Bermuda pays tribute to the Fates. It would, however, be tragic for insurance companies based in Bermuda to surrender themselves to the forces of whimsy and chance. It does not serve the interests of this island nation, of this remnant of the British Empire, to be true to the literal meaning of its motto, "Quo Fata Ferunt," which means "Whither the Fates Carry Us." Not when Bermuda is so attractive to so many insurers. Not when the symbols of this territory represent what most appeals to the insurance industry as a whole. The long continuity of laws, language, literature, history and tradition—all of these things, and more, belong to Bermuda. They come together under the Red Ensign: one flag for two countries, combining the Union Jack with Bermuda’s coat of arms. Promoting that flag as an emblem of security, as a haven of economic stability amid a sea (or a triangle) of physical tumult in which storms strike and hurricanes gather strength—in which the pastels of island homes turn pale beneath a wrathful sky—that that flag is still there is the modern-day story of Bermuda. See also: Awareness: The Best Insurance Policy   To see the Union Jack is to see a terrestrial body with celestial power. It is to see an icon of permanence from a flag without stars. It is to see a light of safety, alerting captains to steer clear of the rocks and reefs that threaten passengers and crew: a warning painted on a shield—of a wrecked ship tossed by a tempest—where the red lion of Britannia is the pride of Bermuda and the protector of the innocent and true. According to Janil Jeal, director of overseas operations for LogoDesign.net: “Few symbols are as potent as a flag. It can unify a people, just as it can be a universal badge of freedom. It can inspire citizens and companies to do their best.” Put another way, insurers based in Bermuda should fly the flag. They should do more to explain why the island is the ideal locale for their industry. They should do so to report—and reinforce—what no amount of marketing can match and no barrage of advertising can equal: that the flag signifies what insurers crave and consumers want, that it sends the right signal about reducing risk, that it stands as its own reward. To get to that point requires repetition. Such is the best insurance policy for the insurance industry: to condense—and to convey—the economic benefits of Bermuda into something tangible, a flag (or the image of a flag), that flies outside all manner of buildings, that flies highest in the island’s capital city, that flies atop institutions of financial capital. Fly the flag—but do not forsake its importance. See also: 3 Reasons Millennials Should Join Industry   Do not dilute its presence by making it ever-present. Do not render it tacky. Do not ruin it by relegating to the realm of some tinhorn dictator Recognize, instead, why it is sacred. Recognize that it is a flag worthy of respect, whose worth accrues to insurers willing to preserve, protect and defend its existence. May it continue to endure.

Yet another hurricane season has left a broad swath of America’s coast in recovery mode following a once-in-a-generation storm, and wildfires are devastating California. The disasters remind the rest of us how fortunate we are to be safe. They remind government agencies about the importance of preparedness. And they remind employers about the importance of risk managers. Disaster response is part of the job description for risk managers, of course, but that doesn’t make it any easier to suddenly be the most important person at the company in the exact moment that the situation is at its least predictable and most frenetic. Lives are in danger, homes are being inundated or burned, entire communities are scrambling for safety -- and you’re the person who is supposed to have answers and a plan. The situation is one that insurance companies can understand. People may not fully appreciate their role when things are going well, but, when things go wrong, clients expect an immediate and efficient response. It may seem that the work of a risk manager or insurance company begins after a crisis, but those working in either field know that it’s the careful work of preparing that makes a successful response possible. Some of the most effective risk managers are also realizing that tools and capabilities that allow for efficient insurance claims intake and processing can serve businesses and risk managers before a crisis. Consider Tropical Storm Harvey as it lined up on the U.S. Gulf Coast a year ago, making landfall near Corpus Christi on Aug. 25 and careening inland toward San Antonio before reversing back to the Gulf of Mexico and crashing into Houston, where it did even more damage. Even the most dramatic satellite images or simulations were never going to prepare people on the ground for what was coming. That sort of work needs to be done on a personalized level, through systems that tell people about their specific risk levels, what to expect in their neighborhood, when to expect it and what to do about it. And then what to do if those initial warnings weren’t heeded. See also: Natural Disasters and Risk Management   It’s the sort of work that third-party administrators (TPAs) for insurance carriers were preparing for as Texas braced for the most damaging storm to strike the continental U.S. since 2005. As risk managers for companies in the U.S. Gulf Coast reviewed their widely distributed workforce and facilities in the storm’s path, they, too, realized that they would soon be managing overwhelmed phone lines and routing calls to keep thousands of employees informed and as safe as possible through the storm. The very same processes that an insurance company or its TPA uses to manage the wave of claims that follow a catastrophe are extremely well-suited to help the companies threatened by a disaster to be operationally resilient throughout. Just as importantly, a well-planned disaster response starts days before the crisis hits. In the social media age, it takes rigorous planning and agile systems to stay ahead of the myriad information channels employees are plugged into. A disaster is overwhelming even for the biggest companies with well-resourced risk management teams. It can be a knock-out punch for smaller firms. About 25% of businesses don’t reopen after a disaster has passed, according to Insurance Information Institute estimates. More than a third of small businesses have no emergency plans for severe weather or natural disasters, according to a report from the U.S. Chamber of Commerce and Met Life in May. With the power and frequency of storms and other natural disasters on the rise, companies are searching for solutions. A San Antonio-based construction and engineering company with dozens of offices and thousands of employees through Texas, Louisiana and the rest of the Gulf Coast saw the crisis coming. Its insurance needs would come soon enough, but, more immediately, it needed to communicate with its employees to keep them safe and informed about operations. The company had never expected to have to equip so many employees for the magnitude of disruption that Harvey represented, and realized with only days to spare that its ability to survive the storm depended on being better prepared for it. The company needed a way to communicate with its employees in the storm’s dangerous and dynamic environment. Most importantly, this would help their employees and families survive the storm, but it would also put the company in a position to spring back faster and outcompete others who took longer to get back on their feet. Taking advantage of today's technological capabilities, it found a service already experienced in rapidly standing up the type of infrastructure the company needed – a hotline, trained operators, automated routing of issues – and reached out to an intake specialist on a Friday evening to build a crisis response system by Monday morning. Practically overnight, the company gave its human resources department a tool for employees to check in and get information about the company’s response and what their own next steps should be. As the storm continued to batter the region, the company was able to swiftly respond to facility concerns, reorganize employees to where they were needed and direct employees to the resources they needed to start rebuilding their lives. In the worst-hit areas, the company made sure that employees were out of harm's way and being given reliable updates, as opposed to relying on digital media and social sharing, which can become a default information source in the absence of a company system that can scale and configure fast. Those outside sources of information can quickly move into the vacuum left by a company’s inability to take and react to information and can become a new crisis in and of themselves, spawning rumors and unchallenged facts. When the storm waters started to recede, this Gulf region firm was still strong. Because the risk management and human resources teams did not try to ride out the storm with legacy systems supporting their work, instead finding more sophisticated solutions, they maintained the trust of their workforce and the integrity of their business. There are critical lessons that can be learned from this kind of quick intake system start and the attempt to build a resilient system:

• A strong contact center team is key, but not sufficient. The technology is available to make sure that the human interactions at the center of disaster response are more accurate, efficient and effective.
• Advanced dissemination and escalation engines are indispensable. Bad information spread over social media can exacerbate the crisis, and the only way to counter it is to make sure the right messages are reaching people faster.
• Intake systems need to start fast and then keep up with a rush of information. You have to prepare for the unexpected. Companies can’t always know what’s coming their way, so they need systems that can set up overnight.
• You have to be ready to adapt at a moment’s notice. Dynamic, rules-based intake scripts are not only essential at the outset, they allow for an intake process capable of adjusting to changing circumstances.

In a crisis, unexpected events are impossible to avoid, and a technology-driven system employing smart automation will take the unique business rules that every risk manager has and make their complexity manageable for intake specialists, minimizing disruptions. See also: 5 Techniques for Managing a Disaster   A consistent concern among risk managers is that no matter how well one forecasts threats, develops detailed plans and runs drills against them, the speed and scale with which crisis can hit seems to be increasing. Preparation can start to seem impossible, but it isn’t. It just calls for new tools. With this year's hurricanes and the harrowing fire season, risk managers are once again reviewing their ability to respond, and a close, detailed look at lessons learned from previous events like Harvey, and putting into place the countermeasures necessary to prevent unwanted surprises, can keep risk managers operating efficiently in the next crisis.

As artificial intelligence (AI)-based solutions are introduced to the insurance industry and a new wave of insurtech companies rise up, it can be difficult to see the forest for the trees. AI-based products are designed to do a great number of things today: solve complex problems associated with care and claims in a fraction of the time; automate operations and improve efficiency; and enable greater, more personalized customer service — just to name a few potential benefits. Every solution a vendor tries to sell you can sound compelling on the surface. But the million-dollar question is whether there is tangible value for your organization. Although it can be tempting to gravitate toward a bright, shiny object, there needs to be a legitimate business reason for adoption other than “everyone is doing it.” I recommend taking the following inventory as you delve into AI to ensure you maximize your investment. Know what specific problem you are solving. Is the problem you are solving a priority? One of the biggest challenges lies in identifying how and why AI fits into the big picture of your organization. Many executives hear a persuasive use case for a new technology and get very excited about how AI can be applied within their own company. This is logical; it’s human nature and fits with how we learn about and discover things in an age when everyone is overcommitted to tasks that are perceived as a higher priority. This approach should be avoided, however. See also: How to Use AI in Customer Service   AI makes it possible to capture so much more data than we’ve ever been able to get our hands on before, but, unless this data pertains to an issue you need to address, it may be deprioritized … data for data’s sake. McKinsey suggests that the process of determining uses for AI that drive value “will require exploring hypothesis-driven scenarios in order to understand and highlight where and when disruption might occur — and what it means for certain business lines.” I recommend starting with a problem, one that is causing real pain to your employees, customers or partners or affecting your bottom line. Then work backward to determine how AI and machine learning could be used to develop something better than the status quo. Now, do a little research. Consult with analysts. Engage with vendors. Try out products and determine how they might work at scale, consult with references and have users test them. Those products now exist or are rapidly coming to market, but, if you don’t have a handle on your needs or know what you are looking for, you risk choosing a solution that fails to live up to the high expectations for AI. Evaluate for simplicity This may be stating the obvious, but that doesn’t make it any less essential. Any AI-based product, service or application must be easy to use. This point is non-negotiable. Your people are probably long-entrenched in certain processes and ways of doing things. There could be some resistance to change, and, if a solution isn’t simple and intuitive, teams won’t adopt it. As a result, even if a system or application yields the best data and insights on earth, your company will never derive maximum value from it. The consumerization of IT has ensured that people of all demographics expect and demand easy-to-use software. Therefore, you have to build or buy something that everyone feels comfortable with and wants to adopt. If they can see how it makes their day-to-day job more rewarding, all the better. Have a plan to embed it in your processes and measure ROI You have great data, and people suddenly have access to information they never had before. Now, what do you actually do with that information? What is the next step? You must consider how it enters into your processes. Knowing exactly how the product will be used will not only help you make the implementation painless, but also will define what product functionality is critical for your business. Take your existing workflow, and plan to integrate your AI application into it so that you’re not creating more work, nor are you making the transition for others harder than it needs to be. To accomplish this effectively, you need to make sure to involve at least one team member with deep operational experience, who knows processes and workflows, and can educate and collaborate with data scientists and technologists to ensure all of the organization’s needs are met. This team will work together to develop the best processes and practices for leveraging new levels of intelligence. If your new application doesn’t drive ROI, then it’s nothing more than a shiny new gadget. Create a plan to track and measure performance before you implement anything new. And integrate as much measurement as you can into your existing processes. See also: AI Still Needs Business Expertise   Over the next decade, we will see huge advances in how the insurance industry conducts business. The formula for success is knitting each of these pieces together: deep data science with a purpose, accessible through consumer-grade software that is guided by operational expertise. To ascertain the actual value of these components, track how people use AI-based tools as well as what the results are over the short and long term. Strive toward “better than before” rather than perfection — and continue iterating. AI is poised to profoundly change the industry, but implementation of these exciting new technologies is not a one-and-done thing — it’s a journey. If all goes according to plan, and AI lives up to potential, your organization will reap tremendous rewards. As first published in DATAVERSITY.

