Having completed the exploration of our global trends in our previous post on services, investments and job roles, we now turn to our key themes. In our next round of posts, we will explore 11 key functional and technological areas within insurance, starting with today's installment on analytics and AI. The following statistics on big data, analytics and AI are drawn from the extensive survey we conducted as part of our Global Trend Map; a full breakdown of our respondents, and details of our methodology, are available as part of the full Trend Map, which you can download for free at any time. Insurance, relying as it does on predictions about complex future events, has always been a data-hungry, data-driven industry. The big-data explosion of the past decade is therefore something that insurers have followed with keen eyes:

According to IBM, the world generates 2.5 quintillion bytes of data every day, with 90% of the world’s data having been created in the last two years.

While insurers, and most companies for that matter, have for a fair while had more data than they’ve known what to do with, analytical and machine-learning models are now sufficiently mature and sophisticated for them to start reaping the much-heralded rewards of the big-data revolution. This is not without its challenges, though, with silos and legacy systems in particular acting as a drag on innovation. Analytics is being deployed pretty much everywhere, and by everyone, in the insurance ecosystem, so this post covers:

• Analytics and data usage across various insurance ecosystem players
• Overall data strategy
• Issues with silos and legacy systems
• Contrasting flavors of analytics in use: descriptive, diagnostic, prescriptive, predictive, behavioral and, of course, AI!

"Causing the greatest stir out of all today’s analytics tools is AI, which stands to revolutionize the whole insurance industry over the next 2-5 years, from robo-advisers and chatbots through to claims automation and mitigating fraud. While analytics teams retain the greatest degree of oversight, AI capabilities are currently being embedded across the whole insurance organization." – Helen Raff, head of content at Insurance Nexus

As we shall see, the leadership on many of these measures is provided by reinsurers. This is evidence of their driving the whole ecosystem forward, and in this they often take the lead over insurers. We also see this more generally; for example, the giants Swiss Re and Munich Re have been particularly active in accelerator-based innovation over the past two years. See also: 10 Trends on Big Data, Advanced Analytics   Is your investment in/focus on analytics increasing? 84% of all respondents are increasing their investment in analytics. This conforms to the stats we presented in our earlier post on services, investments and job roles, where analytics was second only to digital innovation for increased carrier investment. Drilling down further into the responses of different company types, we see that similar proportions of insurers (82%), brokers and agents (76%) and technology partners (85%) are increasing their investment. Of interest is the clean sweep by reinsurers, exemplifying the leadership trend we pointed out. Analytics has applications across all the major lines. Health and auto are two obvious examples given the ready availability of connected health devices and in-car sensors, which make data easier to capture and, as an extension of this, models easier to feed. This facilitates usage-based insurance (UBI), which we explore in more detail in our forthcoming post on Internet of Things, whereby actual living/driving habits inform policy prices (read ahead straight away by downloading the full Trend Map for free). Analytics also has obvious applications for predictive maintenance and security in commercial, auto and P&C/general lines, particularly where valuable assets (like property) are in play. Analytics is also growing in home insurance thanks to the increasing prevalence of connected-home devices, with Berg Insight estimating that there were approximately 18 million smart homes in Europe and North America by the end of 2015.

"There will be much more data from structured and unstructured data sources in the future – a huge challenge! 'Past developments are a good representation of future uncertainty' will not be replaced but solutions with AI-tech (big data) in combination with smart data strategies will enable insurances to make decisions based on models and evidence." –Andreas Staub, managing partner at FehrAdvice

