Following on from last week's post on Regulation, it is time for our final 'Key Theme', on Product Development, after which we move on to our Regional Profiles. Product development is the bread and butter of the insurance industry – the question is not whether to build products but rather which products will best serve the needs of today’s increasingly demanding insurance customers. What has become clear across this content series is that product development can no longer occur in silos, with one function creating products for another function to sell. Insurers are determined to make every moving part of their business serve the customer, and what this means in concrete terms is that every division of the business has a contribution to make toward the creation of customer-centric products. The line between product developers and product salespeople, as in so many industries, is therefore becoming blurry. In this sense, Product Development is the central node into which feed all our other 'Key Themes' (Analytics & AI, Digital Innovation, IoT, Marketing & Customer-Centricity, Distribution, Claims, Fraud, Cybersecurity, Investment Management and Regulation). And all the indicators suggest that insurers are only just beginning to tap the opportunities for technology-driven product creation.

"The biggest problem these days is, although everybody is talking about Digitisation and Disruption and are modernising their core systems with huge investments in order to support these new trends, the underlying products are not yet 'digital ready' – even new ones." — Oliver Lauer, former Head of Architecture / Head of IT Innovation at Zurich

In this installment, we start by looking at where innovation is occurring (by insurance line and insurance department) before considering some of the broad trends in product development – from bundling and upselling to diversification and Usage-Based Insurance (UBI). The following stats and perspectives are taken from our Global Trend Map; a full breakdown of our survey respondents, and details of our methodology, are included as part of the full report, which you can download for free at any time. So first up: which departments is product innovation currently coming from? ... The three highest-scoring departments were Underwriting (with 70% of respondents naming it), Pricing (55%) and Marketing (54%). Other areas that warrant mention were Actuarial (51%) and Distribution (36%). We noted in our earlier post on Marketing & Customer-Centricity that the roots of today’s consumer-led disruption are in the rise and ease-of-use of new distribution channels – so insurers that leave Distribution outside of their product discussions do so at their peril! See also: Next for Insurtech: Product Diversity   Which insurance lines are driving the greatest degree of product innovation? In addition to seeing product as department-driven, we also investigated the extent to which it is line-driven. The chart below shows Auto (voted by 56% of respondents), Home (45%) and Health (41%) to be the three lines experiencing the most product innovation (according to carriers taking our survey). This is corroborated anecdotally by the sheer number of in-market IoT products we see across these fields, from in-car telematics through to smart-home controllers and connected-health armbands. Life and Commercial are relative laggards in this regard, although we do believe there is ample opportunity in both these areas. This may follow the same pattern we identified with IoT (itself an abundant source of product innovation), where we saw platform implementation in Commercial currently trailing but quickly drawing level with other lines (see our earlier post on IoT). Regional trends for this question warrant some high-level comment:

#smarthome #mhealth #AutonomousVehicles #telematics See where insurance innovation is greatest in the #InsuranceMap: https://t.co/QH8z3aYH7y pic.twitter.com/qj6KKBrUF3

— Insurance Nexus (@InsuranceNexus) July 26, 2017

Health is a substantial driver of product development for carriers in Asia-Pacific and Europe. In North America, however, it appears relatively insignificant

1. Life appears tagged to Health in terms of how it trends regionally and is consistently the least innovative of the lines#
2. P&C/General, Commercial and Home insurance are relatively consistent across our different geographies
3. Auto is ahead among carriers in Europe and Asia-Pacific compared to North America

The relative prominence of the different lines, as well as the broad regional tendencies outlined above, remain the same when we widen our scope beyond carriers to consider the industry as a whole.

"The biggest risk the insurance industry faces when it comes to innovation is not taking enough risk. True innovation requires experimentation, which most of the time results in failure. Insurance organisations are built to eliminate failure from their culture. Without failure, you can have no innovation. CEOs demand a positive Return on Investment (ROI), they now need to seek out and understand what it means to have a positive Return on Risk (ROR)." — Steve Anderson, President at The Anderson Network

[caption id="attachment_30597" align="alignnone" width="570"] Human hand pointing at touchscreen in working environment at meeting[/caption] Key trends in the development of products It’s clear from this section so far that product development is a strategic priority for a diverse spread of departments and lines. But how are insurers actually going about product development on the ground? Let us now present our trends on a number of product approaches that we identified among our carrier respondents: product diversification, Usage-Based Insurance (UBI) and product bundling/upselling.

"You don’t really have to invent new products in my eyes, you just have to make the existing ones easier and more 'digital native'. Today’s products have been and are still created for non-digitals. And this situation not only makes new customer-facing digital processes complicated, it also makes core replacements and automation more complicated and expensive than necessary." — Oliver Lauer, former Head of Architecture / Head of IT Innovation at Zurich

i) Product Diversification The pace of change in the insurance sector is picking up, and many ecosystem players are quickening their iterations both on new and existing products in a bid to stay relevant. 76% of (re)insurers are pursuing product diversification as part of their organisations’ growth strategies… This move towards diversification is not limited to any one kind of insurance market but is driving insurance growth all around the world. It is naturally very important for insurers looking to break into totally new markets, as is the case in many developing economies, where traditional insurance products may be inappropriate for lower-income demographics (microinsurance being a case in point). In mature markets, growth will come primarily from addressing existing demographics with more tailored products to fill in under-penetrated lines and segments; there is also the perennial threat that existing customers, tired of products that are suboptimal, will churn to competitors and new entrants who can offer better-suited ones. Whatever the market conditions, by trialling multiple products, insurers can both broaden their appeal and arrive at optimal products more quickly. ii) Usage-Based Insurance (UBI) The emerging generation of insurance products differ from those that have gone before in several key ways. One is the on-demand or usage-based component of new products – so that, rather than having idle and inflexible policies that subject the policyholder to the Tyranny of Averages, consumers can enjoy insurance-as-a-service. 32% of insurer respondents have a Usage-Based Insurance (UBI) strategy… This trend towards Usage-Based Insurance (UBI) is a global one, and there was no significant regional variation across our three key regions. More information about UBI models can be found in our earlier Internet of Things section and in our section on Europe in the upcoming Regional Profiles. "Most of the innovation in product development will happen where smart connected devices drive new business models based on behavioural data. I particularly expect improvements in pricing. UBI is a bigger game changer than covering events that are not insured today. In any case, there will be a huge need to understand, measure and manage rational and irrational behaviour." — Andreas Staub, Managing Partner at FehrAdvice iii) Product Bundling and Upselling A key trend we have witnessed in other B2C industries, like Amazon and Netflix, is the rise of the recommendation engine. This is not just a core component of the customer experience but also an important enabler of new business, insofar as it lets companies push new products to customers that they are actually likely to want and to find useful. We also see this in insurance, in the form of data-driven product bundling and upselling. 47% of insurers have a strategy to bundle and upsell products based on customer lifestyle analytics… Insurance has always had relatively few customer touchpoints, and even though insurers are now seeking to increase that number, insurance remains a product that is sold rather than bought. Taking full advantage of every selling interaction they have is therefore the surest way for insurers to increase their customers’ lifetime value. Bundling and upselling products is – like diversification – a strategy with strong applications regardless of what sort of insurance market you are operating in. Whether your focus is to chase new customers or to retain existing business, it is better to reap maximum reward on each customer from the outset than to re-engage them (perhaps unsuccessfully) later on. "The cost of customer acquisition is a critical metric for marketing efforts. Lifetime customer value also helps us know how much we should be spending to acquire as well as how we should expand our share of wallet within the products we offer." — Michael Shostak, SVP and Chief Marketing Officer at Economical Insurance See also: Insurance Product Development (Excerpt, Part 3)   There are obviously many aspects of product development beyond diversification, UBI and bundling/upselling which we were not able to investigate directly. For this reason, we asked our carrier respondents to indicate additional product-development talking points in open text. Two key points that emerged across their comments were:

