Heavy rains are forecast for Northern California this week, which may finally extinguish the vicious and deadly Camp Fire, but our friends in SoCal may not find relief just yet, and those caught up in the fire about 80 miles north of me still have to deal with unprecedented devastation. The latest grim numbers just from the NorCal fire: 77 confirmed dead, nearly 1,000 unaccounted for and almost 13,000 structures destroyed as 150,000 acres burned.

What to do?

Can we somehow mitigate these wildfires, or are we doomed to endure them?

There is plenty of reason for pessimism, a bit for optimism and a lot more for hope because of the intelligence that can be provided by the disciplines of risk management and insurance.

The pessimism comes because there's no end in sight for climate change. California, and other states and countries, will continue to dry out, providing more and more tinder for massive fires. Changing weather patterns may also mean that, as in California this year, rain comes too late in the season to damp the danger of fires and that the winds that arrive with winter can fan the flames to fatal degrees.

The optimism starts because we're learning about what causes massive fires. We're no longer trying to so hard to stop all fires, understanding that limited, localized fires can prevent out-of-control fires later. This doesn't mean raking the floor of California's 30 million acres of forest, as our president oddly suggested, but forest management can be done better, and it seems that it will be. 

The optimism continues because of the role that risk management and insurance can play. The recent California fires didn't occur somewhere in the deep, dark forest. They started in areas where civilization and forest converge, where people have chosen to build despite the possibility of wildfires. Better identification and pricing of those fire risks, updated for our understanding of the growing effects of climate change, will help homeowners see a more accurate cost of risk reflected in their insurance premiums and incent them to take steps to minimize the hazard or choose to live elsewhere. Better risk analysis will also help governmental authorities see where they need to improve evacuation plans and perhaps take other actions that would mitigate catastrophic losses.

Better risk management and higher premiums isn't a panacea. I've been to Paradise, the town that was engulfed in the Camp Fire, and it was such a lovely little place set in hills in the forest that it never would have lent itself to a mass, efficient evacuation. But we can do an awful lot better if we send the right economic signals, and that's something that risk management and insurance professionals are exactly the right people to send.

Have a great Thanksgiving—and please keep those affected by the fires in your thoughts and prayers.