Is your analytics strategy coordinated across your organization? The uses and advantages of analytics have been obvious for a long time, and we have seen analytics initiatives sprouting up in nearly every corner of the insurance business, from underwriting through to counter-fraud. An ad-hoc approach, often inevitable in the early days of a technology, quickly becomes unwieldy, and the benefits from coordination are substantial. It is encouraging therefore to see 57% of all respondents indicating that their analytics strategy is coordinated across their organization. The trend across our different company types is similar to the one we saw in the investment/focus question above – unsurprisingly, as coordination is vital to gain maximum value from increasing investment and focus, and often represents a large investment in and of itself. We thus see 59% of insurers coordinating, 54% of brokers and agents and 55% of technology partners, with reinsurers once more taking the lead (77%). Are you utilizing external data sources? Plenty of data is available for analytics use beyond that directly captured by insurance companies themselves, both publicly available (like social media) and for-purchase (from third-party aggregators). There is no clear trend across our ecosystem players on this measure, with 77% of insurers, 67% of brokers and agents and 81% of technology partners affirming their use of external data sources (reinsurers had a small though insignificant lead). Segmenting by region, we can tentatively identify Asia-Pacific as trailing on this measure, and our broader research and industry engagement does indeed suggest that the third-party data culture is less-well-developed here than it is in North America and Europe. That said, public sources of data remain available, from unstructured social media through to data generated/collected by incipient smart-city infrastructure (like in Singapore). More details to follow in our forthcoming regional profile on Asia-Pacific, or read on straight away by downloading the full Trend Map here. Do you have a formal data-governance strategy? Insurance companies are being borne along on an exponentially growing tide of customer data, which has brought data governance to the forefront of people’s minds; yet, as of today, only 57% of insurers, 51% of brokers and agents and 58% of technology partners possess a formal data-governance strategy. We expect this figure to rise sharply in the years to come. Reinsurers once again appear to lead (with 77% affirming the existence of a data-governance strategy). Are legacy systems and silos a problem for your business? Capturing data is only the first part of the story to building out an analytics-based business. In many cases, analytics and big-data projects within insurance companies come unstuck not because of a lack of investment or strategic focus but for more prosaic reasons: silos and legacy systems. If infrastructural bottlenecks strangle rather than feed analytical models, preventing them from operating at scale across all the relevant data pools, then the output will be etiolated and limited in use. We asked respondents whether legacy systems and silos represented "somewhat" or "very much" of a problem for their businesses, and then created a "burden score" based on a weighted combination of these two figures. Insurers clocked up a burden score of 138, brokers and agents 103 and technology partners 105. (Reinsurers score 123.) There are two key takeaways from this. Firstly, that silos and legacy systems are a problem for the entire insurance ecosystem. And secondly, that carriers are generally harder-hit (comparing insurers and reinsurers to the rest of the industry), which may well reflect their position as the central node of the industry into which all the other players feed. From descriptive analytics to AI: What's your flavor? With all new technologies or methods, there is generally a gap or lag between what is theoretically possible and what finds its way into commercial practice. We asked insurers and reinsurers what forms of analytics they were deploying out of a possible six options: As we can see, every form of analytics has attained at least a modest level of penetration, and we can tentatively construe from this an adoption curve of different analytics formats running roughly from predictive, descriptive and diagnostic (high degree of current adoption) through to behavioral, prescriptive and machine learning/artificial intelligence. So, while most respondents have developed capabilities to describe and predict, only a minority have advanced beyond this toward prescriptive and AI capabilities.

"The rise of insurtech, the analytics explosion and the new face of insurance has created a birth of new roles and impact points across the industry. No longer is analytics and data relegated to just information technology and actuarial — we are now seeing it being integrated into the business culture and DNA of insurance organizations." – Margaret Milkint, managing partner at the Jacobson Group

Analytics is a very broad category with applications across almost every part of insurance, from underwriting and marketing through to fraud and claims, as well as on the investment side of the business. For the sake of clarity, we have chosen to focus in on two areas of insurance work, underwriting and claims, to capture a snapshot of analytics maturity at the start and at the end of the policy lifecycle. The donuts above indicate the share of analytics work (as a proportion of the whole) being undertaken by respondents working in the areas of underwriting and claims – this is an intuitive way to compare the prominence of different flavors both within, and between, these two areas. A larger proportion of the analytics work undertaken by underwriting respondents appears to fall at the early stage of the adoption curve (descriptive and predictive) and a smaller proportion at the later stage (moving toward machine learning and AI), when compared to respondents working in claims. This implies that claims either encourages more advanced analytics than underwriting – which may be oversimplifying things – or that, for whatever reason, it leads underwriting on analytics maturity. See also: Why to Refocus on Data and Analytics   Join us for our next post, on digital innovation, where we talk about the rise of mobile and the many flavors of digital strategy. Or, if you'd like to access all 11 key themes straight away, simply download the full Trend Map free of charge. For any inquiries relating to the Insurance Nexus Global Trend Map, this content series or next year's edition, please contact: Alexander Cherry, head of research and content at Insurance Nexus (alexander.cherry@insurancenexus.com)

Drones are flying higher than ever. A recent Goldman Sachs forecast values the overall market opportunity for drones at $100 billion between now and 2020. Gartner predicts that global sales of drones for personal and commercial use will hit $6 billion this year and grow to $11.2 billion by 2020. But, as drone sales and applications grow, drone accidents are keeping pace. It’s a big opportunity for insurers. By the end of 2020, the drone insurance market could be worth more than $500 million in the U.S. and $1 billion globally, according to Allianz. See also: 5 Ways Drones Are Changing Insurance   Drones have already been involved in many incidents of property damage and other mishaps. Notable examples include collisions with a nuclear power station in Cape Town, the Empire State Building in New York, the grounds of the White House in Washington, DC, a Norwegian ski hill in the middle of a World Cup slalom race and the fingers of the singer Enrique Iglesias during a concert in Mexico. The most recent statistics from the Federal Aviation Authority (FAA) reveal that drone safety violations in the U.S. are up 46% year-over-year. It is therefore no surprise that insurers have started to offer coverage for private and commercial drone users. Some notable examples:

• In July, a subsidiary of the German insurer Allianz announced a partnership with Flock, an insurtech startup that analyzes real-time flight-risk information to provide pay-as-you-fly insurance. Allianz and Flock plan to launch the “Flock Cover” app in the U.K. sometime in 2017, which will offer recreational and commercial coverage for up to £10 million (US$13.6 million). The app is still in development as of this writing, but enthusiasts can sign up to beta test it on Flock’s website.
• Munich Re began offering commercial drone insurance in the U.S. in June in the wake of new regulations from the FAA. The product targets small and medium-sized businesses, including farms, that use drones. It covers injury and property damage coverage for drones that weigh as much as 55 pounds (25 kg).
• Founded in 2015, the insurtech startup Verifly offers on-demand drone insurance for recreational and commercial flights in the U.S. Earlier this year, Verifly partnered with Loveland Innovations to offer insurance for insurance adjustors and contractors using drones. The insurance is provided through Loveland’s IMGING drone property inspection platform.
• In May, a subsidiary of Liberty Mutual Insurance Group announced DroneInsurance.com in conjunction with the insurtech Acend. The site aims to offer a convenient place for American drone users to buy flexible insurance from brokers. As of this writing, DroneInsurance.com was still in development, though interested parties could sign up to be notified when it launches.
• Ageas, a multinational insurer based in Brussels, includes drone coverage in the U.K. under its “Back Me Up” flexible insurance platform. Customers are covered for accidental damage, theft and loss of their drone, anywhere in the world. Coverage starts at £8 (US$11) a month.

See also: Drones + Gig Economy = Win for Insurance As drones become more popular and profitable, insurers will create offerings similar to these examples and innovative new ways of mitigating risk. Some of these new ideas will tap into the broader potential of the Internet of Things, which I recently wrote about in another blog series, and which is becoming increasingly visible in the industrial sector.

Do you know anyone in the professional world who does not talk about risk? I don’t. As a matter of fact, human beings rose to the top of the food chain because of the ability to perceive and manage risk. Other animals also manage risks, but in a more instinctive way generally based on "fight or flight." So, why do we seem to make a big deal out of risk management if everyone does it and we humans have been at it for millions of years? Last I checked on Amazon, there are more than 22,000 books on risk management. But who's counting? It seems new jargon is added to the cauldron of concepts and ideas and frameworks of risk management on a daily basis. By the time companies get halfway through the implementation of a framework, it has already become obsolete. There are so many competing solutions being offered in the risk management marketplace – every consulting company has its own branded product. So many solutions looking for a problem. But what is the problem? See also: 4 Steps to Integrate Risk Management   At a very fundamental level, risk management is about identifying, quantifying and managing risks. And managing risks has four components – avoid, mitigate, transfer or accept risk or some permutation and combination thereof. As Sherlock Holmes would say – "It is elementary, my dear Watson." In reality, though, it is anything but. The challenge is not the what and why of risk management but the how. Let me clarify. Businesses exist and prosper because they create value. That means a decision involving land, labor and capital needs to be made in the present expecting an outcome in the future. Given that no one has perfect insight into the future, there is uncertainty about the outcome and hence there is risk involved in every business decision. So, it makes perfect sense to be able to manage that risk within an acceptable limit. The question is how. There is a lot of fumbling around there. First, before we can manage something, we need to understand it. Risk is manifested in many different ways and often not in a homogeneous manner. For example, a risk to the balance sheet is not easily comparable with risk to earnings or to cash flow. Risks in the short term are not easily comparable with risks in the long term. Risk from the individual leader’s perspective is not easily comparable with the risks from the organizational perspective. Risk professionals often say risk and opportunities are two sides of the same coin. I say not quite. For example, what may look like an opportunity from an earnings perspective may involve a huge risk on the balance sheet. So, how does one compare and manage even when one identifies the risk properly? Second, we need to think of managing risks while the decision is being made, not after or even before. Risk is not the same as uncertainty. I find it fascinating that some GRC (governance, risk and compliance) frameworks talk about creating and maintaining a risk universe as if risks exist independent of organizational decisions. I am not sure if this is because the creators of these frameworks do not know any better or because they are just out to make a fast buck off the naïveté of their clients. See also: Why Risk Management Certifications Matter  Third, I find risk professionals (at least some of the savvier ones) put a lot of emphasis on modeling and quantification of risks. Don’t get me wrong. I absolutely think measuring risks is necessary. But it is a necessary evil, as it is fraught with assumptions, and often the decision maker is oblivious to them. Quantification is only a means toward the end, not the end by itself. The goal needs to be to understand the level of risks so that appropriate resource allocation can be made. Remember, we do not have unlimited resources, and, therefore, we need to prioritize risks. At the heart of it, the purpose should be to understand the level of risk the business needs to accept. No amount of Monte Carlo simulation can help if this goal is not met. I rest my case here. Looking forward to receiving comments and feedback.