Risk management activities of insurance companies are mainly based on three risk types: whole portfolio, supplementary and others. In “others,” two risk types -- operational risk and credit risk -- stand out with their financial impacts and frequencies. Credit risk is defined as “the potential that insurance company’s borrowers or counterparties will fail to meet their obligations in accordance with agreed terms.” The main goal in credit risk management is maximizing insurance company’s risk-adjusted rate of return by maintaining credit-risk exposure within acceptable parameters. Credit risk has six sub-types:

1. Credit default risk
2. Concentration risk,
3. Counterparty risk,
4. Country risk,
5. Sovereign risk and
6. Settlement risk.

Furthermore, traditional credit risk management is based on manual or semi-manual assessment of these domains:

• Detailed assessment of counterparties,
• Financial strength,
• Industry position,
• Qualitative factors and
• Underlying credit exposures.

The first trigger of change in credit risk management was Solvency II. After implementation of the capital regime in Euro Zone, insurance and reinsurance companies integrated further credit risk assessment tools into their internal models, because the credit risk management approach was found very weak in standard model of EIOPA. The second evolution in credit risk management comes not with another capital regime but with technology: insurtech. Insurtech is converting credit risk management into a new form like many other components in insurance business. See also: A ‘Credit Score’ for Your Cyber Risk?   For bringing into the complex structure of risk management with basic inputs, we can classify the insurtech effect on credit risk management mainly on two points. The first point defines the philosophy behind risk management activities, and the second point defines actions:

1. Maximizing a company’s risk-adjusted rate of return by maintaining correct credit risk exposure within the risk appetite of the company and maintaining sufficient risk-return discipline in credit risk management process.
2. Covering all insurance/reinsurance transactions and identification, measurement and monitoring of transactions with embedded credit risk.

The risk-adjusted return is generally defined as a concept that measures real value of risk and enables a company to make comparisons between risk taking and risk aversion. This variable shows real value of business and aims at maximizing efficiency on capital management. In business today, correct allocation of limited capital should be the main object behind all activities of a company, and risk-adjusted rate of return is the pointer that makes this objective visible. Insurtech also converts the calculation methodology of risk-adjusted return. With a more sophisticated methodology, risk managers can cover thousands of variables and calculate a value very close to real, risk-adjusted return exposure. The second point, covering all transactions where credit risk arises, is the inception point of actions. The definition covers not just financial transactions but also all insurance/reinsurance transactions performed during daily business cycles. Furthermore, because of the complex structure of finance, not just loans, the most obvious source of credit risk, but also other structured financial instruments, like trade financing, foreign exchange transactions, financial futures, swaps, bonds, equities, options, etc., should be assessed in an effective credit risk management function. Naturally, the variety of sources brings a huge amount of data, which could not be managed manually, especially by a function like risk management, which should be always preventive and pioneer. One of insurtech's dimensions, big data management, helps risk management professionals especially on this point. With the organization, administration and governance functions of big data management, not just structured data but also unstructured data coming out from mentioned transactions will be measured, analyzed, grouped and monitored according to their likelihood and magnitude within seconds. See also: How to Adapt to the Growing ‘Risk Shift’   Credit risk management is a crucial tool among other risk management functions. Effective credit risk management and efficient capital management make companies ready and solid for their next step on investment, acquisitions and every step they take for their existence.

