While executives have come to understand that happy employees mean satisfied customers, they often miss the other side of the coin. Poor customer experience creates a toxic environment for employees. Are you trying to create a great customer experience in your organization? If you’re focusing on your customers to accomplish that, then you’re already missing half the story. That’s because the quality of a company’s customer experience is inextricably linked to the quality of its employee experience. Over the long term, you can’t deliver a great customer experience unless you have employees who are engaged, inspired and equipped to do so. For many people, this concept makes intuitive sense. After all, if you’re a customer, a good part of the experience you have with a business will be shaped by the staff with whom you interact. If employees are happy and engaged in their jobs, that sentiment will inevitably bleed into their interactions with customers. The staff will be more positive, more solicitous, more helpful—and customers will notice the difference. What’s often overlooked, however, is that the relationship between employee engagement and customer experience is bidirectional. Yes, engaged employees tend to deliver a better customer experience. But a better customer experience also tends to create more engaged employees. Here’s why. Imagine working in the call center of a business that has a horrible customer experience. Nearly every call you take is a complaint—a customer who’s frustrated, annoyed and lashing out because the company has failed to deliver on its promises. Every time that phone on your desk rings, you look at it with trepidation, knowing that, when you pick it up, you’ll likely be the target of another dissatisfied customer’s ire. See also: New Customer Decision Models   Do you think you’d like that job? Would it engage you, make you happy, propel you out of bed in the morning? Probably not. No matter how many cool perks might come with the assignment, there’s no getting around the day-to-day agony of having to repeatedly deal with angry, unhappy customers. It literally saps the engagement and energy from even the best-intentioned employees. Now imagine the other end of the spectrum, working for a company whose customers are consistently satisfied—if not impressed—with the products and services they receive from your firm. Sure, even an organization like that will have its share of customer experience failures that employees need to address. But those would be exceptions rather than the norm, making for a much healthier work environment. Instead of cringing every time the phone rings or a customer approaches, employees would be able to adopt a more positive and constructive stance. Instead of shrinking from customer interactions, they would lean into them with enthusiasm. Instead of focusing on defense, they would focus on delight. Executives often don’t fully grasp how toxic a poor customer experience can be to their employees (let alone their customers). Keep in mind, it’s usually not the employees who are principally at fault for a poor customer experience. Their best efforts are constrained by the systems, processes and workplace infrastructure in which they operate. Consider, for example, how much better a call center representative’s job is when the longest call waiting rarely exceeds a couple minutes. Or how much better a claim adjuster’s job is when policyholders aren’t surprised by “small print” coverage terms. Or how much better an agents' job are when they don’t have to spend hours helping customers decipher unintelligible premium and policy notices. These are just a few examples of common customer experience friction points whose negative influence can be felt not just among customers but employees, as well. It’s important to understand the bidirectional relationship between customer experience and employee engagement because it truly amplifies the value of customer experience excellence to any organization. The impact of experience enhancements, and the return on such investments, must be considered in a more holistic context. See also: Much Higher Bar for Customer Service   Yes, a better customer experience helps raise policyholder retention, increase cross-purchase rates and boost revenues, among other benefits. But it also improves employee engagement, which triggers a whole host of additional benefits, such as reduced staff turnover, lower absenteeism and higher productivity, just to name a few. It’s for this reason that the economic calculus around a great customer experience is far more compelling than many organizations recognize. Happy, engaged employees help create happy, loyal customers who, in turn, help create happy, engaged employees. The value of this virtuous cycle cannot be overstated, and it’s why the most successful companies appreciate—and act on—both sides of the equation. The original article was published here.

Artificial intelligence stands out as one of the hottest technologies in the insurance industry in 2018. We are seeing more insurers identifying use cases, partnering and investing in AI. 85% of insurers are investing time, money and effort into exploring the AI family of technologies. The focus is not so much on the technology itself as on the business challenges AI is addressing.

• For companies looking to improve internal efficiency, AI can assist through machine learning.
• For those working to create a dynamic and collaborative customer experience, AI can assist with natural language processing and chatbots.
• For those seeking an edge in data and analytics, AI can help to gain insights from images with the help of machine learning.

Through our annual SMA Innovation in Action Awards program, we hear many success stories from insurers throughout the industry that are innovating for advantage. AI was a key technology among this year’s submissions. The near-ubiquity of AI was even more obvious among this year’s insurer and solution provider winners, many of whom are leveraging some type of AI to solve widely variant business problems. They have provided some excellent use cases of how insurers are applying AI and how it is helping them to succeed. Two AI technologies, machine learning and natural language processing, fuel Hi Marley’s intelligent conversational platform, which West Bend Mutual Insurance piloted in claims with outstanding results. The Marley chatbot lets West Bend’s customers text back and forth to receive updates, ask and answer questions and submit photos. Its use of SMS messaging means that communication can be asynchronous and done on a customer’s own schedule, eliminating endless rounds of phone tag.

• Natural language processing allows Marley to communicate with customers in plain English – both to understand their needs and to respond in a way that they will understand.
• Machine learning enables Marley to continue to improve. The platform analyzes every conversation and uses it to shape how Marley responds to specific requests, refining its insurance-specific expertise for future interactions.

See also: Strategist’s Guide to Artificial Intelligence   Natural language processing is also a critical tool for Cake Insure, a digital workers’ comp MGA with a focus on making the quoting experience easier for direct customers. One of the hurdles that would-be customers had to overcome in obtaining workers’ comp coverage was answering a multitude of questions regarding very specific information that a layperson is unlikely to know about or understand.

• NAIC codes, for example, are required for every workers’ comp policy, but the average small business owner would be baffled if asked about them. Cake circumvents this by asking usera to type in descriptions of their companies in their own words. Natural language processing parses this plain-language description and searches for its approximate match in the NAIC data sets. This back-end process occurs without the user’s awareness and without exposing potentially confusing content.
• As with Hi Marley’s chatbot functionality, natural language processing is paired with machine learning to improve its ability to respond to specific phrases and content.

Machine learning can also be deployed in conjunction with other AI technologies. Image analysis and computer vision are combined with machine learning in Cape Analytics’ solution, which can automatically identify properties seen in geospatial imagery and extract property attributes relevant to insurers. The result is a continually updated database of property attributes like roof condition and geometry, building footprint and nearby hazards.