Is this claimant supposed to be off work? Did I get enough discount on the services? Were those services even necessary? I would argue that the question everyone should be asking instead is: Who is your doctor? After all, the physician is the person who sets all of the other wheels in motion — wheels that influence things from quality of care to how long an employee is out of work and the ultimate cost of an injury. Throughout the past 15 years that I’ve spent managing networks and working with top companies developing custom solutions, one thing has consistently held true: Physician quality matters … A LOT. In fact, provider quality is shown to make the single greatest impact on a claim. It’s something that shouldn’t be overlooked, and yet all too often it is. Numerous studies have shown that good doctors make a difference. There is a huge discrepancy in claims associated with doctors who score well on an outcomes basis versus those who don’t. The average costs associated with a problematic D- or E-rated physician, compared with a rock star A- or B-rated doctor, are astounding when you really dig into the data. It is even more profound when you factor in case mixing and adjust results based on severity or type of claim. See also: The State of Workers’ Compensation   A wealth of information now exists on physician quality, and many different models, from simple to complex, can provide useful insights into which doctors can be associated with better outcomes. Carriers and employers should apply this data to think more aggressively about their networks. The PPO Dilemma Before we get there, however, let’s look at what’s going on with preferred provider organizations (PPOs). PPOs are the most common strategy used to control costs in our market. A PPO’s value comes from providing a negotiated discount on a medical encounter. Once you have entered into business with the PPO, its primary revenue source comes from matching your bills to a pre-negotiated discount — and the PPO gets more matches by contracting with more doctors. Therefore, if the PPO only contracts with the doctors who show the best outcomes, the PPO loses significant amounts of revenue any time bills come in from uncontracted doctors who don’t perform as well in outcomes. As such, all discount networks must contract with as many doctors as possible to ensure they don’t lose revenue by missing a hit on a bill. A perfect PPO would include 100% of doctors who pass the base qualifications of credentialing. But, as shown in the prior illustration, there is a huge difference in outcomes between the top half and bottom half of the PPO’s doctors. I don’t fault PPOs for this — PPOs do offer a clear value in reducing purchase costs per episode. They also must contend with multiple factors from jurisdiction to jurisdiction that will always limit how choosy they can be. There is a role to be played by discount networks, but that role is not the full picture of how to bend the curve on claim costs. “Savings” Don’t Always Reduce Costs Here is a simple concept: If a cheap pair of shoes costs 30% less than a high-quality pair, I might save money on the initial purchase, but, if the cheaper pair of shoes needs to be replaced twice as often, my savings on each transaction doesn’t lower my total shoe cost. Applying this logic to medical care, let’s look at two patients — one going to a discounted doctor and one going to a full-fee-schedule doctor. Let’s assume a typical ratio of 7:5 visits between high-scoring and mid-tier doctors (the real difference is typically higher). Patient A goes to an in-network doctor selected at random from an approved list of providers that generates a 5% savings off each bill. Patient B is sent to a doctor with a high outcome score but no discount. The average bill from each doctor is $100. After the first visit, Patient A has cost $95, and Patient B has cost $100. The payer for Patient A saved $5, and the payer for Patient B has saved $0. By the time Patient A has been to his/her seventh and final visit, medical care cost $665, with PPO savings of $35. Patient B’s care wrapped up after five visits, costing $500, with $0 in PPO savings. This showcases the problem of using percent of savings as a metric – longer duration and $165 more in total medical costs reflects $35 in savings over Patient B. The metric is flawed because the more you spend the more you save. The point to consider is that network savings are the shiny object that distracts from the difference in total costs. I am not arguing against leveraging savings where available; rather, I want to underscore that quality at a higher price point can significantly outpace discounts when you look at the total cost of a patient in any market. All health markets suffer from the cost of care that requires too many visits or the additional costs of a second necessary procedure to repair a bad surgery. In workers’ comp, this is exponentially compounded when you factor in the costs of temporary disability as a result of poor recovery and permanent disability stemming out of failed procedures. The Path Forward The best way to start down the path forward is to separate the decision about which doctors to work with from how to work with them. The who should be determined by some level of quality metric while the how is figuring out which PPO or contractual relationships get you the best access to doctors who will get you the best results. This means you should first find the doctors who perform well on your chosen metrics, and then look at the PPO or combination of PPOs that get you contractual access. It works in the opposite flow as well; you can look at the total population of doctors available through your network vendors, then pick who you want to work with from that list. See also: Even More Tips For Building A Workers Compensation Medical Provider "A" Team   In part two of this series, I will go into the concept of right-sizing networks and the relationship between PPOs and exclusive provider organizations (EPOs). Pick the doctor, and then figure out which network or combination of networks provides access. It may require a little more work and data science on the front end, but the outcome is well worth it. As first published in Claims Journal.

