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Helen YatesSeptember 05, 2018
Are we moving off the baseline
Are we moving off the baseline
Are We Moving Off The Baseline?
September 05, 2018

How is climate change influencing natural perils and weather extremes, and what should reinsurance companies do to respond? Reinsurance companies may feel they are relatively insulated from the immediate effects of climate change on their business, given that most property catastrophe policies are renewed on an annual basis. However, with signs that we are already moving off the historical baseline when it comes to natural perils, there is evidence to suggest that underwriters should already be selectively factoring the influence of climate change into their day-to-day decision-making. Most climate scientists agree that some of the extreme weather anticipated by the United Nations Intergovernmental Panel on Climate Change (IPCC) in 2013 is already here and can be linked to climate change in real time via the burgeoning field of extreme weather attribution. “It’s a new area of science that has grown up in the last 10 to 15 years,” explains Dr. Robert Muir-Wood, chief research officer at RMS. “Scientists run two climate models for the whole globe, both of them starting in 1950. One keeps the atmospheric chemistry static since then, while the other reflects the actual increase in greenhouse gases. By simulating thousands of years of these alternative worlds, we can find the difference in the probability of a particular weather extreme.” “Underwriters should be factoring the influence of climate change into their day-to-day decision-making” For instance, climate scientists have run their models in an effort to determine how much the intensity of the precipitation that caused such devastating flooding during last year’s Hurricane Harvey can be attributed to anthropogenic climate change. Research conducted by scientists at the World Weather Attribution (WWA) project has found that the record rainfall produced by Harvey was at least three times more likely to be due to the influence of global warming. This suggests, for certain perils and geographies, reinsurers need to be considering the implications of an increased potential for certain climate extremes in their underwriting. “If we can’t rely on the long-term baseline, how and where do we modify our perspective?” asks Muir-Wood. “We need to attempt to answer this question peril by peril, region by region and by return period. You cannot generalize and say that all perils are getting worse everywhere, because they’re not. In some countries and perils there is evidence that the changes are already material, and then in many other areas the jury is out and it’s not clear.” Keeping Pace With the Change While the last IPCC Assessment Report (AR5) was published in 2014 (the next is due in 2021), there is some consensus on how climate change is beginning to influence natural perils and climate extremes. Many regional climates naturally have large variations at interannual and even interdecadal timescales, which makes observation of climate change, and validation of predictions, more difficult. “There is always going to be uncertainty when it comes to climate change,” emphasizes Swenja Surminski, head of adaptation research at the Grantham Research Institute on Climate Change and the Environment, part of the London School of Economics and Political Science (LSE). “But when you look at the scientific evidence, it’s very clear what’s happening to temperature, how the average temperature is increasing, and the impact that this can have on fundamental things, including extreme events.” According to the World Economic Forum’s Global Risks Report in 2018, “Too little has been done to mitigate climate change and … our own analysis shows that the likelihood of missing the Paris Agreement target of limiting global warming to two degrees Celsius or below is greater than the likelihood of achieving it.” The report cites extreme weather events and natural disasters as the top two “most likely” risks to happen in the next 10 years and the second- and third-highest risks (in the same order) to have the “biggest impact” over the next decade, after weapons of mass destruction. The failure of climate change mitigation and adaptation is also ranked in the top five for both likelihood and impact. It notes that 2017 was among the three hottest years on record and the hottest ever without an El Niño. It is clear that climate change is already exacerbating climate extremes, says Surminski, causing dry regions to become drier and hot regions to become hotter. “By now, based on our scientific understanding and also thanks to modeling, we get a much better picture of what our current exposure is and how that might be changing over the next 10, 20, even 50 to 100 years,” she says. “There is also an expectation we will have more freak events, when suddenly the weather produces really unexpected, very unusual phenomena,” she continues. “That’s not just climate change. It’s also tied into El Niño and other weather phenomena occurring, so it’s a complex mix. But right now, we’re in a much better position to