The insurance industry is hundreds of years old and full of ingrained perceptions and antiquated processes, which continue to cause frustration among customers. Insurers know they need to innovate, but the question is – how? How can global insurers, which have been operating in and underwriting insurance the same way for hundreds of years, know which types of technology they need to meet consumer demand and remain competitive in a rapidly changing market? Insurance technology is the missing link. The insurtech market is growing rapidly, and players have to be prepared to adapt. There is little time to sit idle, because, if you can’t keep up with consumer demands today, there is a small chance you’ll keep up with them tomorrow. Whether it’s the need for small business cyber insurance or the necessity for pay-per-use homeshare insurance, insurance is moving away from the traditional model. The on-demand culture and sharing economy continue to disrupt industries across music, entertainment, transportation and payments. The wave of acceptance by consumers flags a fundamental shift in consumer behavior, where consumers can get what they want now, without delayed gratification. The insurance industry is the next in line, ripe for disruption. With the continued explosion of rideshare and homeshare applications, the traditional models for car and home insurance are not substantial enough to protect individuals using their personal property as a commercial asset. See also: Insuring a ‘Slice’ of the On-Demand Economy   While the battle of insurers vs. insurtechs continues, we firmly believe that both parties have equally valuable offerings to bring to the table. To truly drive the industry forward, an open-source cloud platform that allows insurers to quickly build, test and deploy their own on-demand insurance products will be the beginning of the insurance industry transformation in response to the sharing and gig economy. Legacy carriers have centuries of experience writing insurance policies and have the historic industry knowledge that insurtechs need to be able to grow – emerging industry players that don’t see that are missing a huge opportunity. On the flip side, technology is changing fast and, therefore, changing the way people work and live. It’s the new norm for consumers to get what they want, when they want it; and while insurers might have the industry knowledge needed to be competitive, what most don’t have is the ability to be agile to protect against emerging risks and meet increasingly demanding customer needs. Largely due to the lack of technology and resources available, our partners tell us there is much higher value in cooperation, as insurtechs have the technical resources insurers need to improve time to market. For both parties, it’s a win, win. Cloud platforms are allowing insurers to quickly ideate, experiment, test and deploy new, on-demand insurance products. Since making our Insurance Cloud Services platform publicly available in January 2018, we’ve experienced higher-than-anticipated demand, causing us to make a heightened focus on global expansion as insurers increasingly realize the need to adopt agile technology. AXA XL and the Co-operators both launched their first on-demand cyber and homeshare insurance products in the last two months. Through cooperation vs. combat, the two are now ahead of the curve, with AXA XL’s product being the first ever on-demand cyber insurance product in market, and Co-operators launching the first on-demand homeshare insurance solution in Canada, allowing the company both to reach and work with customers in a way that works for them vs. the other way around. See also: A New Way to Develop Products   The path forward for fully digital on-demand insurance is moving quickly, and, as the industry continues to experience disruption, it’s critical that insurers consider not only what type of technology they need to improve internal processes and compete in the market, but also the changing, increasingly in-demand needs of their customers. Insurtechs that are able to provide solutions for insurers that allow them to quickly ideate, experiment with and launch new products are set to lead the future of the insurance evolution.

Reference-based pricing, also called metric-based pricing, is an alternative to the traditional PPO model that offers substantial cost saving and benefits for self-funded employers by leveraging fair and transparent practices. If you aren’t familiar with reference-based pricing, it could seem disruptive to your operations to make a change. However, many self-funded employers are implementing this alternative and reaping the benefits. How does reference-based pricing compare with the PPO employers are currently offering to their employees? PPO: The most prevalent form of health insurance, where the annual cost for employers increases year-over-year and high deductibles are a challenge for patients. Members use a network of hospitals and doctors under a discount to take advantage of pre-negotiated costs. Oftentimes, these discounts vary widely inside the network and result in fluctuating costs. An independent study conducted by Castlight Health, a San Francisco-based healthcare price transparency company, shows PPO allowable amounts for common procedures swing as much as 500% in some regions. The variable discounts are calculated on variable billed charges from the hospitals’ chargemaster, prices that many times are inflated and fluctuate dramatically between hospitals for the same service. In one example, the California Public Employees’ Retirement System (CalPERS), which manages the largest public employee benefit fund in the U.S, found that facilities throughout the state charged vastly different rates — between $15,000 and $110,000 — for a hip or knee replacement. Referenced-based pricing: A modern solution for self-funded employers to manage healthcare costs for their business and employees. Under this model, reimbursements to providers are based on the actual cost to deliver service or Medicare reimbursements. This more level approach starts at the bottom and adds a fair profit margin. Working with a reputable solution provider, self-funded employers can save up to 30% in their first year after switching to reference-based pricing. See also: Myths on Reference-Based Pricing   It’s not uncommon for employers to question making the switch from a PPO to a reference-based model. Is it worthwhile to make a change? Will employees understand the change? Does it require a lot of work? Let’s explore six tips for a smooth transition to reference-based pricing without disruption. 1. Do a little homework: Start by finding an experienced provider Employers should only work with partners that are trusted and experienced with providing successful reference-based pricing solutions. Look for a provider that has more than five years of experience auditing claims in all 50 states, welcomes reference calls, shares case studies from successful partnerships and retains clients long-term. 2. Schedule face time: Vet your potential provider Request to see a provider’s operations in person to assess if the provider is financially secure, is equipped with resources and demonstrates a commitment to the success of their clients. Look for a partner that welcomes site visits and pay particular attention to the size of the customer service team. 3. Commitment counts: Co-fiduciaries are an important consideration Your reference-based pricing solution provider should be a partner that is 100% invested in your success. Look for a partner that is willing to sign on as a co-fiduciary because it may be asked to assist in managing the financial assets of your plan. 4. Knowledge is power: Employee education is paramount When you make a change to a benefits package, clear communication is important to ensure employees understand the new plan. Look for a partner that will educate, answer questions and serve as a continuing resource to your office for the duration of the partnership. 5. Relationships count: Employers and medical providers must work together Reference-based pricing is not a one-size-fits-all solution. Look for a partner that collaborates with health systems (especially solution providers with established partnerships), and demonstrates dedication toward fair provider reimbursement. See also: Innovation: ‘Where Do We Start?’   6. Measure the impact: Assess how your plan is working The partnership doesn’t stop after a plan is in place! Look for a partner that is results-driven and reports on your cost savings. A provider should also provide a dedicated support specialist and be a continuing, committed resource.