Telemetry, IoT, wearables, AI, chatbots and drones are tools that help group insurers better engage with customers and improve business processes. There is one thing that all of these technologies have in common: data. Personal data to be precise. Exactly how insurers will mine, manage and utilize the massive amounts of data now available from various internal and external sources may mean the difference between data mastery and data mystery for many carriers. In this blog, I’ll outline a few things carriers can start to think about as they incorporate big data into their corporate strategies. See also: 10 Trends on Big Data, Advanced Analytics   Start Out Simple and Stay Focused Data science is composed of several disciplines and skill sets. AJ Goldstein does an excellent job of deconstructing this complex craft into what he calls, “The Data Science Process,” consisting of six parts:

1. Frame the problem
2. Collect raw data
3. Process the data
4. Explore the data
5. Perform in-depth analysis
6. Communicate the results

Goldstein says that, although data science is a large, complex paradigm, only about 20% of the skills needed will contribute to 80% of the outcomes. So focusing on that core 20% necessary to achieve the results you’re looking for will help simplify the process and keep IT departments focused on the goals you originally set out to achieve with the data. Applications for big data in insurance currently center on providing solutions to tasks like premium setting, fraud reduction and target marketing. How this looks will differ across projects, but regardless of the application, data experts will collect data from various sources, analyze it and use it to draw conclusions about how the company can improve the bottom line and provide value to customers. They don’t call it big data for nothing! The amount is gigantic. New variables and trends that arise can easily lead you astray from the original question you set out to answer. Stay on track and focus on what you set out to determine. You can always circle around to address new insights later. Mitigating Risks Consumers know that sharing data comes with risks. Even the most hardened networks can be vulnerable to cyber-attacks and data breaches, leaving consumers understandably wary of how and with whom they share their personal information. Carriers that take the proper cybersecurity measures will be better prepared to ward off or respond to breaches. Obtaining accreditations such as ISO 27001 may help identify any gaps before hackers do. Privacy is another important factor when obtaining and storing customer data. Consumers want to know what their data is being used for and be assured that it will not be used for anything else. If carriers can guarantee this, studies show that customers are willing to provide personal data in exchange for lower fees and improved services. See also: Next Step: Merging Big Data and AI   When the proper measures to manage big data are in place, an opportunity to form digital trust with customers is possible. If this is established, the possibilities are endless for the kind of engagement and relationships that can be developed and sustained. With information everywhere, people still value relationships they can trust. That’s never going to change. Insurers have gone from seeing the value in data, to being able to analyze it, to capitalizing on automation that is now having an immediate impact on operations. The ability to automate business front-ends and back offices has in many cases catapulted insurers into the digital age, and most are landing on their feet. This is due in no small part to strong leadership from CIOs, a shared understanding of what customers now expect and a mandate to provide it. Insurers that master big data will likely leap to the front of the pack. Those that see it as a mystery may quickly find themselves out of the race.

Given that the customer of the future wants solutions rather than products, the employee benefits provider of the future will offer a wider range of products, all designed to work together. Knowing that careers are becoming to be more fragmented (shorter tenure, parallel income streams, the gig economy), the employee benefits provider will also reduce its dependence on employers. See also: The Insurer of the Future – Part 10   The employee benefits provider of the future will offer a broad platform with multiple products (not least life, retirement, health, auto and home) open to employees of multiple companies. That doesn't mean every employer's scheme will be the same, as there will still be specifics tuned to the desires of individual companies. But all of the core covers will be the same, allowing the benefits provider to leverage massive buying power, securing excellent deals for employers and employees alike. Because the core benefits are the same across companies, they're also portable - very helpful in a world where employees hop regularly from job to job. When an employee leaves company A, he or she can port the entire benefits package to company B. If there’s any premium shortfall, the employee can pay that personally. And the employee benefits provider retains the employee as a customer for longer. But the new proposition goes even further - because the model recognizes the gig economy and is therefore open to one-person businesses such as Uber drivers as well as employees of larger companies. This, of course, further broadens the customer base served by the provider. See also: 4 Hot Spots for Innovation in Insurance   In time, workers' loyalty will perhaps become more focused on their employee benefits provider than on their individual employers - re-positioning this segment of the industry and opening up further opportunities for innovation. Earlier articles in this series can be found here.