understand what’s going on and to appreciate that climate change is having an impact.” Pricing for Climate Change For insurance and reinsurance underwriters, the challenge is to understand the extent to which we have already deviated from the historical record and to manage and price for that appropriately. It is not an easy task given the inherent variability in existing weather patterns, according to Andy Bord, CEO of Flood Re, the U.K.’s flood risk pool, which has a panel of international reinsurers. “The existing models are calibrated against data that already includes at least some of the impact of climate change,” he says. “Some model vendors have also recently produced models that aim to assess the impact of climate change on the future level of flood risk in the U.K. We know at least one larger reinsurer has undertaken their own climate change impact analyses. “We view improving the understanding of the potential variability of weather given today’s climate as being the immediate challenge for the insurance industry, given the relatively short-term view of markets,” he adds. The need for underwriters to appreciate the extent to which we may have already moved off the historical baseline is compounded by the conflicting evidence on how climate change is influencing different perils. And by the counterinfluence or confluence, in many cases, of naturally occurring climate patterns, such as El Niño and the Atlantic Multidecadal Oscillation (AMO). The past two decades have seen below-normal European windstorm activity, for instance, and evidence builds that the unprecedented reduction in Arctic sea ice during the autumn months is the main cause, according to Dr. Stephen Cusack, director of model development at RMS. “In turn, the sea ice declines have been driven both by the ‘polar amplification’ aspect of anthropogenic climate change and the positive phase of the AMO over the past two decades, though their relative roles are uncertain. “We view improving the understanding of the potential variability of weather given today’s climate as being the immediate challenge for the insurance industry, given the relatively short-term view of markets” Andy Bord Flood Re “The (re)insurance market right now is saying, ‘Your model has higher losses than our recent experience.’ And what we are saying is that the recent lull is not well understood, and we are unsure how long it will last. Though for pricing future risk, the question is when, and not if, the rebound in European windstorm activity happens. Regarding anthropogenic climate change, other mechanisms will strengthen and counter the currently dominant ‘polar amplification’ process. Also, the AMO goes into positive and negative phases,” he continues. “It’s been positive for the last 20 to 25 years and that’s likely to change within the next decade or so.” And while European windstorm activity has been somewhat muted by the AMO, the same cannot be said for North Atlantic hurricane activity. Hurricanes Harvey, Irma and Maria (HIM) caused an estimated US$92 billion in insured losses, making 2017 the second costliest North Atlantic hurricane season, according to Swiss Re Sigma. “The North Atlantic seems to remain in an active phase of hurricane activity, irrespective of climate change influences that may come on top of it,” the study states. While individual storms are never caused by one factor alone, stressed the Sigma study, “Some of the characteristics observed in HIM are those predicted to occur more frequently in a warmer world.” In particular, it notes the high level of rainfall over Houston and hurricane intensification. While storm surge was only a marginal contributor to the losses from Hurricane Harvey, Swiss Re anticipates the probability of extreme storm surge damage in the northeastern U.S. due to higher seas will almost double in the next 40 years. “From a hurricane perspective, we can talk about the frequency of hurricanes in a given year related to the long-term average, but what’s important from the climate change point of view is that the frequency and the intensity on both sides of the distribution are increasing,” says Dr. Pete Dailey, vice president at RMS. “This means there’s more likelihood of quiet years and more likelihood of very active years, so you’re moving away from the mean, which is another way of thinking about moving away from the baseline. “So, we need to make sure that we are modeling the tail of the distribution really well, and that we’re capturing the really wet years — the years where there’s a higher frequency of torrential rain in association with events that we model.” The Edge of Insurability Over the long term, the industry likely will be increasingly insuring the impact of anthropogenic climate change. One question is whether we will see “no-go” areas in the future, where the risk is simply too high for insurance and reinsurance companies to take on. As Robert Muir-Wood of RMS explains, there is often a tension between the need for (re)insurers to charge an accurate price for the risk and the political pressure to ensure cover remains available and affordable. He cites the community at Queen’s Cove in Grand Bahama, where homes were unable to secure insurance given the repeated storm surge flood losses they have sustained over the years from a number of hurricanes. Unable to maintain a mortgage without insurance, properties were left to fall into disrepair. “Natural selection came up with a solution,” says Muir-Wood, whereby some homeowners elevated buildings on concrete stilts thereby making them once again insurable.   “In high-income, flood-prone countries, such as Holland, there has been sustained investment in excellent flood defenses,” he says. “The challenge in developing countries is there may not be the money or the political will to build adequate flood walls. In a coastal city like Jakarta, Indonesia, where the land is sinking as a result of pumping out the groundwater, it’s a huge challenge.  “It’s not black and white as to when it becomes untenable to live somewhere. People will find a way of responding to increased incidence of flooding. They may simply move their life up a level, as already happens in Venice, but insurability will be a key factor and accommodating the changes in flood hazard is going to be a shared challenge in coastal areas everywhere.” Political pressure to maintain affordable catastrophe insurance was a major driver of the U.S. residual market, with state-backed Fair Access to Insurance Requirements (FAIR) plans providing basic property insurance for homes that are highly exposed to natural catastrophes. Examples include the California Earthquake Association, Texas Windstorm Insurance Association and Florida Citizens Property Insurance Corporation (and state reinsurer, the FHCF).  However, the financial woes experienced by FEMA’s National Flood Insurance Program (NFIP), currently the principal provider of residential flood insurance in the U.S., demonstrates the difficulties such programs face in terms of being sustainable over the long term.   With the U.K.’s Flood Re scheme, investment in disaster mitigation is a big part of the solution, explains CEO Andy Bord. However, even then he acknowledges that “for some homes at the very greatest risk of flooding, the necessary investment needed to reduce risks and costs would simply be uneconomic.”  

NIGEL ALLENMay 11, 2018
10-Data-Flow-in-a-Digital-Ecosystem
10-Data-Flow-in-a-Digital-Ecosystem
Data Flow in a Digital Ecosystem
May 11, 2018

There has been much industry focus on the value of digitization at the customer interface, but what is its role in risk management and portfolio optimization? In recent years, the perceived value of digitization to the insurance industry has been increasingly refined on many fronts. It now serves a clear function in areas such as policy administration, customer interaction, policy distribution and claims processing, delivering tangible, measurable benefits. However, the potential role of digitization in supporting the underwriting functions, enhancing the risk management process and facilitating portfolio optimization is sometimes less clear. That this is the case is perhaps a reflection of the fact that risk assessment is by its very nature a more nebulous task, isolated to only a few employees, and clarifying the direct benefits of digitization is therefore challenging. To grasp the potential of digitalization, we must first acknowledge the limitations of existing platforms and processes, and in particular the lack of joined-up data in a consistent format. But connecting data sets and being able to process analytics is just the start. There needs to be clarity in terms of the analytics an underwriter requires, including building or extending core business workflow to deliver insights at the point of impact. Data Limitation For Louise Day, director of operations at the International Underwriting Association (IUA), a major issue is that much of the data generated across the industry is held remotely from the underwriter. “You have data being keyed in at numerous points and from multiple parties in the underwriting process. However, rather than being stored in a format accessible to the underwriter, it is simply transferred to a repository where it becomes part of a huge data lake with limited ability to stream that data back out.” That data is entering the “lake” via multiple different systems and in different formats. These amorphous pools severely limit the potential to extract information in a defined, risk-specific manner, conduct impactful analytics and do so in a timeframe relevant to the underwriting decision-making process. “The underwriter is often disconnected from critical risk data,” believes Shaheen Razzaq, senior product director at RMS. “This creates significant challenges when trying to accurately represent coverage, generate or access meaningful analysis of metrics and grasp the marginal impacts of any underwriting decisions on overall portfolio performance. “Success lies not just in attempting to connect the different data sources together, but to do it in such a way that can generate the right insight within the right context and get this to the underwriter to make smarter decisions.” Without the digital capabilities to connect the various data sets and deliver information in a digestible format to the