• Computer vision helps turn the unstructured data in photos and videos from drones, satellite and aerial imagery into structured data.
• Machine learning allows the solution to train itself on how to do that more effectively, as well as higher-level analysis like developing a risk condition score for roofs.

We are only scratching the surface of how AI can be applied across the value chain. The incredible variety of AI’s potential applications in insurance is difficult to overstate. QBE knows that well: It won a company-wide SMA Innovation in Action Award for wide-ranging activities in emerging technologies and partnerships with insurtech startups, but AI in general, and machine learning specifically, are their top priorities. In addition to partnering with dozens of insurtechs, QBE has also pushed itself to deploy each insurtech’s technology somewhere within its business – meaning QBE has dozens of different creative AI applications in play at once. For example, in partnership with HyperScience, QBE is improving data capture from paper documents through machine learning and computer vision. These winners’ stories demonstrate the myriad ways that insurers are applying AI to improve business operations. Notably, its deployment helps them to significantly improve the customer experience – or, in the case of data capture, the internal employee experience. The need for this kind of seamless customer experience in the digital world cannot be overemphasized. AI, which struck many as a science-fictional concept, has proven its real-world worth by enabling insurers to transform their customer journeys and experience. With full-scale implementations popping up across the insurance industry, as well as the pilots and limited rollouts that we have seen in previous years, it is easy to lose sight of the fact that we are seeing only the very tip of the iceberg in terms of how AI can transform the business of insurance. Applications of more advanced and advancing AI technologies, as well as the combination of AI with emerging technologies such as drones, new user interaction technologies, autonomous vehicles and IoT, are unexplored territory that is bright with promise. See also: 3 Steps to Demystify Artificial Intelligence   This much is clear: AI will change the face of the insurance industry. In fact, it’s already happening. For more information on the SMA Innovation in Action Awards program and this year’s winners, please click here. To download a free copy of SMA’s white paper AI in P&C Insurance: Pragmatic Approaches for Today, Promise for Tomorrow, please click here.

For anyone involved in vehicular transportation, it’s accepted that distracted driving is a deadly problem that needs continued attention. Earlier this year, the National Highway Traffic Safety Administration (NHTSA) published a detailed research report on Distracted Driving in 2016. According to the NHTSA’s statistics:

• Nine percent of fatal crashes in 2016 were reported as distraction-affected crashes
• In 2016, there were 3,450 people killed in motor vehicle crashes involving distracted drivers.
• Six percent of all drivers involved in fatal crashes were reported as distracted at the time of the crash.
• Nine percent of drivers 15 to 19 years old involved in fatal crashes were reported as distracted. This age group has the largest proportion of drivers who were distracted at the time of the fatal crashes.
• In 2016, there were 562 nonoccupants (pedestrians, bicyclists, and others) killed in distraction-affected crashes

Notice that teen drivers are the largest proportion of drivers who were distracted at the time of fatal crashes. However, a recent Arity survey shows that millennials are significantly less likely than the general population to say that “I never multi-task while driving” (48% vs 57%). What does this say about that demographic? With National Teen Driver Safety Week approaching at the end this month, it’s important to fuel this age range with the danger that distracted driving imposes on them. Here at Arity, we used our own data to compare the rate of smartphone penetration in the US, with distracted driving activity of telematics users and industry losses. Our research goes a step further to demonstrate that this problem is only getting worse. The percentage of losses attributed to distraction over the last several years has tripled, costing the industry an estimated $9 billion annually. See also: Distracted Driving — an Infographic   The insurance industry has taken a multi-pronged approach to reduce distracted driving. In addition to high-profile campaigns designed to raise general awareness of distracted driving, such as AT&T’s #ItCanWait initiative, distracted driving solutions have been developed by insurance providers, OEMs and shared mobility and telecommunications companies. As these solutions get closer to reality, there are a few core elements to consider. Here is a five-step process for the creation of a superior recipe for distracted driving detection:

1. Mobile Phone, No Substitutes: While embedded systems and OBD devices are the gold standard for assessing vehicular motion and risky driving patterns, today there is no substitute for the mobile phone in distracted driving detection. The mobile phone is the leading culprit fueling higher rates of distracted driving accidents. Pinpointing mobile phone movement and interaction is the most robust way to identify and prevent these risks.
2. One Part Movement, One Part Interaction: Phone movement only reveals part of the story. Distracted driving algorithms that rely solely on sensor information―accelerometer for translational motion, gyroscope for rotational motion, gravitometer for orientation, etc.―will be subject to false positives and false negatives. For instance, a motorcyclist with a phone safely in his pocket could be unfairly penalized each time he puts his foot down at a stop for balance.
3. Measure Each Ingredient Carefully: Not all forms of distracted driving are equally risky. Checking navigation while stopped at a traffic light is generally less risky than taking a selfie while speeding down the beltline during rush hour. To effectively assess relative risks, there are two fundamental considerations: context and mode. Context means, what were the conditions present at the time of the distracted driving behavior? At what speed was the car being driven; what was the weather like; was there traffic? Mode means, what distracted driving behaviors were taking place? Phone call; texting; navigation; gameplay; etc.
4. Monitor Continuously: Discrete or instantaneous markers only tell part of the story. For instance, counting only moments of large phone movement omits important information about the behaviors that took place interstitially. We can conceptualize distracted driving in terms of continuous sessions and endeavor to identify the starts and ends of these sessions. The total duration of distracted driving will provide the most predictive metrics for risk.
5. Modeling Bakeoff: Distracted driving models can be founded on logic and intuition, but they should be developed and validated with a data-driven approach. For the best solution to emerge, many alternatives should be assessed relative to their performance on labeled data sets―data sets composed of both telematics data as well as reliable labels for the periods of distracted driving. An example of this blended approach would be the Arity and Allstate research that estimated the cost of distracted driving for the insurance industry at $9 billion. This insight was derived from data sourced from national smart phone usage, vehicle telematics and incident claims data.

See also: Distracted Driving: a Job for Insurtech?   At Arity, our mission is to make transportation smarter, safer and more useful for everyone, and understanding and eliminating distracted driving is central to why the company was founded. What’s important is that we don’t see this solely as a technical problem. Aside from understanding the true behaviors that are causing insurance loss, we must also provide a meaningful experience to the driver to eliminate the behavior. It’s important that we don’t stop learning and experimenting; there’s so much more we can do to #enddistracteddriving.