In the last few years, insurers have raced to capture the massive opportunities created by new technologies and have learned to turn the threat of insurtech startups into smart collaborations. The result has been the avoidance - so far - of any significant loss in revenue and profitability. Nevertheless, not only does technology continue to progress rapidly, but the American and Chinese tech giants, with their global ambitions, pose new challenges to the industry. Policyholders have come to expect the same level of convenience and engagement from their insurers, and some observers even start to fear that, in their ruthless march to global domination, those giants may encroach into insurers’ territory. Insurers have a window of opportunity to leverage their consolidated customer base, deep industry knowhow and solid balance sheets to strengthen their competitive position. Look at what happened to Google Compare, an auto insurance aggregator launched in U.S. and U.K. that has been far from successful. To pursue long-term profitable growth, insurers should start focusing on opportunities for non-disruptive market creation, as well. Most of us, including insurers and insurtech startups, have come to equate technology with disruption, where a market is created by a new solution that displaces an existing one. Look at the KYC technologies that are replacing the need for face-to-face interactions. In reality, as pointed out by Professors Kim and Mauborgne in "Blue Ocean Shift," the sequel to their global best seller "Blue Ocean Strategy," a focus on disruption is limiting and leaves half the opportunities to create growth and markets off the table. The key is to realize that we do not necessarily need to destroy an existing market to create a new one. While disruption sets out to better solve an existing problem faced by current customers, non-disruptive innovation creates “blue oceans” by targeting noncustomers of the industry or solving “brand new” problems. See also: On-Demand Insurance: Ultimately a Bust?   Take BIMA, which is creating a blue ocean by offering affordable microinsurance products to the “bottom of the pyramid.” BIMA, which was established in 2010 in Ghana, has rapidly gained scale and is now bringing microinsurance to 24 million customers across Asia, Latin America and Africa. More than 90% of its customers live on less than $10 per day, and three-quarters are accessing insurance for the first time. Developing countries have economies that are generally based on farming and agriculture and require a wide range of insurance products from health and life, accidental death and disability, agricultural and property insurance, to catastrophe cover. In those countries, microinsurance already covers around 135 million people,  but that represents only around 5% of the entire market potential. Growth is expected to be between 8% and 10% a year for the next years. Similarly, microinsurance can be marketed in developed countries to reach the underserved segments of the population who struggle to afford more comprehensive products. However, microinsurance is not just a reduced-cost coverage for low-income customer segments in both emerging and developed economies; it is an entirely new way of selling insurance and creating demand. In fact, consumers who can afford traditional covers may not perceive the need for insurance until an event occurs or an intermediary stimulates such awareness. They are often unaware of the need or just the possibility to insure against a specific risk; insurers submit complex and cryptic contracts requiring a lengthy and cumbersome purchasing process that individuals are not able or willing to follow. Not surprisingly, recent studies report that millennials are the most underinsured generation and are the least likely to have any health, rental, life and disability insurance. Millennials are just one of the segments of the so-called "connected generation," an immense blue ocean opportunity also including Generation Y and the Silent Generation, Baby Boomers, and Generation X, who are shifting to mobile purchase habits. Empowered by technology, all these individuals look for authentic services that they can access across multiple platforms and screens, whenever and wherever they need. Their protection gap is estimated at more than $3.5 trillion. The key to selling insurance to the “connected generation” is to reach them with the right proposal through engaging touchpoints on a device they swipe, tap and pinch thousands of times a day: their smartphone. Helping insurers to unlock this blue ocean opportunity with a customer-centric mobile insurance proposition is the mission of Neosurance, the start-up that we cofounded and that created the first virtual AI-based insurance engine. Neosurance stimulates the protection need “pushing” the right cover at the right time on customers’ smartphone, thus triggering an emotional and impulse purchase for a small-ticket item. Insurance purchase becomes a “rational impulse,” and the transaction is completed at the “point of need” rather than at the traditional “point of sale.” This is possible because the customer experience is entirely paperless and takes less than 20 seconds. See also: The Insurance Renaissance Rolls On   Neosurance relies on a partner-friendly “plug and play” SDK easily embeddable in any app, allowing carriers not only to target their captive audience but also to tailor their insurance proposition to the front-ends and customer journeys of their community partners. In doing so, insurers (and reinsurers) can maximize customer engagement by protecting people’s common interests and passions and build a holistic ecosystem of digital communities to create a blue ocean of uncontested demand. In the future, as insurers learn to leverage the massive amount of data they collect and to analyze it through context, psychographic and behavioral profiling, more blue ocean opportunities will be generated. In particular, carriers will be able to upgrade their role throughout the end-to end customer journey from that of a simple "payer" to that of an active "player," multiplying customer touchpoints, boosting satisfaction and ultimately creating opportunities to cross-sell insurance and non-insurance products and services. This article was originally published on InsurTechNews.com. It was written by Andrea Silvello and Luciano Pezzotta.