Recently, I did a Kiplinger interview about shopping for homeowners insurance focused, of course, on how to save money…as are virtually all consumer articles about insurance. I tried to make a point of how important it is to understand that you can’t compare prices in isolation. It is impossible to make a rational purchasing decision without considering what that price buys you in the form of coverage and exclusions. It would be like buying a car online based solely on the name of the manufacturer and a price. Then I got a link to an article by the Texas Department of Insurance that says: How to Shop Smart for Insurance 1.  Shop Around Yes, it’s that simple. Make sure to check prices for home and auto policies at least every three years. Insurers want your business, and you often get the best rates when you’re willing to switch companies. You can also get sample rates at www.HelpInsure.com. Sorry, but no, it’s NOT that simple. You would think a regulator charged with reviewing policy forms would know that. The advice does NOT help consumers “shop smart.” In fact, it makes it far more likely that they will choose poorly, thinking that price comparison is the only criterion for buying insurance. The first statement in this advice piece says, “We have a few tips to help you get the protection you need at the best price.” None of their tips necessarily get the consumer “the protection you need” because they don’t caution about the differences in protection provided within different quotes. I did a sample price quote at the link they provided and found premiums ranging from $250 to $2,500 for the same quote. There’s no way, for the factors used in the quote, that you could have that kind of premium differential. That tells me the quoting system is likely worthless and, worse, misleading and misrepresentative of the carriers’ programs. Who is being served by this kind of system? See also: Future of Insurance Looks Very Different   Recently, I made a blog post about the bad advice that permeates the internet and media on whether someone renting a car should buy the loss damage waiver (LDW), lamenting that much of the erroneous insurance advice comes from within the insurance industry itself in the form of advertising and well-intentioned information from insurance regulators and others. How can we expect mainstream media outlets to write accurately about the insurance industry when we don’t do it ourselves?

Consumer attitudes toward the insurance industry are changing faster than ever. Millennials make up the most populous generation today, and with many of them entering their mid- and late thirties, they are shopping for insurance in higher numbers. This tech-savvy generation expects personalized services and demands greater control over their experiences and decisions. Millennial consumers are calling the shots in almost every B2C industry – and insurance is no exception. The insurance industry traditionally relied on the fear of the unknown as its most powerful sales enabler, but with millennials making decisions based on brand experience, insurers need to turn to emerging technologies to transform and customize the way they reach customers. The status quo is simply unsustainable if they want growth. Forward-looking insurers know that the key to attracting and retaining clients is to leverage predictive technology and provide them with the seamless, smart, digital-first experience they need. But for this future to become a reality, companies need to implement and use predictive analytics in a way that truly enhances the customer experience. Here are the steps every insurer needs to know before embarking on that journey: Collect the Right – Not the Most – Data Knowing the ins and outs of customer needs and behaviors is essential in operating an insurance business, but it is not enough to know the general needs of a customer base. In fact, the majority of consumers are willing to share personal information in exchange for added benefits like enhanced risk protection, risk avoidance or bundled pricing. To deliver personalized service, insurers must collect data at the individual level – and quantity does not always mean quality. The accuracy of predictive analytics relies on the certainty and relevancy of the data those systems are fed. Before doing anything else, insurers must determine exactly what information drives business decisions and collect that data on both individual and grand scale as efficiently as possible. See also: 3 Ways to Optimize Predictive Analytics   This is where the Internet of Things (IoT) steps in. As one of the most ground-breaking technologies on the market today, IoT has only just begun to realize its potential in the insurance industry. IoT sensors attached to infrastructure, cars, homes and other insurable items, can feed real-time data back to providers with unprecedented accuracy. Not only does this live feed of data prevent emergencies by identifying potential problems before they arise, the highly precise information acts as a foundation for analytics at a customer-specific level in the next phase of the process. Get Personal With Predictions Once insurers are collecting relevant, accurate and individualized data, the next step on the road to customer satisfaction is applying machine learning and AI to that information. The outcomes of this analysis not only determine truths about the current status of an asset or situation but reveal patterns that enable insurance companies to predict what is in store down the road. For an insurer, this predictive knowledge means more accurately being able to evaluate, price and plan for risk – whether evaluating individual portfolios or aggregating data to foresee larger trends in the marketplace. But as predictive technology becomes more mainstream, the true value of digital foresight will be its ability to offer the millennial customers the deep personalization and hyper-relevance they crave and expect from all their services. By transforming the industry into a predictive and even preventative experience, insurance companies are changing the status quo of fear-based customer relationships and instead leverage technology to make insurance feel tailored and assuring. Engage With Emerging Technology The insurance industry is not and never will be based on static, one-time decisions. As risk is calculated on various constantly changing variables, it is essential to continue evolving customer predictions, recommendations and prices based on incoming information. Analyzing both existing and new data from IoT sensors allows companies to pivot strategies in the face of new predictions, enhance underwriting, reduce claim ratio and remain agile to meet the needs of their customers today and tomorrow. See also: What Comes After Predictive Analytics   Just as predictions do not stand still, neither should an insurance company’s methods for determining them. In an era of hyper customer relevance, with disruptive players like Uber, Venmo and Mint, millennials have come to expect services that are not only predictive but get deeply personalized in accuracy and usability overtime. The insurance industry has traditionally lagged behind other B2C industries in terms of adoption, however, due to its changing customer base it will have no other choice than to evolve rapidly over the next few years. Placing emerging technologies like AI, machine learning, automation and IoT at the core of business operations now will be key in setting insurance up for continued progression in the future. Appealing to the new generation of insurance customer is all about offering tailored experiences that cater to their needs and expectations. The insurance industry is in for an acceleration of change to accommodate their new millennial consumer – a change fueled by technology that creates bonds of loyalty and trust via personalization, not fear.