underwriter, their view of risk can be severely restricted — particularly given that server storage limits often mean their data access only extends as far as current information. Many businesses find themselves suffering from DRIP, being data rich but information poor, without the ability to transform their data into valuable insight. “You need to be able to understand risk in its fullest context,” Razzaq says. “What is the precise location of the risk? What policy history information do we have? How has the risk performed? How have the modeled numbers changed? What other data sources can I tap? What are the wider portfolio implications of binding it? How will it impact my concentration risk? How can I test different contract structures to ensure the client has adequate cover but is still profitable business for me? These are all questions they need answers to in real time at the decision-making point, but often that’s simply not possible.” When extrapolating this lack of data granularity up to the portfolio level and beyond, the potential implications of poor risk management at the point of underwriting can be extreme.  With a high-resolution peril like U.S. flood, where two properties meters apart can have very different risk profiles, without granular data at the point of impact, the ability to make accurate risk decisions is restricted. Rolling up that degree of inaccuracy to the line of business and to the portfolio level, and the ramifications are significant. Looking beyond the organization and out to the wider flow of data through the underwriting ecosystem, the lack of format consistency is creating a major data blockage, according to Jamie Garratt, head of innovation at Talbot. “You are talking about trying to transfer data which is often not in any consistent format along a value chain that contains a huge number of different systems and counterparties,” he explains. “And the inability to quickly and inexpensively convert that data into a format that enables that flow, is prohibitive to progress. “You are looking at the formatting of policies, schedules and risk information, which is being passed through a number of counterparties all operating different systems. It then needs to integrate into pricing models, policy administration systems, exposure management systems, payment systems, et cetera. And when you consider this process replicated across a subscription market the inefficiencies are extensive.” A Functioning Ecosystem There are numerous examples of sectors that have transitioned successfully to a digitized data ecosystem that the insurance industry can learn from. One such industry is health care, which over the last decade has successfully adopted digital processes across the value chain and overcome the data formatting challenge. It can be argued that health care has a value chain similar to that in the insurance industry. Data is shared between various stakeholders — including competitors — to create the analytical backbone it needs to function effectively. Data is retained and shared at the individual level and combines multiple health perspectives to gain a holistic view of the patient. The sector has also overcome the data-consistency hurdle by collectively agreeing on a data standard, enabling the effective flow of information across all parties in the chain, from the health care facilities through to the services companies that support them. Garratt draws attention to the way the broader financial markets function. “There are numerous parallels that can be drawn between the financial and the insurance markets, and much that we can learn from how that industry has evolved over the last 10 to 20 years.” “As the capital markets become an increasingly prevalent part of the insurance sector,” he continues, “this will inevitably have a bearing on how we approach data and the need for greater digitization. If you look, for example, at the advances that have been made in how risk is transferred on the insurance-linked securities (ILS) front, what we now have is a fairly homogenous financial product where the potential for data exchange is more straightforward and transaction costs and speed have been greatly reduced. “It is true that pure reinsurance transactions are more complex given the nature of the market, but there are lessons that can be learned to improve transaction execution and the binding of risks.” For Razzaq, it’s also about rebalancing the data extrapolation versus data analysis equation. “By removing data silos and creating straight-through access to detailed, relevant, real-time data, you shift this equation on its axis. At present, some 70 to 80 percent of analysts’ time is spent sourcing data and converting it into a consistent format, with only 20 to 30 percent spent on the critical data analysis. An effective digital infrastructure can switch that equation around, greatly reducing the steps involved, and re-establishing analytics as the core function of the analytics team.” The Analytical Backbone So how does this concept of a functioning digital ecosystem map to the (re)insurance environment? The challenge, of course, is not only to create joined-up, real-time data processes