At the InsureTech Connect conference, I witnessed several win-win-win scenarios. For example, one of my friends is doing some fantastic work with data models for the auto industry. One of my other friends is doing amazing work on providing back-end infrastructure (secure chain) for carriers and insurtech startups. All I did was make the introduction, and I witnessed something cool – true collaboration, as other introductions have occurred and produced a possible contract for one of my friends. In my startup journey, I’ve learned we are stronger together and that, the more wins we have, the better for all of us. Even if we are in different industries or verticals in the same industry, the more we collaborate and share, the better for everyone. Startups are interesting, and mentors and experts come in all shapes and experience – folks with deep knowledge/industry expertise and folks who have recent experience in the area they are wanting to disrupt. I’ve seen entrepreneurs chase mentors who have lots of experience. That is awesome! Don’t forget to build relationships with your peers and other startups. The recency of experience for startups is just as important. See also: Future of Insurance Looks Very Different   Let’s look at a couple of examples of creating win-win-win scenarios: Fundraising: Someone who has raised capital for their company 10 years ago is different than someone who is doing that now. Why? Strategies could have changed; players could have changed; and tactics could have changed. For startups wanting to raise capital, talk to your peers who recently raised money. You will get a lot of knowledge vs. a traditional spiel on how to raise money from someone who did it years ago. Collaborate and share! If there is a carrier VC group that may help your colleague, introduce them. If there is an accelerator or competition, share with your network. For insurtechs, insurance is HUGE! I keep joking within our founding team of Benekiva that I have a backlog of problems I want to solve. The only way to win is to collaborate and create win-win-win scenarios not just for you but also for your peers, even if you don’t see a win directly for you. Prospecting: Prospecting during startup stage takes a different lifecycle than for a traditional mature organization. If you come from sales, don’t get hung up on the “sales process and roles.” Be nimble. Involve your team – diversity and team matter. We've seen at Benekiva that, if we stick to traditional sales roles, the passion of the founding team doesn't come through. At ITC, I heard someone make a comment: “The best thing to do with knowledge is to share – not to hoard.” I encourage all my startup colleagues to continue collaborating and train your sixth sense on finding the right collaborative partners. Not everyone talks to you in the spirit of collaboration, but even when you get burned you get great experience and can build a great support system to vet opportunities. See also: Innovation: ‘Where Do We Start?’   Indra Nooyi, whom I've admired and who was the ultimate boss when I was fortunate enough to be working at Pepsico, said during a graduation address at Wake Forest University that it's crucial to help others rise. “Greatness comes not from a position," she said, "but from helping build the future.” Cheers to creating win-win-win scenarios!

Incumbent insurers face both challenges and opportunities from concurrent forces. Dramatically changing customer expectations and low investment returns threaten both property and casualty and life insurers. Declining participation rates and indifference from millennial consumers restrict growth in life companies. Technologies such as driverless cars and sensors (Internet of Things) promise to shrink revenue in P&C. To evolve their business and technology models, insurers are diversifying their approach to automation. Historically, in most insurance technology initiatives, the projects were fairly well-understood and had likely been implemented before. Policy, claims, and billing administration replacement efforts were typical of these automation investments. In contrast, emerging digital approaches are uncertain and require new service models, products and capabilities. The continued rise in insurance-related technology startup funding reflects the changes that are underway in insurance IT. Insurers need advanced skills in emerging technologies. Technology startups need industry and regulatory compliance knowledge. The result has been an increasing number of partnerships between insurers and startups that go beyond a supplier-buyer relationship. See also: Startups Take a Seat at the Table   However, there are significant barriers to success on both the insurer and the startup sides of this equation. Insurers must address risk-averse behaviors and increase decision speed. Startups need to scale (gain customers), understand the regulatory environment and navigate opaque insurance products. Left unmanaged, partnerships do not work as well as expected. The report titled Insurer-Startup Partnerships: Key Success Factors presents the feedback of 89 insurers and 78 insurance-focused startups from online surveys regarding best practices in partnership management. The major finding is that the two groups are generally aligned in terms of the importance of insurance innovation, but that there are key challenges related to initiative definition and accommodation of different cultural norms that must be addressed. It will take time to work out the best ways to accomplish this new partnership model, but the barriers faced by both sides will force each to adjust. An analysis of survey results indicates that success will be improved by recognizing the following:

• Cultural alignment and a shared vision are key.
• Startups perceive that they are being more disruptive than they actually are.
• Leaders of innovation initiatives must seek and implement bridging activities that join the two worlds.

See also: Engaging Employees: Key to Success   Success will come to those insurers and startups that can make the necessary adjustments to their own preferences, cultures and working models to create meaningful partnerships.

In 1997, a colleague and I sat in the office of Sears CEO Arthur Martinez and tried to convince him of two ideas. First, he needed to rethink his business because of the advent of e-commerce. Second, he had a major opportunity to position Sears as what today we would call the Airbnb for home repairs—just set up a sort of digital market that would act as a middleman between repair technicians and homeowners and renters, the vast majority of whom were Sears customers to some degree. Martinez demurred. He said Sears would thrive for the foreseeable future.

He was right if "foreseeable" meant five or six years, but Sears was already struggling when financier Eddie Lampert bought it in 2004, and, after a long, slow-motion train wreck,   Sears filed for bankruptcy protection  this week.

The Martinez story isn't just a what-might-have-been for Sears. It sheds light on what's happening in insurance, where the threats and opportunities at least rhyme with what Martinez faced in 1997. I'd draw three main lessons:

--Bill Gates is right. (He isn't always right, but he sure is right a lot.) As he said to me (and others) right around the time of the Martinez meeting, people tend to overestimate the effects of digital technology in the short run but underestimate the effects in the long run. The overestimation has happened in many ways with insurtech, such as in the belief years ago that Amazon or some other big tech would soon move into insurance and take over. But we can't let any complacency seep in. Just because some big tech hasn't eaten our lunch by now doesn't mean it won't, or that some other threat won't emerge. Sears didn't lose to some startup in 1998, but it still lost. The forces of transformation have been unleashed in insurance, and they won't stop. We all have to be careful to not underestimate their long-term effects.