Insurtech making your head spin? Perhaps it’s because of the confusion whether insurtech is a “there and back again” project or more of a paradigm shift? No one can deny the great impact that J.R.R. Tolkien’s books and movies have had on our culture. He’s been called the father of modern high fantasy literature. Not that money has the final say on one’s success and impact, but in 2009 he was ranked by Forbes as the fifth top-earning dead celebrity. From my perspective, Tolkien’s books are fabulous and intensely engaging. I was listening to a literature professor talk about Tolkien, and he made a most interesting observation on how very different his books were. He described "The Hobbit" as an adventure, while "The Lord of the Rings" was a quest. He went on to say that "The Hobbit" is a “there and back again” adventure story, where you go out, experience thrilling events and then come home again. But "The Lord of the Rings" was a quest; you leave home and are fundamentally changed by the events you experience. In a quest, you may physically return home, but you are so altered that in a real sense you never return home. I had never thought of the books in this way before. As a matter of fact, "The Hobbit’s" official title is “The Hobbit, or There and Back Again.” At the end of "The Lord of the Rings – The Return of the King," Frodo Baggins returns to the Shire but never quite feels at home and eventually leaves Middle Earth with the elves and Gandalf. See also: Core Systems and Insurtech (Part 3)  Insurtech can be looked at in a similar way. Do we view insurtech as a journey, or is it a quest? Is insurtech a “there and back again” project that has a start, middle and end, or a more fundamental paradigm shift in our thinking? Is insurtech to be bandied about as yet another consult-speak hype-phrase added to web pages, slide decks, articles, polls and white papers so we can be 100% buzzword-compliant? Is it hurriedly tacked on as yet another topic on an already bloated agenda of items to be covered? Or is it something substantially more? There are more insurtech lists, companies, conferences, accelerators and analysts than you can shake a stick at. There are more than 1.2 million results when you Google "insurtech." You could make it your life’s work just tracking insurtech. Using the “there and back again” definition, the vast preponderance of what is labeled today as insurtech is a journey, and there is nothing wrong with that. Within the insurance industry, we definitely need incremental new products, ideas and solutions that gradually move the needle when it comes to process streamlining, reducing costs and greater customer engagement. We applaud their efforts and wish them all success. But the number of insurtechs that can earn the quest moniker is much smaller. While many web sites and brochures purport to be a game-changing quest, most are actually a journey in quest’s clothing. So, how do we make sense of it all? First, figure out if the insurtechs you are working with are on a journey or a quest. Here are six marks of an insurtech that is on a quest. You don’t have to exhibit all six to be on a quest, but four is a minimum:

• Big Audacious Dream – Sometimes referred to as the BAD idea, this visionary and emotionally compelling future state is dramatically different than anything yet proposed.
• Multiple Directors – There are not only numerous users that employ the solution, but it directs multiple stakeholders both inside and outside multiple organizations.
• Revenue Diversity – Income comes from numerous different users, stakeholders and sources; the quest is not tied to traditional license/use fee revenue streams.
• Elongated Delivery – Because the quest is by nature long and complicated, quick deployment is not possible; delivery will take time and significant investments.
• Lots of Data – While functionality is important, large amounts of data from various sources are brought together in new and compelling ways that transform traditional tasks into new opportunities for customer satisfaction, additional sales and revenue opportunities.
• Numerous Detractors – Few will understand or initially identify with an insurtech quest, thinking it outlandish and outrageous; most will immediately dismiss it or continually poke fun at it.