1. The need to increase the service element of products, to keep up with evolving consumer needs and to drive customer retention
2. The problem of constrained development resources, especially in expert personnel and IT

Now that we have worked our way through all our Key Themes, it's time to move on to our Seven Regional Profiles, exploring on a geographical basis the stats and perspectives presented in the series so far. If you'd like to access all our Regional Profiles straightaway, then please feel free to skip ahead and download the full Trend Map here (it's free!).

In programming circles, there is an aphorism known as the “90-90 rule.” It states that the first 90% of code accounts for the first 90% of the expected development time—and the remaining 10% of code takes another 90% of time. The rule is a tongue-in-cheek acknowledgement that technology projects always take longer than you expect, even when you know that they are going to take longer than you expect. Sacha Arnoud, director of engineering at Waymo, recently used a variant of the 90-90 rule to characterize Waymo’s self-driving car program. Waymo’s experience, he said, was that the first 90% of the technology took only 10% of the time. To finish the last 10%, however, is requiring 10x the initial effort. Arnoud’s remarks were given at a guest lecture at Lex Fridman's MIT class on “Deep Learning for Self-Driving Cars.” He offered technical insights on the history of the Waymo program, how it is applying artificial intelligence and deep learning and how it is moving from demo to industrial-strength product. The Waymo engineer’s lecture goes beyond most Waymo management presentations and press events. He provides vivid details on the complexity of the effort to date and insight on challenges to come—both for Waymo and for those trying to catch up to its pioneering efforts. Here are 5 takeaways, though I recommend watching the entire presentation. 1. Industrialization requires 10x the effort. Arnoud emphasized the large amount of work needed to go from a demo that works in a lab to an industrialized product that is safe to put on the road: “You need to 10x the capabilities of your technology. You need to 10x your team size, including finding effective ways for more engineers and more researchers to collaborate. You need to 10x the capabilities of your sensors. You need to 10x the overall quality of the system, including your testing practices.” 2. Deep learning enabled algorithmic breakthroughs. Arnoud noted that deep learning techniques were much less advanced in 2010 when Google started its work on self-driving cars. But, in the years since, deep learning has advanced to enable algorithmic breakthroughs in several critical areas for autonomous driving, including mapping, perception and scene understanding. Arnoud gave numerous examples, such as using deep learning to analyze street imagery to extract street names, house numbers, traffic lights and traffic signs. The ability to precompute such data and store them as maps in the car saves precious onboard computing power for real time tasks. See also: When Will the Driverless Car Arrive?   Deep learning is driving breakthroughs in real-time tasks as well, such as analyzing sensor data to identify traffic signals, other vehicles, obstacles, pedestrians, and so on. Deep learning capabilities also help in anticipating possible behavior of other drivers, cyclists and pedestrians, and driving accordingly. 3. Synergy with other Google units is key to Waymo’s progress. Arnoud acknowledged the importance of Google’s “whole machine learning ecosystem” to Waymo’s progress. This includes the seminal software advances by the Google Brain team and on-going collaboration with other Google teams working on deep learning at scale, such as in vision, speech, natural language processing and maps. The Google ecosystem also provides specialized infrastructure and tools for machine learning. This includes accelerators, data centers, labelled datasets and research that support Google’s TensorFlow programming paradigm. 4. Waymo’s testing program might be its secret sauce. Arnoud emphasized that however great Waymo’s algorithms, sensors and overall package might be, driverless cars are still complex, embedded, real-time robotic systems that must work safely with imperfect data in an unpredictable world. He highlighted Waymo’s three-prong testing program of real-world driving, simulation and structured testing as key to iterating on and productizing the technology. Much is made of the millions public-road miles that Waymo’s cars have driven autonomously. Arnoud described this as the equivalent of about 300 years of human driving experience and 160 times around the globe. Real world driving is critical, he said, but what is more important is the ability to simulate. Simulation is critical because it allows for Waymo to test each new iteration of software against all previously-driven miles. Even more important is the ability to test against “fuzzed” versions of those millions of miles, such as seeing how the software would handle cars going at slightly different speeds, an extra car, pedestrians crossing in front of the car and so on. Arnoud described Waymo’s simulation-based testing capability as the equivalent of 25,000 virtual cars driving 2.5 billion real and modified miles in 2017. The third component of Waymo’s testing program is its structured testing program. Arnoud said that there is a “long tail” of driving situations that happen very rarely. Rather than trying to encounter every possibility in real-world driving, Waymo set up a 90-acre mock city at the decommissioned Castle Air Force base where it can test its cars against such edge cases. These tests are then fed into the simulation engine and fuzzed to create variations for more testing. 5. Waymo’s next steps are big (and hard) ones. Arnoud closed with a discussion of the engineering challenges in front of Waymo. He described two big next steps. One next step is expanding the “operational design domains” (ODD) of the cars. This includes expanding into “dense urban cores,” such as San Francisco (in which Waymo recently announced it is expanding its testing program). The other ODD was additional weather conditions, such as hard rain, snow and fog. (Waymo CEO John Krafcik recently told an audience that he was “jumping up and down” recently when it snowed 12 inches near Detroit, because it would enable Waymo’s testing in snow.) See also: 7 Steps for Inventing the Future The other area of focus was what Arnoud called “semantic understanding.” As an example, he pointed to the chaotic Place de l'Étoile traffic circle around the Arc de Triomphe in Paris. The circle is a meeting point of 12 roads and notoriously difficult to navigate. Arnoud says he has driven it many times without incident, however, and that such situations require a lot more than perception and vehicle operating skills. They require deep understanding of local rules and expectations. They also require constant communication and coordination with other drivers, including signals, gestures and so on. This kind of deep reasoning is key to numerous edge cases and improving the general abilities of driverless cars. * * * While Waymo has clearly made tremendous progress towards the driverless future, Arnoud closed his presentation by emphasizing the engineering infrastructure and the complexities of scaling that have to be addressed in order to turn driverless cars into safe production systems. How far along is Waymo in the last 90% of that industrialization process? Arnoud never said. But, to put a point on the complexities, he showed a closing video of a Waymo car stopped at an intersection as a gaggle of kids bounced on frogger sticks across the street on all sides of the car. Some things are waiting for, he seemed to imply.