Paul Carroll
Editor-in-Chief 

When Chloe steps out the door of her apartment on her way to work in the morning, her vehicle automatically unlocks its doors while the navigation system maps out the best route based on the latest weather and traffic conditions. Simultaneously, her home’s thermostat resets, and her security system arms. During her commute, Chloe decides to stop at a name-brand franchise for a cup of coffee. In a moment of weakness, Chloe – a diabetic – elects to consume a fresh-baked pastry along with her java. Fortunately, Chloe’s smart glucose monitoring system sends her an alert quantifying the size of the impending spike, and she responds appropriately to avert any issues. At her destination, Chloe’s car locks and arms when she walks away from it. As she makes her way indoors, Chloe’s workspace is simultaneously adjusting to her established lighting, temperature and activity levels. During the morning hours, Chloe elects to override two of the standing periods she’s selected for her daily routine. In the afternoon, Chloe’s home heating system detects a part is on the verge of failure. It generates a signal that triggers an automated process and orders the needed part, contacts a service provider and schedules the repair. Moments later, Chloe receives a notification of the impending breakdown as well as the day and time of the repair appointment, which she quickly confirms – via an app on her phone – and, using the same app, books a florist visit during the repair time frame to get some expert advice on an issue with her house plants. In the evening, as she arrives home from work, Chloe’s proximity disarms the household alarm and adjusts HVAC accordingly. After a healthful meal and her nightly yoga routine, Chloe sits down to finish reviewing several mortgage offers for the home she’s buying. Working on the mortgage causes Chloe to think about other ways to protect her family, so she clicks on a banner ad for a customized life insurance product. After staying up beyond her usual time, Chloe retires for the night. The Insurance IoT Imperative Today, most of us are familiar with basic forms of the electronic connectedness known as the Internet of Things (IoT). We obtain driving directions from our smartphone assistant, order pizza via smart speakers and control smart home devices with an app. But Chloe’s game-changing level of automated, integrated and connected IoT will arrive sooner than many people realize. As numerous consulting firms have discussed, businesses are becoming interdependent within and across categories. This will dissolve traditional industry boundaries and replace them with a set of distinctive and massive ecosystems clustered around fundamental human and business needs. In this article, we’ll review the current state of the Insurance IoT, explore what’s needed for future success and provide an executive-level overview of the technology considerations required for gaining favorable outcomes in a connected world. At the Starting Line Although IoT is most common among insurtechs, industry-wide efforts to harness insurance IoT are in their infancy. Many insurers are still focused on modernizing their core systems. Most are still struggling with defining what it means to transform into a “digital insurer” to meet escalating user experience expectations. As the accompanying overview graphic “Market Maturity” suggests, the majority of early insurance IoT initiatives have concentrated on one type of IoT, telematics, in personal and commercial auto lines. In the U.S., adoption is still minimal, with many initiatives having yet to realize a positive ROI. However, insurers have clearly grasped the larger potential as the traction and evaluation of new entrants, like Root, have captured the market’s attention and raised the sense of urgency. We’ve also seen some property insurance IoT efforts around residential and commercial structures. There, the focus has been assessing the impacts of mitigating various risks. By and large, even the most advanced initiatives are in the piloting or developmental phases, as insurers conduct research on sensor types, analytics tools, management systems, human interaction layers and adoption barriers. Progress among health insurers is similar to property. Early efforts range from offering fitness trackers to arming chronic obstructive pulmonary disease (COPD) inhalers with sensors for automatic tracking of medication use. Again, initiatives are in early phases, with real-world outcomes and profitability impacts yet unknown. See also: Insurance and the Internet of Things   Understanding the Real Value Proposition Moving forward, there’s little doubt the insurance industry will accelerate its embrace of insurance IoT. The true winners will be those who understand the real value proposition of insurance IoT, which are the opportunities for value creation and sharing that ultimately boost an insurer’s bottom line. To visualize how insurance IoT improves bottom lines, compared with traditional approaches, see the graphic portraying the respected “Insurance IoT Value Creation Framework.” This waterfall framework was created by the IoT Insurance Observatory, a think tank representing over 50 North American and European enterprises, including ValueMomentum. The Observatory also includes six of the top U.S. P&C insurance groups and four of the top seven global reinsurers. Let’s review some examples drawn from Chloe’s life, which illustrate the framework’s building blocks and how insurers benefit. First, Chloe’s renter’s insurance is a smart policy, offering more than monetary reimbursement when something bad has happened. Her insurer sold her a safety and security service for a monthly fee. Moreover, the insurer connected its systems to her smart home infrastructure and even added some water leakage sensors that were not previously present. The insurer created and manages the automated process that gets triggered by the signal from the heating system, enabling the insurer to intervene. Further, Chloe’s insurer receives revenue from its preferred service providers, like the repair technician and the florist, who pay the insurer a fee for automatic access to fulfilling Chloe’s needs. Although the policy Chloe selected permits her health insurer to raise her deductible for chronically engaging in risk-elevation activities, such as the contra-indicated pastries, reduced standing periods and sleep deprivation, Chloe chose this product because her transgressions are infrequent. As for the health insurer, it gains a self-selected, lower-risk policyholder. Chloe’s health insurer is also involved in her hyper-connected day, providing the glucose monitoring system together with an app that supplies Chloe with 24/7 access to a network of nutritionists. Chloe also receives a preferred rate for the monitoring and coaching, which reduces the insurer’s claims costs. Some of Chloe’s other activities also reduce risks and create value. These include automatically securing her home against intrusion and keeping indoor spaces the proper temperature to avoid infrastructure incidents and damage from frozen pipes, not to mention wearing her glucose monitoring system. Chloe’s insurers benefit from the reduced probability of Chloe submitting a claim. As for Chloe’s morning stop, she obtained her coffee for free by redeeming a QR code from her auto insurer sent as a reward for driving a certain number of miles at low risk (no hard braking, speeding, phone