--Many executive teams and boards have personal timing that is out of sync with the pace of change in the industry. They know they need to set up their businesses for the future, but they also can feel in their bones that they might make it safely to retirement before the really disruptive changes come. Why launch major initiatives now, with all the complication that will be introduced and with all the money that will need to be invested (and diverted from the bonus pool)? I'm not saying that anyone deliberately starves the future, just that it's hard not to make personal calculations. Martinez retired in 2000 and is listed on his Wikipedia page as "the person who saved Sears," mostly because he increased sales among women through a campaign about "the lighter side of Sears." I'd recommend that boards and CEOs have explicit discussions about timing issues and that all have a significant part of their compensation tied to how their businesses look a decade from now. 

--You can't always tell where the threat or opportunity will emerge—yet you'd better get it right. As Chunka Mui and I wrote in "Billion Dollar Lessons" 10 years ago, Sears set itself up for failure in the early 1980s when it bought Coldwell Banker and Dean Witter based on an odd theory sometimes referred to as "socks and stocks." The idea was that people would go to Sears stores and buy some inexpensive clothing, then want to make an investment. They'd buy their financial tools along with their power tools. Coldwell Banker and Dean Witter weren't disasters as investments, but their integration into Sears took a huge amount of management time and distracted the company from the real issue: Walmart. While Sears focused on dreams of synergy, Walmart staked out a lead in hyperefficient, low-cost retailing that it never relinquished. Once e-commerce kicked in, then Lampert made a series of decisions driven by financial engineering rather than long-term strategy, well, we saw the results this week. As it happens, the bankruptcy filing comes just as Sears' e-commerce nemesis, Amazon, is expanding in physical stores, including   opening of a cashierless store in Sears' longtime hometown of Chicago and as Amazon's market value has flirted with $1 trillion.

There are ways to test the market with innovations to see where those threats and opportunities are, but that's a longer story for another day. In the meantime, let us know if we can help.

Have a great week. 