There are a lot of reasons why negotiating a workers' comp settlement at a mediation is better than at the board, such as control over scheduling and lack of time constraints. But how does that compare with an informal? The presence of the mediator makes all the difference. Here are three examples: Stop the Posturing When opposing counsel sit together they keep their cards close to the vest. They magnify the strengths of their own case while denigrating the opposing viewpoint. Once I separate the parties into separate rooms (caucuses), the motivation to aggrandize diminishes. Attorneys and their clients can reasonably discuss the good and bad sides of the issues with the mediator without giving up their negotiation position. Then it’s my job to convey that position so that another reasoned discussion happens in the other room. See also: Work Comp Mediation in a #MeToo World   The Neutral Sounding Board As a professional neutral, I do not have a stake in the outcome. I want to help the parties reach a settlement, which is the optimal result for all. I can provide untainted feedback and sometimes point out overlooked data. Some clients refuse to listen to their lawyer’s case assessment, and some lawyers have learned that their continued employment mitigates against contradicting their client’s overconfidence. As mediator, I can deliver an unwelcome message about the prospect of success, opening the door to a more frank discussion between attorney and client. Stakeholders Have Active Roles Unlike at the WCAB or an informal, the stakeholders are encouraged to take an active part in mediation. In caucus, clients and their attorneys can have frank discussions with the mediator—and each other. When claims adjusters and risk managers attend mediation, they maximize their understanding of the dynamics of the negotiation. Injured workers can receive settlement offers in real time. Some applicant attorneys keep their clients away from the negotiation in an informal meeting. The injured worker may be hidden in a back office or on telephone stand-by. There may be important reasons to prevent interaction between the defense attorney and the injured worker, but this approach prevents the injured worker from buying in to the negotiation. Sometimes, the result can be disastrous when the injured worker later repudiates that carefully crafted compromise and release. <See also: 25 Axioms Of Medical Care In The Workers Compensation System   In contrast, once the parties are separated into their caucus rooms, the stakeholders, their attorney and the mediator can have a confidential, free-flowing discussion without the presence of opposing counsel. It may be the only time the injured worker gets to tell the story to a neutral. The neutral intermediary is missing in an informal. My job is to steer the proceedings, frame communications to facilitate the negotiation and help parties decide their course.

From May 2018, new data protection laws will be implemented by the EU to help protect citizens' data. This looming deadline has made this a particularly hotly debated topic, in all sectors, not simply insurance. However, the question of how this new legislation will affect the insurance sector and future policies have been a contentious issue. Being caught unprepared by GDPR come May will lead to a number of issues for business, especially the bigger they are and the more data they deal with. As the insurance sector deals with intimate details of people’s lives and financials, it is vital that the implications of GDPR are considered and the necessary steps are taken to prepare the industry in time. An Overview of GDPR At the face of it, GDPR (General Data Protection Regulation) is designed to strengthen and unite data protection for all individuals with European Union citizenship. This includes the export of personal information outside of the EU, also. Meaning that this is a change which the whole world is watching with bated breath. This officially comes into effect from May 25th, 2018. The data specifically covered by GDPR includes name, date of birth, physical address, online IP address and other attributes that contribute to a person’s online presence. Non-compliance to protect this data comes with hefty fines. These can be either up to €20 million or 4% of a company’s annual turnover (whichever is the highest sum). See also: How to Avoid Being Bit by GDPR (Part 1)   The legislation specifically states that GDPR will have a greater impact on businesses with 250 or more employees, however, that does not mean that small business or even sole traders are exempt. Does Insurance Cover GDPR? Well, yes and no. It’s becoming a little bit of a grey area in the lead up to GDPR. Many companies are relying on their Cyber insurance policies to cover any fines they may garner as a result of GDPR, however, many professionals are stating that this will be unlikely to happen. Although many companies are trying to adapt their cyber insurance to cover GDPR, many are saying this is unrealistic. For most insurers, cyber insurance has a maximum cut off point of around £400 million, typically. GDPR has the ability to demand 4% of global turnover for larger companies - which can quickly outvalue this. How can insurance policies cope with this? This also begs another question: where does this leave freelancers and other smaller business, who perhaps can’t afford multiple types of insurance policies, or at least not one that can cover the eye-watering €20 million that GDPR calls for? Of course, there is a lesser tier of fines (2% of revenue or €10 million), but this is for lesser offences and not levelled for the turnover or size of a business. In fact, privately some insurance companies are considering that - realistically - GDPR may be wholly uninsurable in the long term. However, many are waiting for a test case in order to see whether this is the case or not. New Wave of Insurance So, the big question: will GDPR cause a new wave of insurance to be created? At the moment, it certainly seems that current insurance policies will have to be adapted in order to try and cover GDPR. There has been a surge in people taking out cyber insurance in the hope that it will cover them in the case of a GDPR infraction. And if this adaption fails, perhaps in the case of cybersecurity, the insurance industry must look to move forward with a wholly new type of insurance. Perhaps this is a specific policy which covers the fine up to a certain point, leaving it up to the business to cover the rest of the cost themselves. The ability to accurately measure risk is at the heart of the insurance sector. Which means that, as far as GDPR is concerned, the sector could be a leading force in setting the standard against this new legislation. Effect on the Insurance Sector According to Mark Williamson of Clyde & Co, many companies in the insurance sector itself will not be GDPR compliant by May. But, what does this really mean? Confusion surrounding GDPR and how to deal with it, industry-wide, has meant that many companies have been slow to take any action at all. Insurance companies both control and process data, two key factors being considered by GDPR, the need to adapt is vital. This includes insurance that is handled outside of the EU, so it isn’t an issue that will be resolved overnight. Policyholders are often switching insurance providers for better deals and rates. Moving forward, these changes may also be an incentive for people to choose an insurance provider, as proving able to handle GDPR will be a huge incentive for potential customers. In turn, it may also make insurers more wary of new customers. As data processors who are not compliant will be much more open to being fined and having to claim on their insurance policy. GDPR and Brexit The question of whether or not Brexit will also have an effect for British insurers has been raised. As the scission between Britain and the EU looms ever closer, the true impact of the move looms as a large question mark for many industries. See also: How to Earn Consumers’ Trust   But, as GDPR will be enforced both in and outside of the EU, this is one issue that Brexit will seemingly have no impact. Meaning at least one straightforward answer when it comes to GDPR for the insurance sector. A Need for Change If one thing is clear as we move closer and closer to the May 28th deadline, it is the fact that change needs to happen in the industry sector. The insurance sector needs to become fully compliant in the run-up to this deadline, while also auditing itself more carefully and even appointing a Data Protection Officer if necessary. Perhaps, the future solution will be a new type of policy. Currently, however, that seems to be a long-off thought for many insurance brokers. The immediate necessity is compliance, post-May we may see a move for a more concrete policy change. It is something to be watched carefully, especially in the first instance. As the first few cases, whether large or small, will help to set the precedent moving forward.