at the organizational level, but also look at how that unified infrastructure can extend out to support improved data interaction at the industry level. An ideal digital scenario from a risk management perspective is where all parties operate on a single analytical framework or backbone built on the same rules, with the same data and using the same financial calculation engines, ensuring that on all risk fronts you are carrying out an ‘apples-to-apples’ comparison. That consistent approach would need to extend from the individual risk decision, to the portfolio, to the line of business, right up to the enterprise-wide level. At the underwriting trenches, it is about enhancing and improving the decision-making process and understanding the portfolio-level implications of those decisions. “A modern pricing and portfolio risk evaluation framework can reduce assessment times, providing direct access to relevant internal and external data in almost real time,” states Ben Canagaretna, managing director at Barbican Insurance Group. “Creating a data flow, designed specifically to support agile decision-making, allows underwriters to price complex business in a much shorter time period.” “It’s about creating a data flow designed specifically to support decision-making” Ben Canagaretna Barbican Insurance Group “The feedback loop around decisions surrounding overall reinsurance costs and investor capital exposure is paramount in order to maximize returns on capital for shareholders that are commensurate to risk appetite. At the heart of this is the portfolio marginal impact analysis – the ability to assess the impact of each risk on the overall portfolio in terms of exceedance probability curves, realistic disaster scenarios and regional exposures. Integrated historical loss information is a must in order to quickly assess the profitability of relevant brokers, trade groups and specific policies.” There is, of course, the risk of data overload in such an environment, with multiple information streams threatening to swamp the process if not channeled effectively. “It’s about giving the underwriter much better visibility of the risk,” says Garratt, “but to do that the information must be filtered precisely to ensure that the most relevant data is prioritized, so it can then inform underwriters about a specific risk or feed directly into pricing models.” Making the Transition There are no organizations in today’s (re)insurance market that cannot perceive at least a marginal benefit from integrating digital capabilities into their current underwriting processes. And for those that have started on the route, tangible benefits are already emerging. Yet making the transition, particularly given the clear scale of the challenge, is daunting. “You can’t simply unplug all of your legacy systems and reconnect a new digital infrastructure,” says IUA’s Day. “You have to find a way of integrating current processes into a data ecosystem in a manageable and controlled manner. From a data-gathering perspective, that process could start with adopting a standard electronic template to collect quote data and storing that data in a way that can be easily accessed and transferred.” “There are tangible short-term benefits of making the transition,” adds Razzaq. “Starting small and focusing on certain entities within the group. Only transferring certain use cases and not all at once. Taking a steady step approach rather than simply acknowledging the benefits but being overwhelmed by the potential scale of the challenge.” There is no doubting, however, that the task is significant, particularly integrating multiple data types into a single format. “We recognize that companies have source-data repositories and legacy systems, and the initial aim is not to ‘rip and replace’ those, but rather to create a path to a system that allows all of these data sets to move. For RMS, we have the ability to connect these various data hubs via open APIs to our Risk Intelligence platform to create that information superhighway, with an analytics layer that can turn this data into actionable insights.” Talbot has already ventured further down this path than many other organizations, and its pioneering spirit is already bearing fruit. “We have looked at those areas,” explains Garratt, “where we believe it is more likely we can secure short-term benefits that demonstrate the value of our longer-term strategy. For example, we recently conducted a proof of concept using quite powerful natural-language processing supported by machine-learning capabilities to extract and then analyze historic data in the marine space, and already we are generating some really valuable insights. “I don’t think the transition is reliant on having a clear idea of what the end state is going to look like, but rather taking those initial steps that start moving you in a particular direction. There also has to be an acceptance of the need to fail early and learn fast, which is hard to grasp in a risk-averse industry. Some initiatives will fail — you have to recognize that and be ready to pivot and move in a different direction if they do.”

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