Paul Carroll
Editor-in-Chief

It is of course much easier to look back and second-guess regulatory actions. It is far more difficult to propose a way forward and to do so in light of the emerging hot-button issues, including data and the digitization of the industry, insurtech (and regtech), emerging and growing risks, cyber, the Internet of Things (IoT), natural catastrophes, longevity and growing protectionism. The way forward requires consideration of the primary goals of insurance regulation and raises critical questions regarding how regulators prioritize their work and how they interact with one another, with the global industry and with consumers. We offer below some thoughts and suggestions on these important questions and on how regulation might best move forward over the next 10 years. Establish a reasonable construct for regulatory relationships. Relationships matter, and it is imperative for there to be careful consideration of how regulators organize their interactions and reliance on each other. We have some examples in the form of the Solvency II equivalence assessment process, the NAIC’s Qualified Jurisdiction assessment process (under the U.S. credit for reinsurance laws), the NAIC’s accreditation process for the states of the U.S., the U.S.-E.U. Covered Agreement, ComFrame, the IAIS and NAIC’s memorandum of ynderstanding and the IMF financial sector assessment program (FSAP). Each of these provide varying degrees of assessment and regulatory cooperation/reliance. These processes and protocols, however, have largely emerged on an ad hoc, unilateral basis and in some cases have had a whiff of imperial judgment about them that may not be justified – and certainly is off-putting to counterparties. We would urge regulators to give careful consideration to the goals, guiding principles and the process for achieving greater levels of cooperation and reliance among global regulators. We hope these efforts would include an appreciation that different approaches/systems can achieve similar results that no jurisdiction has a monopoly on good solvency regulation. There must also be respect for and recognition of local laws and a recognition that regulatory cooperation and accommodation will benefit regulators, the industry and consumers. Most importantly, regulators need to work together to develop confidence and trust in one another. The IAIS first coined the phrase “supervisory recognition” in 2009. In March of that year, the IAIS released an “issues paper on group-wide solvency assessment and supervision.” That paper stated that: “To the extent there is not convergence of supervisory standards and practices, supervisors can pursue processes of ‘supervisory recognition’ in an effort to enhance the effectiveness and efficiency of supervision. Supervisory recognition refers to supervisors choosing to recognize and rely on the work of other supervisors, based on an assessment of the counterpart jurisdiction’s regulatory regime.” See also: Global Trend Map No. 14: Regulation   The paper noted the tremendous benefits that can flow from choosing such a path: “An effective system of supervisory recognition could reduce duplication of effort by the supervisors involved, thereby reducing compliance costs for the insurance industry and enhancing market efficiency. It would also facilitate information sharing and cooperation among those supervisors.” This is powerful. We urge global insurance regulators to take a step back and consider how they can enhance regulatory effectiveness and efficiency by taking reasonable and prudential steps to recognize effective regulatory regimens − even where these systems are based on different (perhaps significantly different) rules and principles, but which have a demonstrated track record of effectiveness. As noted above, we have seen some efforts at supervisory recognition. These include Solvency II’s equivalence assessment process, the NAIC’s accreditation process for other U.S. states, the NAIC “Qualified Jurisdictions” provisions for identifying jurisdictions that U.S. regulators will rely on for purposes of lowering collateral requirements on foreign reinsurers, the E.U.-U.S. Covered Agreement and the IAIS’s Memorandum on Mutual Understanding. Some of these processes are more prescriptive than others and have the danger of demanding that regulatory standards be virtually identical to be recognized. This should be avoided. One size for all is not the way to go. The alternative approach to recognition of different, but equally effective systems is the pursuit of a harmonized, single set of regulatory standards for global insurers. This approach is much in vogue among some regulators, who assert the “need for a common language” or for “a level playing field” or to avoid “regulatory arbitrage.” Some regulators also argue that common standards will lead to regulatory nirvana, where one set of rules will apply to all global insurers, which will then be able to trade seamlessly throughout all markets. There are, however, a variety of solvency and capital systems that have proven their effectiveness. These systems are not identical, and indeed they have some profoundly different regulatory structures, accounting rules and other standards such as the systems deployed in the E.U. (even pre-Solvency II), the U.S., Canada, Japan, Bermuda, Australia, Switzerland and others. Attempting to assert a signal system or standard ignores commercial, regulatory, legal, cultural and political realities. Moreover, we question some of the rationale for pursuing uniform standards, including the need for a common language. We suggest that what is really needed is for regulators to continue to work together, to discuss their respective regulatory regimes and to develop a deep, sophisticated knowledge of how their regimes work. From this, trust will develop, and from that a more effective and efficient system of regulation is possible. The engagement and trust building can happen within supervisory colleges. We have seen it emerge in the context of the E.U.-U.S. regulatory dialogue. We saw it in the context of the E.U.-U.S. Covered Agreement. No one, however, has made a compelling case for why one regulatory language is necessary to establish a close, effective working relationship among regulators. Similarly, the call for a level playing field sounds good, but it is an amorphous, ambiguous term that is rarely, if ever, defined. Does the “playing field” include just regulatory capital requirements? If so, how about tax, employment rules, social charges? How about 50 subnational regulators versus one national regulator? Guarantee funds? Seeking a level playing field can also be code for, “My system of regulation is heavier, more expensive than yours, so I need to put a regulatory thumb on the scales to make sure you have equally burdensome regulations.” This argument was made for decades in the debate surrounding the U.S. reinsurance collateral rules. We hear it now regarding the burdens of Solvency II. It must be asked, however, whether it is the responsibility of prudential regulators to be leveling playing fields, or should their focus be solely on prudent regulatory standards for their markets. Finally, the dark specter of regulatory arbitrage is often asserted as a reason to pursue a single regulatory standard, such as the development of the ICS by the IAIS. But one must ask if there is really a danger of regulatory arbitrage today among global, internationally active insures? Yes, a vigilant eye needs to kept for a weak link in the regulatory system, something the IMF FSAP system has sought to do, supervisory colleges can do and the IAIS is well-equipped to do. But using regulatory arbitrage as an argument to drive the establishment of the same standards for all insurers does not seem compelling. Proportionality is required. Often, regulators roll out new regulatory initiatives with the phrase that the new rules will be “proportionate” to the targeted insurers. Too often, it seems there is just lip service to this principle. Rarely is it defined – but it is tossed out in an attempt to say, “Do not worry, the new rules will not be excessive.” Greater debate and greater commitment to this principle is needed. Clearly a key component of it must be a careful cost/benefit analysis of any proposed new standard, with a clear articulation of the perceived danger to be addressed – including the likelihoods and severity of impact and then a credible calculation of the attendant costs – economic and otherwise to industry and to regulators. In October 2017, the U.K. Treasury Select Committee published a report criticizing the PRA for its excessively strict interpretation of Solvency II and its negative effect on the competitiveness of U.K. insurers. The report concluded that the PRA had enhanced policyholder protection at the expense of increasing the cost of capital for U.K. insurers, which hurt their ability to provide long-term investments and annuities. Although the PRA emphasized its mandate of prudential regulation and policy holder protection, the Treasury Committee reiterated its concern with how the PRA interpreted the principle of proportionality. Simplicity rather than complexity. Over the past 10 years, there has been a staggering increase in proposed and enacted regulatory requirements, many of which are catalogued above. There is a danger, however, that increasingly complex regulatory tools can create their own regulatory blind spots and that overly complex regulations can create a regulatory “fog of war.” Andrew Haldane, executive director at the Bank of England, in August 2012 delivered a paper at a Federal Reserve Bank of Kansas City’s economic policy symposium, titled “The Dog and the Frisbee.” He graphically laid out when less is really more by talking about two ways of catching a Frisbee: One can “weigh a complex array of physical and atmospheric factors, among them wind speed and Frisbee rotation” − or one can simply catch the Frisbee, the way a dog does. Complex rules, Haldane said, may cause people to manage to the rules for fear of falling in conflict with them. The complexity of the rules may induce people to act defensively and focus on the small print at the expense of the bigger picture. Focusing on the complexity of the banking world, Haldane compared the 20 pages of the Glass-Steagall Act to the 848 pages of Dodd-Frank together with its 30,000 pages of rulemaking, and compared the 18 pages of Basel 1 to the more than 1,000 pages of Basel III. The fundamental question is whether that additional detail and complexity really adds greater safety to the financial system or has just the opposite effect and significantly increases the cost. Haldane’s analysis provides compelling evidence that increasing the complexity of financial regulation is a recipe for continuing crisis. Accordingly, Haldane calls for a different direction for supervisors with “…fewer (perhaps far fewer), and more (ideally much more) experienced supervisors, operating to a smaller, less detailed rule book.” Although Haldane’s analysis and discussion focuses on the banking system, his assessment and recommendations should be considered carefully by global insurance regulators. The sheer volume and complexity of rules, models and reports that flood into regulatory bodies raise the real question of who reviews this information, who really understands it and, worst of all, does a mountain of detailed information create a false confidence that regulators have good visibility into the risks – particular the emerging risks – that insurers are facing? A real danger exists of not seeing the forest for the trees. See also: To Predict the Future, Try Creating It   Regulation should promote competitiveness rather than protectionism. At a time when competition has been growing not only from within the established companies but also more importantly from outside the traditional companies, protectionism will only inhibit growth and stifle better understanding of risk in a rapidly changing business environment. The goal must be to make the industry more competitive and to encourage transfer of innovation and create better ways to address risk, distribution of products and climate changes. Protectionism will only limit the potential of growth of the industry and is both short-sighted and self-defeating. Recognition of the importance of positive disruption through insurtech, fintech and innovation. The consensus is that the insurance industry is ripe for disruption because it has been slow (but is now working hard) to modernize in view of an array of innovative and technological advancements. Equally, regulators are trying to catch up with the rapid changes and are trying to understand the impacts through sandbox experiments and running separate regulatory models. The pace is fast and presents challenges for the regulators. Solvency and policyholder protection remain paramount, but cybersecurity, data protection, artificial intelligence and the digital revolution make advancements every day. Where this will lead is not clear. But changes are happening and regulators must work to understand the impact and need to calibrate regulatory rules to keep up with the industry and encourage innovation. Regulation must be transparent. Too often, regulation is drafted in times of crisis or behind closed doors by regulators believing they know better how to protect policy holders and how to prevent abuse of the system. As we have said, getting it right matters. A strong and healthy industry is the best way to protect consumers and policy holders. Industry engagement is essential and acknowledging and actually incorporating industry’s views is critical. This is particularly true given the dramatic changes in the insurance sector and the need to adopt regulation to new economics, business practices and consumer needs and expectations This is an excerpt from a report, the full text of which is available here.