As we first noted in our 2014 publication, Broking 2020: Leading from the front in a new era of risk, trends reflecting larger macroeconomic forces have been fueling a contentious debate between brokers and underwriters on compensation, leading to a war of words in 2017 that saw leading players on both sides invest to reinforce their market positions. The same trends are also driving increased customization of products, increasing reliance on direct-to-consumer models and greater economies of scale for an increasingly large number of market participants. Collectively, we categorize these trends into the “three Cs” of consolidation, customization and collaboration. Consolidation: We continue to see overall consolidation of the brokerage market; Conning tracked more than 450 transactions through October 2017. This activity compares favorably with 537 transactions in 2016 and an annual average of 414 transactions from 2011 to 2015. Looking forward, the factors that are driving consolidation and greater levels of operational efficiency include a low-interest-rate environment, the presence of alternative capital providers and continuing demand for expanded broker capabilities. Customization: Over all, the desire for more localized market knowledge and custom products is a strong and recurring trend, with historically strong insurance hubs such as Lloyd’s recognizing the increasing need to meet local demands. For brokers, the need is clear: provide local knowledge coupled with global scale to rapidly place risks across geographies. Collaboration: Technologies such as blockchain have the potential to transform insurance processes, providing efficiency savings and greater levels of information to both brokers and their customers. Depending on blockchain's ultimate implementation, it is possible that brokers could operate within a fully electronic process or be innovated out of it (i.e., be replaced by electronic platforms and algorithms for many categories of risks). Ultimately, the broker’s place in the insurance lifecycle likely will remain despite increasing automation, but for those risks from which an intermediary can be removed, disintermediation will occur. For example, we have seen innovative carriers such as Hiscox offer a direct-to-consumer model for small commercial risks. Trends that had an impact on the personal lines market in prior years are beginning to affect commercial lines, with risk managers looking for more customized products and technology-driven innovations for even the most specific product classes. Consolidation: The commercial brokerage market has experienced continued consolidation, with the top 10 brokers generating 2.5 times more revenue than the next 90 brokers in the market (Conning Insurance Segment Report: Property – Casualty Distribution, p. 2). We believe that three trends are driving this M&A wave: 1. Alternative capital – Alternative capital providers (e.g., hedge funds, private equity) have continued to play a role in accelerating consolidation, lured by consistent revenue streams (many brokers have renewal rates in the 80% to 90% range), as well as systemic diversification outside of the debt and equity markets. With continuing low investment yields, the presence of alternative capital is expected to keep influencing the market. The “hunt for yield” has raised broker multiples and created a feedback loop of higher valuations and deal volumes. 2. Stagnant revenue – Despite some short-term hardening as a response to catastrophic events in the second half of 2017, we believe generally favorable loss experience and historically high policyholder surplus will continue to pressure pricing for the foreseeable future. As a result, premium pricing could remain soft across most commercial classes, thereby restricting both premium and commission growth. This ceiling on commission growth will challenge brokers of all sizes to improve their internal cost structures, particularly for back-office processing, which can represent well over half of their operating costs. They are increasingly able to cut costs through technology initiatives that automate standard or low-value processes, as well as introducing better analytics and sales tools to increase conversion and retention ratios. 3. Demand for local market presence – As risk managers struggle with increasingly complex risk exposures, they are looking for brokers to provide enhanced services across their enterprises. While this would seem to benefit the largest brokers, we believe there is a growing appetite for a seemingly contradictory skill set: a global footprint with enhanced local knowledge – which puts pressure on brokers to expand their footprint in new or existing locations. See also: Why Commercial Insurers Can Rock   For brokers whose operating model is “hub and spoke” with branch offices remitting central placement to a global office, we believe smaller specialist firms that can provide immediate service on the spot will continue to compete strongly against brokers that are unable to provide comparable, enhanced local support. In fact, this expectation goes beyond the brokerage side of the value chain to insurers and even placement markets such as Lloyd’s, which are increasingly challenged to provide more efficient and localized service. PwC’s 2014 “Risk Buyer Survey” noted that risk managers ranked price-driven change as the third most likely reason to switch brokerages, below service capabilities and geographic reach. This strongly implies that brokers must continue to expand their service offerings while simultaneously offering local market knowledge and global scale. Three trends will continue to fuel the broker consolidation wave: alternative investors bringing new capital to the market, stagnating broker revenue driving efficiencies of scale and demand for greater local market presence. Customization: Current operating models need reassessment as the insurance buyer demands change. Beyond price, buyers are looking for a variety of choices and flexibility when working with their insurance brokers. The demand for choice has begun to split the commercial market, with buyers falling into two behavioral groups:

• Insurance as a service: These buyers look for comprehensive risk management solutions and view insurance as a set of services (risk transfer, risk management and risk mitigation) that can lower their overall exposures to loss.
• Insurance as a product: These buyers view insurance as a product and transaction and therefore look for the best combination of price and ease of doing business.

“Insurance as a service” buyers look for bespoke risk management services beyond placement. Their carriers need to provide risk advisory, value-added services such as site audits and close interaction with the company’s internal finance and accounting departments to align their insurance portfolios to their risk exposure. A relevant example is Hartford Steam Boiler providing site inspection and engineering consulting as a complementary service that moves beyond risk transfer into a recurring advisory role. On the opposite end of the spectrum, “insurance as a product” buyers look for a variety of insurance choices and the ability to compare and build more modular insurance products as needed. These buyers look to on-line solutions for their purchases and want to easily understand products for which robo-advisers and comparison sites are becoming competitors to traditional brokerages. We believe there are a number of new market entrants that can challenge incumbents in the “insurance as a product” space:

• Direct-to-consumer carrier: Insurers such as Hiscox offer a consumer-facing website that allows SME markets to quote select liability exposures directly.
• E-brokerage: Internet brokers such as Coverhound allow purchasers to submit quote information on-line.
• Peer to peer: Startups like Lemonade and Bought by Many may displace the entire insurance model with peer-to-peer risk pooling.

Consumers are increasingly looking for more customized buying experiences and products from all industries. Commercial risk buyers are no different, and, as buyer expectations change, brokers will need to align their business models to their targeted buyer profiles. Collaboration — In the U.S. alone, Conning has estimated that 3,000 insurance companies and more than 30,000 agents and brokers serve the insurance market. Looking forward, blockchain could enable common data sharing across this fragmented market. Two possible scenarios could play out, broker-centric v. direct-to-consumer. In either model, blockchain has the potential to transform the (re)insurance value chain, including:

• Risk Management – Blockchain could be combined with other Internet of Things products (such as RIFD) to track the transport of high-value goods.
• Policy Validation – Blockchain implementation could support policy validation in real time, minimizing coverage validation and improving subrogation/recovery capabilities. Steps to create insurer-to-insurer (I2I) communications have already begun, with the carrier-led “B3i” initiative between Aegon, Munich Re, Zurich, SwissRe and Allianz to link the numerous insurer-specific use cases for blockchain.
• Reinsurance – Complex, multi-layer reinsurance contracts could be managed on a common blockchain, allowing participants to automatically track and manage ceded/assumed premiums and losses.