How a building is constructed and maintained and where it is located all have a massive impact on its potential to be damaged or destroyed. That knowledge is as old as insurance itself. So why do so many underwriters still suffer from lack of decent data about the buildings they insure? And when better data does get collected for U.S. properties, why does it seem to get lost as it crosses the Atlantic? London is an important marketplace for insuring U.S. risks. It provides over 10% of the capacity for specialty risks -- those that are hard, or impossible, to place in their home market through admitted carriers. Reinsurers of admitted carriers, insurers of homeowners and small businesses in the excess and surplus markets and facultative reinsurers of large corporate risks all need property data. The emergence and growth of a new type of property insurers in the U.S. such as Hippo and Swyfft has been driven by an expectation of having access to excellent data. They are geared up to perform fast analyses. They believe they can make accurate assessments and offer cheaper premiums. The level of funding for ambitious startups shows that investors are prepared to write large checks, tolerate years of losses and have the patience to wait in the expectation that their companies will displace less agile incumbents. If this works, it’s not just the traditional markets in the U.S. that will be under threat. The important backstop of the London market is also vulnerable. So what can established companies do to counter these new arrivals? Neither too hot nor too cold The challenge for any insurer is how to get the information it needs to accurately assess a risk, without scaring off the customer by asking too many questions. The new arrivals are bypassing the costly and often inaccurate approach of asking for data directly from their insureds, and instead are tapping into new sources of data. Some do this well, others less so. We’re already seeing this across many consumer applications. They lower the sales barrier by suggesting what you need, rather than asking you what you want. Netflix knows the films you like to watch, Amazon recommends the books you should read, and soon you’ll be told the insurance you need for your home. Health insurers such as Vitality are dramatically improving the relationship with their clients, and reducing loss costs, by rewarding people for sharing their exercise habits. Property insurers that make well-informed, granular decisions on how and what they are underwriting will grow their book of business and do so profitably. Those that do not will be undercharging for riskier business. Not a viable long-term strategy. Fixing the missing data problem would be a good place to start. We recently brought together 28 people from London Market insurers to talk about the challenges they have with getting decent quality data from their U.S. counterparts. We were joined by a handful of the leading companies providing data and platforms to the U.S. and U.K. markets. Before the meeting, we’d conducted a brief survey to check in on the trends. A number of themes emerged, but the two questions we kept coming back to were: 1) Why is the data that is turning up in London so poor, and 2) what can be done about it? This is not just a problem for London. If U.S. coverholders, carriers or brokers are unable to provide quality data to London, they will increasingly find their insurance and reinsurance getting more expensive, if they can get it at all. Regulators around the world are demanding higher standards of data collection. The shift toward insurers selling direct to consumer is gathering momentum. Those that are adding frictional costs and efficiencies will be squeezed out. This is not new. Rapid systemic changes have been happening since the start of the industrial revolution. In 1830, the first passenger rail service in the world opened between Liverpool and Manchester in the northwest of England. Within three months, over half of the 26 stagecoaches operating on that route had gone out of business. See also: Cognitive Computing: Taming Big Data   Is the data improving? Seventy percent of those surveyed believed that the data they are receiving from their U.S. partners has improved little, if at all, in the last five years. Yet the availability of information on properties had improved dramatically in the preceding 15 years. Why? Because of the widespread adoption of catastrophe models in that period. Models are created from large amounts of hazard and insurance loss data. Analyses of insured properties provide actionable insights and common views of risks beyond what can be achieved with conventional actuarial techniques. These analytics have become the currency of risk, shared across the market between insurers, brokers and reinsurers. The adoption of catastrophe models accelerated after Hurricane Andrew in 1992. Regulators and rating agencies demanded better ways to measure low-frequency, high-severity events. Insurers quickly realized that the models, and the reinsurers that used the models, penalized poor-quality data by charging higher prices. By the turn of the century, information on street address and construction type, two of the most significant determinants of a building’s vulnerability to wind and shake, was being provided for both residential and commercial properties being insured for catastrophic perils in the U.S. and Europe. With just two major model vendors, RMS and AIR Worldwide, the industry only had to deal with two formats. Exchanging data by email, FTP transfer or CD became the norm. Then little else changed for most of the 21st century. Information about a building’s fire resistance is still limited to surveys and then only for high-value buildings, usually buried deep in paper files. Valuation data on the cost of the rebuild, another major factor in determining the potential scale of loss and what is paid to the claimant, is at the discretion of the insured. It's often inaccurate and biased toward low values. If data and analytics are at the heart of insurtech, why does access to data appear to have stalled in the property market? How does the quality of data compare? We dug a bit deeper with our group to discover what types of problems they are seeing. In some locations, such as those close to the coast, information on construction has improved in the last decade, but elsewhere things are moving more slowly. Data formats for property are acceptable for standard, homogeneous property portfolios being reinsured because of the dominance of two catastrophe modeling companies. For non-admitted business entering the excess and surplus market, or high-value. complex locations there are still no widely adopted standards for insured properties coming into the London market, despite the efforts of industry bodies such as Acord. Data is still frequently re-keyed multiple times into different systems. Spreadsheets continue to be the preferred medium of exchange, and there is no consistency between coverholders. It is often more convenient for intermediaries to aggregate and simplify what may have once been detailed data as it moves between the multiple parties involved. At other times, agents simply don’t want to share their client’s information. Street addresses become zip codes, detailed construction descriptions default to simple descriptors such as "masonry." Such data chaos may be about to change. The huge inefficiency of multiple parties cleaning up and formatting the same data has been recognized for years. The London Market Group (LMG), a powerful, well-supported body representing Lloyd’s and the London company market has committed substantial funds to build a new Target Operating Model (TOM) for London. This year, the LMG commissioned London company Charles Taylor to provide a central service to standardize and centralize the cleaning up of the delegated authority data that moves across the market. Much of it is property data. Once the project is complete, around 60 Lloyd’s managing agents, 250 brokers and over 3,500 global coverholders are expected to finally have access to data in a standard format. This should eliminate the problem of multiple companies doing the same tasks to clean and re-enter data but still does nothing to fill in the gaps where critical information is missing. Valuation data is still the problem Information on property rebuilding cost that comes into London is considered “terrible” by 25% of those we spoke to and “poor quality” by 50%. Todd Rissel, the CEO of e2Value, was co-hosting our event. His company is the third-largest provider of valuation data in the U.S. Today, over 400 companies are using e2Value information to help their policy holders get accurate assessments of the replacement costs after a loss. Todd started the company 20 years ago, having begun his career as a building surveyor for Chubb. The lack of quality valuation data coming into London doesn’t surprise Todd. He’s proud of his company’s 98% success in accurately predicting rebuilding costs, but only a few states, such as California, impose standards on the valuation methods that are being used. Even