“Somehow we have created a monster, and it's time to turn it on its head for our customers and think about providing some certainty of protection." - Inga Beale, CEO, Lloyds of London In an early-morning plenary session at this year’s InsureTech Connect in Las Vegas, Rick Chavez, partner and head of digital strategy acceleration at Oliver Wyman, described the disruption landscape in insurance succinctly: while the first phase of disruption was about digitization, the next phase will be about people. In his words, “digitization has shifted the balance of power to people,” forcing the insurance industry to radically reorient itself away from solving its own problems toward solving the problems of its customer. It’s about time. For the 6,000-plus attendees at InsureTech Connect 2018, disruption in insurance has long been described in terms of technology. Chavez rightly urged the audience to expand its definition of disruption and instead conceive of disruption not just as a shift in technology but as a “collision of megatrends”–technological, behavioral and societal–that is reordering the world in which we live, work and operate as businesses. In this new world order, businesses and whole industries are being refashioned in ways that look entirely unfamiliar, insurance included. This kind of disruption requires that insurance undergo far more than modernization, but a true metamorphosis, not simply shedding its skin of bureaucracy, paper applications and legacy systems but being reborn as an entirely new animal, focused on customers and digitally enabled by continuing technological transformation. In the new age of disruption … 1. Insurance is data “Soon each one of us will be generating millions of data sets every day - insurance can be the biggest beneficiary of that” - Vishal Gondal, GOQUii While Amazon disrupted the way we shop, and Netflix disrupted the way we watch movies, at the end of the day (as Andy G. Simpson pointed out in his Insurance Journal recap of the conference) movies are still movies, and the dish soap, vinyl records and dog food we buy maintain their inherent properties, whether we buy them on Amazon or elsewhere. Insurance, not simply as an industry but as a product, on the other hand is being fundamentally altered by big data. At its core, “insurance is about using statistics to price risk, which is why data, properly collected and used, can transform the core of the product,” said Daniel Schreiber, CEO of Lemonade, during his plenary session on day 2 of the conference. As copious amounts of data about each and every one of us become ever more available, insurance at the product level– at the dish soap/dog food level–is changing. While the auto insurance industry has been ahead of the curve in its use of IoT-generated data to underwrite auto policies, some of the most exciting change happening today is in life insurance, as life products are being reconceived by a boon of health data generated by FitBits, genetic testing data, epigenetics, health gamification and other fitness apps. In a panel discussion titled "On the Bleeding Edge: At the Intersection of Life & Health," JJ Carroll of Swiss RE discussed the imperative of figuring out how to integrate new data sources into underwriting and how doing so will lead to a paradigm shift in how life insurance is bought and sold. “Right now, we underwrite at a single point in time and treat everyone equally going forward,” she explained. With new data sources influencing underwriting, life insurance has the potential to become a dynamic product that uses health and behavior data to adjust premiums over time, personalize products and service offerings and expand coverage to traditionally riskier populations. Vishal Gandal of GOQuii, a “personalized wellness engine” that is partnering with Max Bupa Insurance and Swiss Re to offer health coaching and health-management tools to customers, believes that integrating data like that generated by GOQuii will “open up new risk pools and provide products to people who couldn’t be covered before.” While some express concern that access to more data, especially epigenetic and genetic data, may exclude people from coverage, Carroll remains confident that it is not insurers who will benefit the most from data sharing, but customers themselves. See also: Is Insurance Really Ripe for Disruption?   2. Insurance is in the background “In the future, insurance will buy itself automatically” - Jay Bergman Some of the most standout sessions of this year’s InsureTech Connect were not from insurance companies at all, but from businesses either partnering with insurance companies or using insurance-related data to educate their customers about or sell insurance to their customers as a means of delivering more value. Before unveiling a new car insurance portal that allows customers to monitor their car-related records and access a quote with little to no data entry, Credit Karma CEO Ken Lin began his talk with a conversation around how Credit Karma is “more than just free credit scores,” elucidating all of the additional services they have layered on top of their core product to deliver more value to their customers. Beyond simply announcing a product launch, Lin’s talk was gospel to insurance carriers, demonstrating how a company with a fairly basic core offering (free credit scores) can build a service layer on top to deepen engagement with customers. It’s a concept that touches on what was surely one of the most profound themes of the conference–that, like free credit scores, insurance only need be a small piece of a company’s larger offering. This may mean embedding insurance into the purchase of other products or services (i.e., how travel insurance is often sold) or it may mean doing what Credit Karma has done and layering on a service offering to deepen engagement with customers and make products stickier. Assaf Wand, CEO of the home insurance company Hippo, spoke to both of these models in his discussion with David Weschler of Comcast about how their two companies are partnering to make insurance smarter and smart homes safer. When asked about what the future of insurance looks like, Wand put it plainly when he said: “Home insurance won’t be sold as insurance. It will be an embedded feature of the smart home.” Jillian Slyfield, who heads the digital economy practice at Aon, a company that is already partnering with companies like Uber and Clutch to insure the next generation of drivers, agrees: “We are embedding insurance into these products today.” Until this vision is fully realized, companies like Hippo are doing their part to make their insurance products fade into the background as the companies offer additional services for homeowners, “Can I bring you value that you really care about?” Wand asked, “Wintering your home, raking leaves, these are the kinds of things that matter to homeowners.” 