In addition, as we noted in Broking 2020, one way brokers can create value in this environment is to become risk-facilitation leaders. This role would connect various industry leaders, (re)insurance leaders and governmental officials on select risks (e.g., cyber) to discuss holistic risk management solutions. Brokers seem ideally placed to facilitate such discussions, which would provide them an opportunity to move beyond risk transfer and become a collaborative partner in their clients’ operational success. PwC’s 2014 Risk Buyer Survey supports this idea: 67% of risk managers considered their brokerage firm a “trusted adviser," versus 46% who simply viewed themselves as a “placer of coverage.” (Note: respondents were able to select multiple choices, resulting in values greater than 100%.) See also: Commercial Lines: Best Is Yet to Come   New technologies such as blockchain could provide the insurance industry a unique opportunity to collaborate. How these technologies will affect the industry remain to be seen, but forward-thinking (re)insurers are already establishing collaborative initiatives to establish proofs of concept. Implications

• Faced with the “three C’s” of consolidation, customization and collaboration, we believe brokers have an opportunity to implement changes before these trends cause even more disruptive change(s). Changing buyer demands will require brokerages to reassess their operating models to confirm they provide the correct balance of enhanced local market knowledge and scale efficiencies.
• Industry consolidation will further concentrate market power. Smaller brokerages need to determine the appropriate business strategy for a market where the top 10 brokerages produce 2.5 times as much revenue as the next 90 firms.
• Brokers could position themselves to compete in price-sensitive “insurance as a product” markets or establish risk management/advisory offerings to serve “insurance as a service” buyers.
• Emerging technologies such as blockchain have the potential to disrupt insurance placement and policy management processes. Brokers should establish a plan to leverage these emerging technologies to manage or avoid disruption from new market entrants.

This article was written by Richard Mayock, Jamie Yoder, Francois Ramette, Marie Carr, Matthew Wolff and Joseph Calandro Jr. You can find the PwC report here.

As debate continues to swirl about the future of U.S. healthcare regulation, here are the four high-level trends we may expect, and how stakeholders could be affected: 1. Healthy people may start leaving the individual market Recent changes eliminate the penalty for not having health insurance. Under the ACA, consumers were charged a penalty for the year they lacked coverage. But now, when consumers file their taxes, they won’t be charged a penalty. Without the penalty, younger and healthier consumers may choose to not have individual coverage. However, this doesn’t mean they don’t need or want health insurance coverage. Expect employers to play an increasingly important role in filling the gap. That being said, not all employers offer health insurance. It’s still ambiguous what the self-employed (think contract, freelance or gig workers) will do. Under the likely scenario in which many of the self-employed forgo insurance under the new regulation, the uninsured rate may increase. See also: A Road Map for Health Insurance   2. Carriers may have to adjust their business The premiums received from healthy people are generally a great hedge for the unhealthier, or higher-risk, populations for carriers. With the changes occurring in the individual market, carriers can expect a worsening loss ratio: The ratios paid by the premiums to the insurance company to cover settled claims begin to decrease. With the risk pool looking worse, carriers may concentrate on boosting their sales in relatively more stable segments. 3. Employer-sponsored coverage will be critical for employee retention If the ACA’s employer mandate is repealed, small businesses may no longer be required to provide affordable, minimum-value coverage to their full-time employees to avoid penalties. That being said, with many people losing their individual health coverage, employees may increasingly expect health coverage from their employers. Employer-sponsored benefits have always played a critical role in attracting and retaining talent, but, with the current instability in the market, many employees will appreciate the security of an employer-sponsored coverage plan more than ever. 4. States may have increasing regulatory power States may gain further flexibility to develop new healthcare models, including changes to affordability and choices offered. A number of states are pushing for their own legislation that could potentially give additional protection to residents beyond the federal level. Keep an eye on states like New York and California, which seek to create programs to increase benefits and requirements set by the ACA.

This article was written with Adrian Jones, a #traditionalindustry guy and insurtech investor who writes in his personal capacity. The authors’ opinions are solely their own, and only public data was used to create this article. *** “All the insurance players will be insurtech,” as Matteo titled his recent book, but some insurtechs have chosen to be insurers. Real insurers. Which means they file detailed financial statements. These obscure but public regulatory filings are a rare glimpse into the closely guarded workings of startups. Full-year 2017 filings for U.S.-based insurers were released earlier this month. Here’s what we found:

1. Underwriting results have been poor
2. It costs $15 million a year to run a startup insurtech carrier
3. Customer acquisition costs and back-office expenses (so far) matter more than efficiencies from digitization and legacy systems
4. Reinsurers are supporting insurtech by losing money, too
5. In recent history, the startup insurers that have won were active in markets not targeted by incumbents

We explain and show data for each of these points in this article. Context and Sources The most notable recent independent U.S. property/casualty insurtech startups that operated throughout 2017 as fully licensed insurers are Lemonade, Metromile and Root. Out of hundreds of U.S. insurtech startups, only a few have taken the hard route of being a fully licensed insurer. The lack of interest in becoming a regulated insurer is evidence against disruption evangelists who say that insurers are going to disappear or be killed by GAFA (Google, Apple, Facebook and Amazon). Despite the lack of interest, being a fully licensed insurer may prove to be a more durable business model than the alternatives like being an agency or otherwise depending on incumbents, and the three carrier startups that we analyze all have strong teams with powerful investors. Adrian has previously argued that being a fully licensed insurer may actually be the best long-term strategy – See: Six Questionable Things Said About Insurtech. The filings we reviewed are called “statutory statements.” and only insurers file them, not agencies, brokers or service providers. Statutory statements provide many of the traditional KPIs of insurance companies. Startups may use additional internal measures as they scale their company. Statutory statements typically do not include the financials of an insurer’s holding company or affiliated agencies, and companies have some flexibility in how they record certain numbers. But for all their limitations, statutory figures have the benefit of being time-tested, mostly standard across insurers and measuring critical indicators like loss ratio and net income. See also: Innovation: ‘Where Do We Start?’   Though the public can access statutory statements, it’s not always easy. Some insurers post them online, even private insurers. This is an area for improvement by both the #traditionalindustry and the startups that tell tales of “transparency” but don’t upload their statutory statement. The statistics Here are the key stats on three companies – from top line to bottom line: [caption id="attachment_30864" align="alignnone" width="563"] *The company has gross paid-in surplus of over $31 million so this figure is probably low. **Excludes a write-in for “revenue from parent for administrative costs,” possibly a way of topping up the company’s surplus[/caption] A combined ratio greater than 100% usually means a loss. Combined ratio doesn’t include returns from investing insurance reserves, but the days of double-digit bond yields are long gone. In a low-rate environment, investment income can’t offset poor technical results. The ratios are typically calculated on net earned premiums, but we also show a row where the expense ratio denominator is total direct premiums written, which may be more appropriate for growing books. Observations:

• Lemonade
  • Considering the statutory top line before reinsurance of $8,996,000 of gross premium written, it’s unclear how Lemonade calculated that “our total sales for 2017 topped $10 million.” The premiums reported by Lemonade may already have deducted the 20% fee paid to the affiliated agency – the parent company’s only source of income due to the giveaway model. (This would also explain why there is no commission and brokerage expense showing.)
  • Lemonade claims to have insured “over 100,000 homes.” If we assume that this figure includes rented apartments, then it implies premium written per policy of $90, or $7.50/month, if premium written is based on an annual policy.
  • Lemonade’s giveaway does not appear to be separately disclosed. Nonetheless, one of the brilliant aspects of the business model is the fact that even with a 791% combined ratio, Lemonade still has at least one or two pools doing well and thus enabling the PR of a giveback.
• Metromile
  • As the oldest startup in this group, Metromile has by far the highest premium, but the loss ratio is still nearly 100%. The expense ratio appears to have scaled down to a reasonable number, but the company puts $7 million of expense into “loss adjustment expense,” which may flatter the expense ratio.
• Root
  • As with Lemonade, the loss ratio around 160% is cause for concern – is this a few volatile claims (bad luck) or a problem with pricing? Time will tell.

A few other notable companies are worth a mention:

• Berkshire Hathaway Direct Insurance sells online via biBERK.com but isn’t a venture-backed startup. They wrote $6.4 million in premium last year, their second year of operations, most of it workers' compensation. Their loss ratio gross of reinsurance was 124%.
• Oscar is a startup brought to you by Jared Kushner and others who have plowed in $728 million already, with more funds being raised currently. Oscar shows no signs of profitability in its three main states:

1. Underwriting results have been poor All three companies have a gross loss ratio of near 100% or higher. (For reference, the industry average in 2016 was 72%). That means they have paid $1 as claims for each $1 earned from policyholders in the last 12 months. An insurance startup has to prove two critical things:

• Does the underwriting model work?
• Does the distribution model work?

We’ve been in debates over which is more important, and we always start with underwriting, because it takes no special talent to distribute a product that has been poorly underwritten (i.e. selling below cost). Underwriting quality/discipline is one of the “golden rules” of the insurance sector. Disrupt it at your investors’ peril. Underwriting returns have generally been poor, in some cases awful (double the industry average counts as awful in our book). Poor results are to be expected at first, even for the first several years. A single big loss can foul a year’s results in a small book. It can be hard to tell if that single loss is an anomaly or a failure in the model. Building an underwriting model is like playing whack-a-mole with a year’s time lag. Sometimes it’s difficult or impossible to address even widely known underwriting issues. 2. It costs $15 million a year to run a startup insurtech carrier All three companies incurred right about $15 million in run-rate expenses last year, of which $5 million to $6 million is headcount expense. It may be possible to keep the overall expense total closer to $10 million if one is especially lean, but the cost of operating in a regulated environment and building a book quickly mount. Some startups have organized as a managing general agency instead of a carrier. Thus they pay a “front” a fee of around 5% to produce their policies. However, even MGAs are state-licensed entities that are subject to most of the same regulation as carriers, so the expense saving of being an MGA is only a true savings at small volumes. The upshot: The capital raises of around $20 million to $30 million that we have recently heard about may only be good for around two years of operating expense, before any net underwriting losses. See also: Insurtech Is Ignoring 2/3 of Opportunity   Scale matters in insurance and venture capital, but it’s a double-edged sword in insurance. Scaling too quickly without underwriting excellence magnifies underwriting losses, but staying too small leaves the book volatile and the expense ratio high. Some startups have been active for several years and have not yet scaled, or even saw a reduction of premiums in the last year, but this may be better than scaling without sustainable underwriting results. Future financial statements will tell if any of the new players will gain a sustainable market share in a major business line in the U.S., or at least in a niche. 3. Customer acquisition costs and back-office expenses (so far) matter more than efficiencies from digitization and legacy systems. Insurance investors need to understand back-office expenses and distribution expenses, both of which are typically fixed costs for startups distributing directly to consumers. Here’s a look at what the three property/casualty insurance startups are spending money on. Beware that holding company expenses and affiliated agencies may or may not be reflected in the figures below, depending on the intercompany arrangements in place. [caption id="attachment_30866" align="alignnone" width="548"] *Likely included in commission and brokerage expense, which is net of $2.1 million ceded to reinsurers **Largest write-in item is “other professional services” at $891,000. ***Includes $1,958 of unpaid current year expenses and write-ins like “other technology” and “contractors”[/caption] Observations:

• Lemonade:
  • This startup is spending almost $1 in advertising for every $1 of premium they wrote ($7.7 million of advertising for $9 million of premium written). Again, if we assume Lemonade has insured 100,000 homes and apartments, then the customer acquisition cost (CAC) assuming only advertising expense is around $77. This is probably a measure that encourages the company’s backers, because the CAC of a renewal policy written directly is minimal, and the industry-average churn rate is single digits in U.S.
  • The regulatory and overhead costs are considerable – notice lines like legal and auditing; taxes, licenses and fees; and some of the salary expense.
  • The volumes have to continue to grow exponentially for some years to get the cost base (also net advertising) lower than the 20% of the premium required to make a profit for the parent company (for reference, the market average expense ratio was 28%). Recall that Lemonade’s parent or affiliates take a 20% flat fee up front for their profits and expenses and gives to charity anything left after paying claims and reinsurance.
• Metromile:
  • Has the highest tax expense, perhaps because it is selling the most, with many states charging premium tax as a percentage of the policy value.
  • Their “legal and auditing” expense is probably much higher but is put into “other.”
  • Note the absence of advertising expense but large commission and brokerage expense, partially ceded to reinsurers. Accounting treatments, as ever, can vary by company.
• Root
  • The company’s small volume makes it difficult to run the same absolute expenses as Lemonade and Metromile, but it might not be wise to grow a book running a loss ratio of more than 150%.
  • Has no telegraph expense (woo-hoo!).
  • Unclear why the company has almost $2 million of unpaid expense.