where high-quality information is available, the motivation may not be there to use it. People choose their property insurance mostly on price. It’s not unknown for some insurers to recommend the lowest replacement value, not the most accurate, to reduce the premium, and the discrepancy gets worse over time. Have the losses of 2017 changed how data is being reported? Major catastrophes have a habit of exposing the properties where data is of poor quality or wrong. Companies insuring such properties tend to suffer disproportionately higher losses. No companies failed after the storms and wildfires of 2017, but more than one senior industry executive has felt the heat for unexpectedly high losses. Typically, after an event, the market "hardens" (rates get more expensive), and insurers and reinsurers are able to demand higher-quality data. 2017 saw the biggest insurance losses for a decade in the U.S. from storms and wildfire -- but rates haven't moved. Insurers and reinsurers have little influence in improving the data they receive. Over two-thirds of people felt that their coverholders, and in some cases insurers, don’t see the need to collect the necessary data. Even if they do understand the importance and value of the data, they are often unable to enter it into their underwriting systems and pipe it digitally direct to London. Straight-through processing, and the transfer of information from the agent’s desk to the underwriter in London with no manual intervention, is starting to happen, but only the largest or most enlightened coverholders are willing or able to integrate with the systems their carriers are using. We were joined at our event by Jake Hampton, CEO of Virtual MGA. Jake has been successful in hooking up a handful of companies in London with agents in the U.S. This is creating a far stronger and faster means to define underwriting rules, share data and assess key information such as valuation data. Users of Virtual MGA are able to review the e2Value data to get a second opinion on information submitted from the agent. If there is a discrepancy between the third party data that e2Value (or others) are providing and what their agent provides, the underwriter can either change the replacement value or accept what the agent has provided. A further benefit of the dynamic relationship between agent and underwriter is the removal of the pain of monthly reconciliation. Creating separate updated records of what has been written in the month, known as "bordereau," is no longer necessary. These can be automatically generated from the system. Even though e2Value is generating very high success rates for the accuracy of its valuation data, there are times when the underwriter may want to double-check the information with the original insured. In the past, this required a lengthy back and forth discussion over email between the agent and the insured. JMI Reports is one of the leading provider of surveys in the U.S. Tim McKendry, CEO of JMI, has partnered with e2Value to create an app that provides near-real-time answers to an underwriter’s questions. If there is a query, the homeowner can be contacted by the insurer directly and asked to photograph key details in his home to clarify construction details. This goes directly to the agent and underwriter enabling the accurate and fast assessment of rebuild value. What about insurtech? We’ve been hearing a lot in the last few years about how satellites and drones can improve the resolution of data that is available to insurers. But just how good is this data? If insurers in London are struggling to get data direct from their clients, can they, too, access independent sources of data directly? And does the price charged for this data reflect the value an insurer in London can get from it? Recent entrants, such as Cape Analytics, have also attracted significant amounts of funding. They are increasing the areas of the U.S. where they provide property information derived by satellite images. EagleView has been providing photographs taken from its own aircraft for almost 20 years. CEO Rishi Daga announced earlier this year that their photographs are now 16 times higher-resolution than the best previously available. If you want to know which of your clients has a Weber barbeque in the backyard, EagleView can tell you. Forbes McKenzie, from McKenzie Insurance Services, knows the London market well. He has been providing satellite data to Lloyd’s of London to assist in claims assessment for a couple of years. Forbes started his career in military intelligence. “The value of information is not just about how accurate it is, but how quickly it can get to the end user,” Forbes says. See also: How Insurtech Helps Build Trust   The challenges with data don’t just exist externally. For many insurance companies, the left hand of claims is often disconnected from the right hand of underwriting. Companies find it hard to reconcile the losses they have had with what they are being asked to insure. It’s the curse of inconsistent formats. Claims data lives in one system, underwriting data in another. It’s technically feasible to perform analyses to link the information through common factors such as the address of the location, but it’s rarely cost-effective or practical to do this across a whole book of business. One of the barriers for underwriters in London in accessing better data is that companies that supply the data, both new and old, don’t always understand how the London market works. Most underwriters are taking small shares of large volumes of individual properties. Each location is a tiny fraction of the total exposure and an even smaller fraction of the incoming premium. Buying data at a cost per location, similar to what a U.S. domestic insurer is doing, is not economically viable. Price must equal value Recently, the chief digital officer of a London syndicate traveled to InsureTech Connect in Las Vegas to meet the companies offering exposure data. He is running a POC against a set of standard criteria, looking for new ways to identify and price U.S. properties. He’s already seeing a wide range of approaches to charging. U.K.-based data providers, or U.S. vendors with local knowledge of how the information is being used, tend to be more accommodating to the needs of the London insurers. There is a large potential market for enhanced U.S. property data in London, but the cost needs to reflect the value. Todd Rissel may have started his career as a surveyor and now be running a long-established company, but he is not shy about working with the emerging companies and doesn’t see them as competition. He has partnerships with data providers such as drone company Betterview to complement and enhance the e2Value data. It is by creating distribution partnerships with some of the newest MGAs and insurers, including market leaders such as Slice and technology providers like Virtual MGA, that e2Value is able to deliver its valuation data to over a third of the companies writing U.S. business. Looking ahead It is widely recognized that the London market needs to find ways to meaningfully reduce the cost of doing business. The multiple organizations through which insurance passes, whether brokers, third-party administrators or others, increase the friction and hence cost. Nonetheless, once the risks do find their way to the underwriters, there is a strong desire to find a way to place the business. Short decision chains and a market traditionally characterized by underwriting innovation and entrepreneurial leaders means that London should continue to have a future as the market for specialty property insurance. It’s also a market that prefers to "buy" rather than "build." London insurers are often among the first to try new technology. The market welcomes partnerships. The coming generation of underwriters understands the value of data and analytics. The London market cannot, however, survive in a vacuum. Recent history has shown that those companies with a willingness to write property risks with poor data get hit by some nasty, occasionally fatal surprises after major losses. With the increasing focus by the regulator and Lloyd’s own requirements, casual approaches to risk management are no longer tolerated. Startups with large war chests from both U.S. and Asia see an opportunity to displace London. Despite the fears that data quality is not what it needs to be, our representatives from the London market are positive about the future. Many of them are looking for ways to create stronger links with coverholders in the U.S. Technology is recognized as the answer, and companies are willing to invest to support their partners and increase efficiency in the future. The awareness of new perils such as wildfire and the opening up of the market for flood insurance is creating opportunities. Our recent workshop was the first of what we expect to be more regular engagements between the underwriters and the providers of property information. If you are interested in learning more about how you can get involved, whether as an underwriter, MGA, provider data, broker or other interested party, let me know.