3. Insurance is first and foremost a customer experience “The insurance industry has to redefine our processes… go in reverse, starting with the customer and re-streamlining our processes around them” - Koichi Nagasaki, Sompo To many outside the insurance industry, the idea of good customer experience may seem unremarkable, but for an industry that has for so long been enamored by the ever-increasing complexity of its own products, redefining processes around customers is like learning a foreign language as a middle-aged adult. It’s hard, and it takes a long time, and a lot of people aren’t up to the task. The insurance industry has been talking about the need for customer-centricity for a while now, but many companies continue to drag their feet. But customer-centricity is and remains more than a differentiator. It’s now table stakes. How this plays out for the industry will look different for different companies. Some will turn to partnerships with insurtechs and other startups to embed their products into what are already customer-centric experiences and companies. Chavez of Oliver Wyman would rather see the industry “disrupt itself,” as he believes it’s critical that companies maintain the customer relationship. In his plenary sessions, he cited the German energy company Enercity as a company that disrupted itself. Operating in a similarly regulated industry, rather than becoming just a supplier of energy, the company invested heavily in its own digital strategy to become a thought leader in the energy space, to be a trusted adviser to its customer and to deliver an exceptional digital experience that, among other things, leverages blockchain technology to accept bitcoin payments from customers. For Chavez, insurtech is already a bubble, and, “If you want to succeed and thrive in a bubble, make yourself indispensable.” The only way to do this, he believes, is to maintain ownership over the customer experience, because, in today’s digital economy, the customer experience is the product. But to own the customer experience and succeed will require insurance companies to completely reorient their business practices and processes - to start with the customer and the experience and work backward toward capabilities. In the words of Han Wang of Paladin Cyber, who spoke on a panel about moving from selling products to selling services, “It’s always a questions of what does the customer want? How do they define the problem? And what is the solution?” 4. Insurance is trust “The world runs on trust. When we live in a society where we have lots of trust, everyone benefits. When this trust goes away, everyone loses.” - Dan Ariely, Lemonade During a faceoff between incumbents and insurtechs during one conference session, Dylan Bourguignon, CEO of so-sure cinched the debate with a single comment, calling out large insurance carriers: “You want to engage with customers, yet you don’t have their trust. And it’s not like you haven’t had time to earn it.” This, Bourguignon believes, is ultimately why insurtechs will beat the incumbents. Indeed, the insurtech Lemonade spent a fair amount of stage time preaching the gospel of trust. Dan Ariely, behavioral economist and chief behavior officer at Lemonade, delivered a plenary session entirely devoted to the topic of trust. He spoke about trust from a behavioral standpoint, explaining how trust creates equilibrium in society and how, when trust is violated, the equilibrium is thrown off. Case in point: insurance. Insurance, he explained, has violated consumer trust and has thrown off the equilibrium–the industry doesn’t trust consumers, and consumers don’t trust the industry, a vulnerability that has left the insurance industry open to the kind of disruption a company like Lemonade poses. As an industry, insurance has incentives not to do the thing it has promised to do, which is to pay out your claims. And while trust is scarcely more important in any industry as it is in insurance, save in an industry like healthcare, the insurance industry is notoriously plagued by two-way distrust. What makes Lemonade stand out is that it has devised a system that removes the conflict of interest germane to most insurance companies – as a company, it has no incentives to not pay out customer claims. In theory, profits are entirely derived by taking a percentage of the premium; anything left over that does not go to pay out a claim is then donated to charity. The result: If customers are cheating, they aren’t cheating a company, they are cheating a charity. Ariely described several instances where customer even tried to return their claims payments after finding misplaced items they thought had been stolen. “How often does this happen in your companies?” he asked the audience. Silence. And it’s not just new business models that will remedy the trust issues plaguing insurance. It’s new technology, too. In a panel titled "Blockchain: Building Trust in Insurance," executives from IBM, Salesforce, Marsh and AAIS discussed how blockchain technology has the capacity to deepen trust across the industry, among customers, carriers, solutions providers and underwriters by providing what Jeff To of Salesforce calls an “immutable source of truth that is trusted among all parties.” Being able to easily access and trust data will have a trickle down effect that will affect everyone, including customers, employees and the larger business as a whole–reducing inefficiencies, increasing application and quote-to-bind speed, eliminating all the hours and money that go into data reconciliation and ultimately making it easier for carriers to deliver a quality customer experience to their customers. See also: Disruption of Rate-Modeling Process   While the progress in blockchain has been incremental, the conference panel demoed some promising use cases in which blockchain is already delivering results for customers, one example being acquiring proof of insurance for small businesses or contractors through Marsh’s platform. With blockchain, a process that used to span several days has been reduced to less than a minute. Experiences like these–simple, seamless and instantaneous – are laying the groundwork for carriers to begin the long road to earning back customer trust. Blockchain will likely play an integral role this process. 5. Insurance is a social good “We need insurance. It is one of the most important products for financial security.” - Dan Ariely, Lemonade For all of the the naysaying regarding state of the industry that took place at InsureTech Connect, there were plenty of opportunities for the industry to remind itself that it's not all bad, and its core insurance is something that is incredibly important to the stability of people across the globe. Lemonade’s Schreiber called it a social good, while Ariely told his audience, “We need insurance. It is one of the most important products for financial security.” Similar sentiments were expressed across stages throughout the conference. In fact, in today’s society, income disparity is at one of the highest points in recent history, stagnating wages are plaguing and diminishing the middle class, more people in the U.S. are living in poverty now than at any point since the Great Depression, the social safety net is shrinking by the minute and more than 40% of Americans don’t have enough money in savings to cover a $400 emergency, so insurance is more important than ever. For Inga Beale, CEO of Lloyds of London, insurance has a critical role to play in society, “It goes beyond insurance–it’s about giving people money and financial independence,” she said during a fireside chat. She went on to describe findings from recent research conducted by Lloyds, which determined that, by the end of their lives, men in the U.K. are six times better off financially than women. When designed as a tool to provide financial independence and equality for everyone, insurance can play an important role in addressing this disparity. While this has been a focus in emerging markets, financial stability and independence is often assumed in more developed markets, like the U.S. and Europe. In reality, it is a problem facing all markets, and increasingly so. Ace Callwood, CEO of Painless1099, a bank account for freelancers that helps them save money for taxes, agrees that insurance has an important role to play. “It’s our job to get people to a place where they can afford to buy the products we are trying to sell,” he said. You can find the article originally published here.