Advertising expense vs. pricing. Old-fashioned insurance agents are a variable cost that scales up with the business – the agent absorbs fixed advertising, occupancy and salary costs in exchange for a variable commission. But in the direct distribution models favored by many startups, variable costs and agents’ costs become fixed costs borne by the startup. (True, some can be kept variable, as we discuss below.) Fixed costs need to be amortized over more premium volume, which requires yet more fixed costs (e.g. advertising) to solve. Insurtech carriers from the dot.com era like eSurance and Trupanion are still investing heavily in advertising and producing losses or barely breaking even. They would probably argue that they could eliminate much of their expense and “harvest” an attractive book of business for years to come – which may be true. The U.S. churn rate in personal auto and home insurance can be as low as single digits, far lower than many Western countries. Because customer-retention cost is much lower than customer-acquisition cost, loyalty is absolutely critical to non-life insurers, particularly in a direct distribution model. (Bain & Co. – both of us are alumni of this consulting firm -- has done excellent work on loyalty in insurance.) It is tempting to acquire insurance customers by underpricing and later transforming them into profitable customers. A loss ratio of more than 100% implies a pricing problem, not a problem with the underwriting model. Insurers with a customer base that came for cheap insurance and expects it to continue will find their market vanishes when they begin repricing to bring loss ratios to acceptable levels, destroying any value from customer loyalty and forcing a pivot to a new value proposition. In some cases, it may be necessary to double prices before underwriting price adequacy can be achieved, even ignoring expenses. (Most U.S. state regulators also have broad powers to disapprove, block or roll back rate increases – for more on the maze of state regulation, see this study from the R Street Institute.) The API approach – a B2B2C model based on distributing the product through the digital fronts of third parties – has become “the new black” to transform fixed acquisition costs in success fees linked to the volumes. This model shows promise, provided that distribution partners do not extract too much value from the competitive insurance market. The point for founders and investors today is to be prepared mentally and financially for a long road to profitability with tens of millions sunk before it becomes apparent whether the underwriting works and whether the relationship between CAC/distribution, fixed expenses and customer loyalty can produce a sustainable and profitable business. 4. Reinsurers are supporting insurtech by losing money, too Some members of the #traditionalindustry have strongly supported the development of insurtech through investment in equity, providing regulatory capital, providing risk capacity and sharing technical expertise. Startup insurers typically are reliant on reinsurance as a form of capital because (1) it can be cheaper than venture capital, (2) startups typically need reinsurance to hold their rating and (3) the strong backing of a highly rated reinsurer shows validation of the company’s business model, just like the backing of the best VCs provides. The carrier model has real advantages concerning reinsurance: reinsurance is easier to arrange and more flexible than an MGA relationship. Many successful agencies find that their economics would be better if they were able to retain some of the risk they produce instead of writing on behalf of a licensed carrier and ceding that carrier all but a commission. Here is a look at results disaggregated for reinsurance: [caption id="attachment_30867" align="alignnone" width="550"] (Source: Schedule P; subject to minor variations compared to prior tables)[/caption] Observations:

• Lemonade seems to have a great reinsurance scheme, but they have to hope that reinsurers continue to take $5 in losses for every $1 in premium ceded to them. The amounts ceded are small, and Lemonade has a big panel of reinsurers.
• Metromile and Root do not appear to get much loss ratio benefit from their reinsurance.

It is a great experience for a giant reinsurer to work with a small and innovative startup. The expected losses in dollar terms are negligible if compared with the value of the lessons learned, the culture created and the halo the reinsurer may partially claim. Startups need to find reinsurers that are both flexible and prepared for losses, potentially for several years. But startups cannot count on reinsurers to take losses forever. 5. In recent history, the startup insurers that have won were active in markets not targeted by incumbents. Since 2000, at least 34 property/casualty insurers were formed in the U.S. without the aid of a powerful parent and earned more than $10 million in premium in 2016. Of these 34 startup insurers:

• 21 specialized in high-volatility catastrophic risk like hurricanes or earthquakes. Incumbent carriers have largely stopped or greatly limited their new business in certain catastrophe-exposed regions, sometimes because they felt that regulators or competitors (often government-run pools) did not allow them to charge adequate premiums.
• Nine were motor insurers, mostly non-standard motor. Non-standard means bad drivers, exotic cars or other risk factors that “standard” carriers avoid.
• Two don’t have a rating.
• Two remain: Trupanion (a pet insurer) and ReliaMax (which insurers student loans).

Adrian readily acknowledges that some carriers aren’t picked up by his screen, such as financial lines companies like Essent. Essent is a Bermuda-based mortgage re/insurer that wrote $570 million of premium at a 33% combined ratio in 2017 after a standing start in 2008 – which might be the most successful U.S.-market insurance startup in the last decade. Other startups were sold along the way, were sponsored by a powerful parent or purchased an older “shell” and inverted into it. The point is that successful insurers have rarely won by attacking strong incumbents in their core markets. They have won by figuring out ways to write difficult risks better than incumbents, have created markets (like pet insurance) or have entered seriously dislocated markets with good timing (like writing mortgage insurance in 2009). This leads to several questions:

• Are urban millennials actually a new market that is being ignored by incumbents?
• Are direct and B2B2C distribution really new markets that incumbents cannot penetrate? Can “platformification” be profitable over the long term?
• How quickly can new/digital systems show cost and pricing benefits over legacy systems that incumbents are retooling aggressively today? How long before the new systems become a legacy for the newcomer that created them?
• Are new underwriting and claims techniques like the use of big data sufficiently disruptive to allow entry to tightly guarded markets?

There are early signs that all of these questions will be answered favorably for at least a couple of startups but not without some bumps along the way. See also: Insurance Coverage Porn   Previous waves of technological changes have allowed new competitors to rise to prominence – think of the big multi-liners that dominated the skyline of Hartford CT with mainframe technology in the ‘50s and ‘60s, the specialists like WR Berkley built on personal computers in the ‘70s and ‘80s and the Bermuda CAT specialists of the ‘90s and ‘00s. Will the next wave of technology-driven insurers include the ones today putting up 150%-plus loss ratios? Perhaps. *** Conclusion Technology changes a lot, but it doesn’t change fundamental facts that make insurance hard. As we said at the start, we admire and support the companies that choose to become fully licensed insurers. They have taken the harder path to market but may be more durable in the long term. We think commentators should be very careful before criticizing startup insurers for not having great performance on the loss ratio and expense ratio in the first few years. We also think companies need to be careful about overselling the awesomeness of their business model too early. To use Matteo’s 4Ps framework to judge any insurtech initiative – from startups or incumbents, we have yet to know whether/how new challengers can leverage technology to outperform incumbents on technical profitability, productivity, proximity with the clients and persistency of the book of business. Whoever is capable of doing this will survive and may be the next big winner in insurance. Insurtech startup carriers, their investors and their reinsurers need to be prepared for a long and expensive startup phase. Insurance is a get-rich-slowly business, but it is also a durable business that rewards patience, wise risk-taking, data analysis and operational excellence. And for the futurists, disruption evangelists, black swan hunters and anyone who just learned more about insurance than you ever wanted to know, we hope these dispatches from insurtech Survival Island have been informative for examining startup financials in insurance or other markets where you operate. Please follow Adrian and Matteo on LinkedIn for future posts.