distractions, etc.). Previously, Chloe’s auto insurer had negotiated a very favorable rate on the coffee because the chain would benefit from cross- and up-sells, like Chloe’s impulse purchase. Chloe’s insurer reduces the risks to its book of business with this inexpensive behavior-change mechanism. In the evening, when working on her mortgage prompted Chloe to shop for life insurance, she opted in to permit the life insurer to obtain her health records, wellness activities from her mobile phone and the current contents of her refrigerator. In real time, the insurer calculated Chloe’s life score and created an exceptionally accurate quotation. Next, the insurer presented Chloe with a competitive quote based on her age, lifestyle and health history. Due to all of the positives, Chloe now loves her insurers. However, before her life was hyper-connected, she felt insurance was more of a necessary expense than a beneficial experience. Not only was her risk exposure greater, but she never received any rewards from her insurers. What’s more, Chloe’s insurance premiums were over 20% higher. By leveraging IoT data, Chloe’s insurers have created bottom-line value, a portion of which they share with her via discounted prices and other incentives. This value creation/value sharing model embodies insurance IoT’s transformational potential. What’s Required to Get There Once you’ve fully appreciated the business value embedded in the dozens of IoT data points your policyholders create every minute of every day, you can begin to acquire the appropriate technology capabilities for gathering, analyzing and acting on the IoT data in real time. Although this journey will involve numerous steps, a good starting point is understanding the seven primary technology layers required for insurance IoT and the key considerations for assembling them into a complete solution. For a visualization of these layers, consider the graphic “Insurance IoT Architecture” framed by the IoT Insurance Observatory. Technology Layer 1 - Sensors Devices that collect IoT data can range from simple, purpose-built solutions, such as a water flow detector, to complex devices that incorporate multiple types of sensors, like a smartphone. Although there’s no single “correct” type of sensor to use for any given application, it’s vital to consider both what data a given sensor is, or is not, gathering and how the sensor is collecting the data as each significantly affects analytics abilities and outcomes. Technology Layer 2 - IoT Data Collection and Data Sources Management Upon collection, data must be transferred for storage to a location where it, and other collected information, can be properly processed, managed and accounted for. In the early days of telematics, industry-specific solutions handled this layer. Now, as insurance IoT scales up to require data gathering from millions of policyholders, who are each generating thousands of different types of data points every nanosecond, this layer is quickly moving to mega-vendor platforms, like Microsoft Azure. Such platforms are purpose-built for fast transfer and management of vast amounts of information, plus they provide other services like device management, data security, resiliency, load balancing and ease of integration with other systems. All of these capabilities are vital to real-time insurance IoT. Technology Layer 3 - Insurance-Specific Data Analysis and Preparation From this layer forward, success depends on partnering with experienced solution providers that demonstrate a granular understanding of insurance nuances, ranging from rating requirements to loss specifics. Whether you’re developing a proprietary technology layer or adopting a purpose-built solution, partnering with experienced consultants and integrators is the most effective means to achieve your goals. Within Layer 3, collected data from all real-time, non-real time, internal and external sources gets normalized, interpreted and prepared for insurance-related purposes. A simple homeowners’ example is a combination of real-time data from smart sensors, both real-time and historical climate data from external providers and policyholder data such as contact information and preferences. The most advanced solutions for this layer now included advance algorithms and machine learning capabilities, speeding the normalization, interpretation and preparation chores. See also: Global Trend Map No. 7: Internet of Things   Technology Layer 4 - Advanced Insurance Analytics In this off-line layer, advanced analytics are performed on the data from the Layer 3 to create proprietary algorithms and models that are applied in subsequent two layers. A workers’ comp example is the probability of injury based on historical claims data combined with various external data sources. Or, in an automotive scenario, risk indicators that would predict a loss cost for a particular type of accident based on a particular type of vehicle on a specific type of roadway under a specific type of climatic conditions. Technology Layer 5 - Smart Insurance Actions Arguably, it’s within Layer 5, and its close cousin Layer 6, where the real-time “magic” of insurance IoT occurs. In other words, these layers translate the data and information from the forgoing layers into activities insurers can use for differentiating themselves and taking advantage of new opportunities to stay competitive. The technologies in both Layer 5 and Layer 6 can be made up of internal systems, cloud-based solutions or a hybrid. Specifically, Layer 5 rapidly applies algorithms and data from the previous layers to result in smart actions related to traditional insurance activities such as underwriting decisions, pricing calculations, claims management and cross-selling. Technology Layer 6 - Connected Insurance Ecosystems This layer can be thought of as a neighbor to Layer 5, rather than a vertical step up. This layer contains the partnering services and all of the connections required for the use of those services, as illustrated by Chloe’s story. However, the possibilities go far beyond those we’ve presented, making innovative thinking key to competitive success. Technology Layer 7 – User Experience Naturally, any successful insurance IoT deployment will involve integrating all of the forgoing back-end processes and systems with the front-end experience presented to policyholders and prospects. Such experiences should be designed as a mixture of digital and physical interactions, as insurance IoT is characterized by combining automated processes, triggered by data, with human engagement. Note that positive user experiences depend not only on the appropriateness of each interaction but also on appropriate timing. This ensures policyholders and prospects receive what they need and when they need it, rather than alienating users with distracting interactions that cause confusion or create interference. *** Regardless of which of the scenarios we’ve presented apply to your business, or where on the connectivity spectrum your enterprise is today, it’s clear the opportunities inherent in the insurance IoT offer vast possibilities for improving your bottom line and becoming beloved by your policyholders. Given the rapid paradigm shifts already underway, the greatest risk to insurers is delay. In short, the time to start building and executing your insurance IoT strategy is now. This article was first published on Carrier Management.

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.