Automation is transforming claims processing in myriad ways. Damage appraisals that are completed in only a few hours are becoming the norm―shaving days off cycle time and making the claims process easier than ever before. Insurance customers are getting comfortable with snapping a few photos of their damaged vehicle and sending them to their insurer via a simple mobile claim app. Drones are often dispatched to inspect storm damage on a home, allowing property adjusters to complete virtual damage inspections. Data delivered electronically early in the claims process is revolutionizing the claims workflow, simplifying claim reporting and providing a wealth of actionable data to expedite claim settlements. What do customers think about the advent of claims automation? How can insurers leverage today’s technology and real time data to wow their customers? These are just a sample of the questions we wanted to answer with our Future of Claims panel of experts at the LexisNexis Customer Advisory Meeting on Sept. 11, 2018, in Scottsdale, AZ. This session, which I moderated, included experts Dave Pieffer (P&C practice lead with J. D. Power & Associates), Jimmy Spears (AVP auto experience with USAA) and Lily Wray (VP emerging technology operationalization with Liberty Mutual). See also: 3 Techs to Personalize Claims Processing   Data from the 2018 J. D. Power Claims Customer Service Survey, presented by Dave Pieffer, informed our discussion around the following four themes (with the customer perspective for the themes shown in quotes):

• Show Empathy―“Listen to Me”
• Streamline Customer Communications―“Simplify for Me”
• Improve Service Speed―“Prioritize Me”
• Optimize and Balance Self-Service Options―“Empower Me”

Show Empathy The survey found that showing empathy (“Listen to Me”) ―expressed as “ensuring the customer feels more at ease”―scores low, with an industry average of 66%. Pieffer shared that the only empathy category scoring lower was “taking the loss report in 15 minutes or less”―with an average of 59%. The panel explained the importance of listening to customers as a first priority and improving FNOL scripts to be more natural and conversational versus impersonal (such as simply providing a list of questions). Jimmy Spears emphasized the importance of adopting a user-friendly self-service claims reporting process. He introduced the term “digital hug”―an immediate digital response to a customer’s electronic claim report or message. Spears shared that often customers who report electronically will immediately also call to ask, “Did you get my report?” Providing a digital hug gives customers the assurance that they have been heard and action is underway. The panel audience participated in the session by answering real time electronic polling questions from their phones, and in this case responded that simplifying the FNOL process with fewer questions was the most important way to increase customer empathy. Streamline Customer Communications On the topic of streamlining customer communications (“Simplify for Me”), Spears explained that “pro-active communication is the key to success.” Pieffer shared statistics showing that customers are most satisfied when the insurer updates them with claim status information. The survey results supported this information through scores indicating deteriorating satisfaction when customers find themselves having to call their insurer or repair facility. The panel agreed that getting the claim to the right person quickly and avoiding multiple handoffs was critical to improving customer communications. This was confirmed by survey data that showed consumer ratings drop by 133 points when customers are asked to repeat information during the claims process. The audience’s real-time polling indicated that typically at least three claims employees touch even the simplest claims. Improve Service Speed Customers expect their insurance company to make them a priority (“Prioritize Me”) when they have a claim. While we often think this means fast claims service, Pieffer explained that the survey results indicated that setting an accurate customer expectation at loss report was equally important to processing speed. In fact, meeting customer expectations on time-to-settle increases customer satisfaction scores even more than simply providing a fast claim experience. Spears explained how his company has completely redesigned the total loss claims experience by simplifying not only claims processing but also the car purchasing process via USAA Bank services and the USAA car buying service, which allows customers to be in their next car within a few days versus a few weeks (the industry average). Audience polling revealed that the optimal time to pay a simple claim should be within three days. Pieffer noted that the survey indicated today’s industry average is about six days. Optimize and Balance Self-Service Options Our final discussion topic (“Empower Me”) focused on the use of self-service technology. Pieffer shared data showing that Gen X and Gen Y customers (younger than age 50) were most comfortable with submitting damage photos via a mobile app and receiving electronic claims updates. While this was not a surprise, it was interesting to learn that satisfaction with digital FNOL was low for all age groups. The panel spoke about the need to simplify the FNOL process to minimize the clicks it takes to complete a digital FNOL. This was validated by audience polling, which overwhelmingly supported simplifying FNOL apps and minimizing clicks. I shared the value of bringing real-time data into FNOL and self-service applications to electronically verify first-party information to minimize additional inquiry. Furthermore, I noted that real-time FNOL data also allows third-party information to be collected immediately and accurately to simplify the FNOL process and make self-service reporting much easier for customers, which should greatly increase customer adoption. See also: The Missing Piece for Customer Experience   The panel discussion and audience poll answers confirm that delighting customers at time of claim is all about listening to, simplifying for, prioritizing and empowering them. As the P&C insurance industry continues to advance in claims automation, these four customer expectations should be front and center to ensure greater customer satisfaction and retention.

Artificial intelligence (AI) combines ability with autonomy. It is more than the product of its programming, as it evolves in real time—as it learns at an exponential rate—until it almost anticipates the needs of its users. It is proof of the existence of a greater good within the machine; that intelligence has many forms, and forms many languages; that what it says is indeed intelligible, provided we ourselves can speak its native tongue. What, then, does AI have to say about the insurance industry? In so many words: a lot. How we interpret and apply this language, how we convert so many ones and zeros into words of actions, how we honor our words with actions—these things depend on business expertise. By business expertise, I refer to those advisers who can decode the language of a computer code. I refer to those men and women who analyze data, whose analysis informs insurers of new markets and reveals subtle but significant changes in the market; whose guidance is less a matter of intuition and more an issue of intelligence both artificial and actual, as well as wisdom. See also: How to Use AI, Starting With Distribution   According to Nick Chini of Bainbridge, AI is as revolutionary to the insurance industry as actuarial science. It advances accuracy by dissecting the anatomy, so to speak, of policies, benefits and premiums. It atomizes the body of a business, so insurers can see what conventional technology cannot expose: the structure and strength of a particular client. It answers previously unanswerable questions about the health of a multitude of clients. It shows how tensile or tenuous the bond is between a business and its balance sheet, how profound or precarious its profits may be, how robust or ragged its sales will be. The legitimacy of the answers reflects the fluency of the adviser, whose skill determines the clarity of each message; whose scrutiny deciphers the importance of each missive; whose worth is contingent on his conclusions about each communiqué. What that adviser recommends, based on the materials AI allows him to read, promises to be more predictive than any model and more precise than any formula. The recommendation itself is the result of the union between science and sound advice, where guesswork yields to the hard work of substantiating what others claim but cannot prove. The proof is in the success of the insurance industry in general and the growth of individual insurers in particular. See also: 3 Steps to Demystify Artificial Intelligence   To sustain this momentum is to recognize the power of intelligence and the invaluable nature of wisdom. Put another way, a smart mind is no match for a strategic thinker. The latter gives voice to the former: It is a voice that humanizes a theory, because the narrator is a fellow human being. He is a voice of comfort—she is an adviser, whose voice inspires confidence—so insurers have the wherewithal to do and the wealth of resources to see their deeds to completion. So begins a new chapter in the history of the insurance industry.