Industry events, like the recent Reinsurance Association of America’s (RAA) Cat Risk Management conference, are always a great way to take the pulse of the industry and connect with people. I’ve been attending RAA’s conference on behalf of SpatialKey for years, and I generally come away invigorated by my conversations with clients and prospects. This year, however, the energy among these conversations was a bit different. That energy had more urgency and emotion behind it. It’s clear the unprecedented events of 2017 have taken a toll on people, and there’s a compelling need to do something about it. Individuals and teams alike have worked tirelessly; while the events have passed, the emotional fatigue is left in their wake. I can empathize. While insurers worked diligently to serve insureds during back-to-back events, at SpatialKey, we worked around-the-clock to serve up timely, expert data to our insurance clients. The job of 24/7 data put an enormous strain on our own employees—and we have a dedicated data team! Insurers, which lack the expertise or resources to consume and work with the sheer volume and complexity of data that was being put out by multiple data providers, may have found it grueling. That exhaustion still lingers in the faces of the people I spoke with at RAA. And, what’s bubbling to the surface now is the underlying problem:

There’s a ton of data and no easy way for insurers to consume it and act on it.

Put more eloquently, there’s a gap between the wealth of data now available and insurers’ ability to quickly process, contextualize and derive insight from that data. Not just an event-response problem While this transforming-data-into-insight problem was illuminated by 2017’s catastrophic events, this is not just an event-response problem. This is not an underwriting problem. This is not a new problem! Events like those of 2017 touch the entire insurance community—insurers and solutions providers alike. And together we need to solve the problem. What I heard time and again at RAA is that everyone is generally frustrated by a lack of process and an easy way to consume the frequent and sophisticated data that expert providers are putting out during events like Harvey, Irma, Maria, the Mexico City earthquake and the California wildfires. Insurance professionals are expected to use legacy or complex GIS tools to extract and consume expert data from providers. Yet, I didn’t speak to a single GIS expert. It doesn’t make sense. See also: 5 Ways Data Allows for Value-Based Care There’s an opportunity cost to the productivity that employees could be generating elsewhere Nobody has the time to teach himself a complicated GIS solution to look at data while working to deploy help to customers in the wake of catastrophe.

No underwriter has the time to get up to speed on a GIS solution that takes years to learn while trying to win business quickly.

It’s like giving your star quarterback a basketball and expecting him to win the Super Bowl with it. He’s talented, he can throw that ball, but he’ll never throw a winning pass with a basketball. It’s clunky, it’s cumbersome and it just doesn’t fly as fast. In the same way, folks across claims, exposure management and underwriting can’t quickly consume and understand data with legacy or complex tools that weren't created for their specific uses. With all the data comes challenge, and a call for ways to interpret information more efficiently We’d all like to think 2017 was an anomaly. That we won’t have a replay of such extreme events. However, 2017 may only be a precursor of what’s to come. Even so, the insurance industry is poised to handle events like these better than ever before because there’s now a wealth of expert data and models. That’s a good thing, and it energizes me! Data quality and modeling is becoming better all the time—more accuracy, better science, higher resolution—as we can attest to because of working with providers like NOAA, USGS, KatRisk, JBA, RedZone, Swiss Re, Impact Forecasting and HazardHub. But, with all this data choice comes challenge. And a call for ways to interpret information more efficiently. We know it’s possible because we see our insurance clients succeeding every day when it comes to accessing, analyzing and interpreting data within SpatialKey. While late 2017 was exhausting and overwhelming, I’m inspired to see so much data come to life in platforms like ours at SpatialKey, and energized to see how empowering it is for the people using it. See also: How to Earn Consumers’ Trust   Insurers, don’t try to solve this problem alone The solution is collaboration: partnering with experts who have technology purpose-built to consume data quickly and produce intelligence that insurers can readily act on. I’m not advocating collaboration because I’m at the helm of a company that fills the data gap. I saw a lot of pain at RAA in the faces of my insurance friends, and there’s quite honestly just a simple way to solve this.

Processing information is a basic need that has become incredibly complex and time-consuming for insurers.

This can be easily outsourced, so insurance professionals can go about analyzing, managing and mitigating risk. Insurers have an opportunity right now to empower underwriters with the intelligence they need to keep losses on the scale of 2017 from happening again — and to empower them to understand data without complex GIS solutions. Start now. Your shareholders will thank you later.

The Berkshire Hathaway annual report is one of my favorite reads. I always find a mountain of wisdom coupled with humility from one of my mentors, Warren Buffett. He doesn’t know he’s my mentor, but I treat him as one by reading and reflecting on what is in these annual letters. I would recommend you do the same; they’re available free of charge online. There was a doozy of a sentence in the latest—right there on page 8—discussing the performance of Berkshire’s insurance operations, which make up the core of Berkshire’s business: “We believe that the annual probability of a U.S. mega-catastrophe causing $400 billion or more of insured losses is about 2%.” Sorry, Mr. Buffett, I have some questions for you on that one. See also: Whiff of Market-Based Healthcare Change?   After reading those words, I quickly ran a CATRADER industry exceedance probability (EP) curve for the U.S. My analysis included the perils of hurricane (including storm surge), earthquake (including tsunami, landslide, liquefaction, fire-following and sprinkler leakage), severe thunderstorm (which includes tornadoes, hail and straight-line wind), winter storm (which includes wind, freezing temperatures and winter precipitation) and wildfire. I used the latest estimates of take-up rates (the percentage of properties actually insured against these perils) and took into account demand surge (the increase in the price of labor and materials that can follow disasters). Bottom line, we believe that the probability of $400 billion in insured losses from a single mega-catastrophe in a given year is far more remote—between 0.1% and 0.01% EP. Buffett is putting this at a 2% EP (or a 50-year return period), which is a gulf of difference. In fact, it is worth noting that, by AIR estimates, the costliest disaster in U.S. history in the last 100-plus years—indexed to today’s dollars and today’s exposures—was the Great Miami Hurricane of 1926. Were that to recur today, AIR estimates it would cost the industry roughly $128 billion.  So, what is Buffett basing his view on? In 2009, he famously said “Beware of geeks bearing formulas.... Indeed, the stupefying losses in mortgage-related securities came in large part because of flawed, history-based models used by salesmen, rating agencies and investors.” Obviously, this was a reference to the 2008 financial crisis and the use of models by banks. His view on catastrophe models, however, has never been made public. See also: Why Risk Management Certifications Matter  Assuming Buffett’s point of view was not model-based, it would be good to know his methods. For example, was it based on some estimate of insured exposures and a PML%, as was common in the pre–catastrophe model days? But he didn’t get to that level of detail. It would be interesting to know if this is also the view of Ajit Jain, his head of insurance operations, and now vice chairman of Berkshire? I have lots of questions, and I am not holding my breath for Buffett to respond to this blog. But it would be great to get your thoughts below.