To be reminded of the power of insurance these days, I just have to step out the front door. I live about 80 miles south of the Camp Fire in northern California, and, even at this distance, the effect is obvious. The color of the air—not something I usually notice—sometimes reminds me of Mordor in the "Lord of the Rings" movies.

These fires, like every natural disaster, also serve as a reminder of how far we need to go as an industry, and not just to show people the value of insurance and narrow the "protection gap." We need to innovate to provide better, much cheaper policies that will be bought, not sold. We also need to find new business models, including ones based on helping people head off claims—if not from natural disasters, then at least from more controllable issues.

To that end, I encourage you to read a survey on innovation readiness that we did with The Institutes, which you can download for free here. The survey, led on our end by Guy Fraker and Paul Winston, shows that companies are making measurable progress but are still struggling, then provides a five-point checklist to overcome the common problems.

The Institutes will shortly unveil an insurance innovation curriculum, developed with Guy Fraker, that can help you build a culture of innovation and attack point #5 on that checklist: Encouraging employee participation. When the curriculum is ready for release, we will provide more details.

In the meantime, you might want to refer back to two detailed pieces from Guy that I've previously highlighted, on what's wrong and what's right with current innovation efforts. You can find them here and here.

As always, let me know if you have questions or if we can help.

In any case, let's all continue to hope and pray that the fires throughout California are contained as quickly as possible, with no more loss of life, and that all those affected can start to pull their lives together again as quickly as possible, assisted by the very best efforts of the insurance industry.

Have a safe week.

Paul Carroll
Editor-in-Chief