technical price for risk. Pricing differences will be a function of an insurer’s investment income, return expectations, expense management and ability to effectively manage claims as compared to competitors.
While the industry is making strides to improve the quality of data capture and analytics, there is a long way to go. Many insurers are saddled with legacy systems that do not talk to one another, let alone to third parties. Submissions still come in a variety of forms, from spreadsheets to paper to PDFs. As a result, much of the data is not structured. Similarly, loss runs in many environments are flat files that are not easy to manipulate. While re-keying the data can solve some of the issues, data consistency and quality remain concerns.
At the same time, even when data is harnessed, the sheer volume can make deciphering it a challenge. “We’re overwhelmed by the geometric amount of data,” AIG CEO Peter Hancock said at a recent S&P conference. “But its usefulness is also shrinking. We need to figure out how to filter out the noise.”
For example, while they are improving, catastrophe risk models are not yet an accurate predictor of loss magnitude. Nevertheless, these models are used by rating agencies, underwriters and capital providers to determine risk. This is important because weather plays such an important role in commercial property and casualty loss experience. But until long-term weather models can predict weather 12 months out, the industry will be subject to unforeseen fluctuations, and these limitations will create market uncertainty.
More broadly, while predictive modeling is a hot topic in the industry, its commercial applications are in their infancy. A 2012 study by IBM showed that only 28% of insurers were using big data. The rest were either not engaged or still in planning stages. While much has certainly changed over three years, the industry is still far from fully harnessing the power of big data to transform their business models. Thus, it will also be a long time before big data and predictive modeling fundamentally transform the industry and flatten out market cycles. And even when they do, it may not be the traditional players who benefit first—it may take a new technology or approach to risk to eliminate market cycles.
Emerging Risk Identification
While the industry improves its ability to accurately quantify and price known risks, emerging risks must also be understood and accurately modeled. These risks can severely impact insurer profitability and the overall market. In some cases, these risks can be anticipated as they develop (employment practices), while in other cases, they are only discovered after the fact (asbestos and environmental risk), which creates more market disruption.
In the current environment, cyberliability is a good example of an emerging risk the industry is actively trying to quantify and create products for. Recent high-profile losses have created a strong demand for cyberliability policies and these are evolving both in terms of coverage and price. Cyber is appealing to insurers because it represents a new avenue for premium development and a large potential market. A Marsh report indicated that cyber underwriters are not yet able to accurately underwrite and price individual risks, so instead they are looking to manage exposure across the portfolio and set prices accordingly. “Insurers appear to be underwriting and managing loss potential not by individual account selection and pricing disparity, but by controlling aggregate loss potential through limits constraints according to industry, geography and total amount of cyber coverage offered,” read the report. This is creating a volatile market as demand grows with little differentiation from one risk to another. Without the ability to accurately understand and price emerging risks, the market cannot find equilibrium.
Beyond emerging risks like cyber, black swan events like 9/11 are unpredictable and can dramatically impact industry profitability. These will not necessarily alter the price for a specific risk, but will impact insurer profitability, which will have an impact on supply and, ultimately, market pricing.
In spite of the uncertainty, capital continues to be attracted to the insurance industry because hazard-based risks do not correlate to the returns of other financial instruments and typically operate independently of them. Alternative investment products and vehicles have proliferated over the past 10 years and have really taken off over the least three.
As mentioned earlier, industry surplus has increased by more than 50% since 2009. While some of this has been a result of retained profits, much of it is fresh capital coming into the marketplace. This increase in surplus is in part a result of the growth of alternative capital in the reinsurance industry. According to Aon Benfield, alternative capital now represents over 10% of total reinsurance capital and has doubled over the past three years. This capital has put extreme downward pressure on reinsurance pricing, which ultimately impacts commercial pricing.
Alternative capital investors have benefited from the low level of catastrophe losses in recent years. A report by Willis Capital Markets indicates that the risk spread on U.S. wind-exposed catastrophe bonds has fallen from 12% in 2012 to 5.8% at the end of 2014. These price swings led to large price changes for catastrophe-exposed commercial property risks.
While it is generally accepted that alternative capital has become a permanent fixture in the industry, the durability of this capital depends on both other return opportunities and the reliability of the models used to price the products. If the models are proven wrong after the next major event, it may be a while before alternative capital is again as large a factor as it is today. Over the long term, alternative capital should help smooth out industry cycles by allowing capital to flow in and out of the industry much more rapidly than in the past and eliminate price inefficiencies and excess profit opportunities. In the short term, it has the opposite effect, as increasingly rapid capital flowing into the market shifts the supply curve and exacerbates cyclical activity.
To date, alternative capital has been concentrated in the catastrophe property marketplace. This has not only depressed pricing in that market segment, but also pushed capital into other areas to search for better returns. Over time, alternative capital will likely find its way into longer-tail lines as well. Until perfected, this will also impact pricing models and cycles in those lines.
The Search for Efficiency Continues
For all buyers, the industry continues to be focused wherever possible on risk differentiation. High-quality risks with a strong risk management approach will always do better regardless of cycle. All insureds should focus on understanding their data and providing it to insurers in a structured format. Just as important is the underlying “story” of the account and the insured’s commitment to risk management. The largest risks can continue to take advantage of alternative market capacity, although that could be a double-edged sword as performance in that segment evolves. Sooner or later (probably later), we will get to an efficient market and an end to cycles. In the meantime, understanding why they occur and how they are changing over time is the best strategy for properly managing your insurance portfolio.