Second, it’s more than OK to be engaged with multiple insurtechs that are on an adventure. As a matter of fact, it’s wise not to put all your insurtech eggs in a single basket. Some will make it, others will not, so hedging your bets is a good thing. Third, an insurtech on a quest is not for everyone. You can probably only deal with one at a time. They will take longer to develop and deploy than an adventure insurtech. Fourth, you should periodically reevaluate the insurtechs you’re involved with, eliminating some, adding others. P.S – if you are an insurtech that is on a quest, welcome to the club! See also: Why #Insurtech Doesn’t Matter   It’s easy to become discouraged and think you will never succeed. Take heart. Here are five encouraging Tolkien quotes from "The Lord of the Rings":

• “The quest stands upon the edge of a knife. Stray but a little, and it will fail, to the ruin of all. Yet hope remains while the company is true.” Galadriel, "The Lord of the Rings: The Fellowship of the Ring"
  • There will be days when you are convinced that your quest is teetering on the edge of failure. It’s at times like this that you need to seek encouragement from your team and supporters.

• “The Ring-Bearer is setting out on the quest of Mount Doom.” Elrond, "The Lord of the Rings: The Fellowship of the Ring"
  • There will be days when your quest seems destined for financial failure and industry embarrassment. Listening to your detractors is a recipe for certain defeat. If necessary, recalibrate your goals and move forward with your team and supporters.

• “This quest may be attempted by the weak with as much hope as the strong. Yet such is oft the course of deeds that move the wheels of the world: Small hands do them because they must, while the eyes of the great are elsewhere.” Elrond, "The Lord of the Rings: The Fellowship of the Ring"
  • Leadership is vital on a quest, but more is accomplished not by the great or brilliant, but by average people. Do not overlook their value or contributions.

• "What is to be my quest? Bilbo went to find a treasure, there and back again; but I go to lose one, and not return, as far as I can see." Frodo, "The Lord of the Rings: The Fellowship of the Ring"
  • To succeed in your quest, you need to have an attitude of abandonment, willing to lose to win. You will need to hold loosely those traditional things that have given you stability and success.

• "But do you remember Gandalf's words: Even Gollum may have something yet to do? But for him, Sam, I could not have destroyed the Ring. The quest would have been in vain, even at the bitter end. So let us forgive him! For the quest is achieved and now all is over. I am glad you are here with me. Here at the end of all things, Sam." Frodo, "The Lord of the Rings: The Return of the King"
  • When you have succeeded, you will look back and remember people whom you thought were your supporters and friends but turned out to be your enemies. Don’t harbor anger and bitterness.

Work hard and enjoy the quest.

This morning, I was reading a new article essentially about how insurtech disrupters were going to destroy the insurance industry. As is often the case, these startups were compared to Amazon, something I’ve blogged about on several occasions, including in the article “Insurance and Paper Towels.” Among the predictions of this article were: “And you’re going to get disrupted in a way that’s staggering in its infinite nature, with infinitely more data points, infinitely greater opportunities and, as a result, infinitely more options amid a sea of competition, which makes you feel infinitesimally small. Suddenly. This competitive force has built such a commanding, unexpected lead. Yes, a good, old KO before you even heard the bell go off. You will likely default, and it will be too late to pivot. “For the lucky, the ability to slip into obsolescence and appreciate the nostalgia of the past will do. (Of course, not the positive vibe-nostalgia, the punch-drunk love of sentimental warmth. Nope, as you become a relic of history, the nostalgia will be more like the Greek word root for nostalgia, which translates to pain, or more specifically the debilitating and often fatal medical condition expressing extreme homesickness).” See also: How to Respond to Industry Disruption   Yikes! Gadzooks! Godfrey Daniel! (and other “old-timey” expressions of fear and terror used by industry fossils like me). Or, better yet, he “blathers like a bubbly-jock,” an 18th century expression that means to prattle like a gobbling turkey or “to talk rubbish.” The article concluded with: “…you’re about to be disrupted. Amazon ring any bells?” Yep, so does Google Compare. And Airbnb Insurance and Guevara and Guild and Health Republic and Risk Genie and Tribe Cover and Zensure and RiskGone and…. Amazon sells products with a known cost. Insurance involves parties entering into complex, legal, highly regulated indemnification contracts where the costs are not fully known and one event can be financially catastrophic for either or both insurer and insured. Insurance is more process than product. It begins with an individual risk exposure analysis, continues with matching the results of that detailed survey with the proper risk management technique (one of which is “insurance”), then moves to interpreting a complex legal contract IF a loss event occurs. Insurance in its present form does not lend itself to an Amazon-like “1-Click” purchase. Insurance contracts are not commodities distinguished only by price. If I buy three pairs of crew socks on Amazon and they don’t fit or I don’t like them, at worst I’m out a few bucks or the inconvenience of a return. If I choose the wrong insurance product, I may almost literally lose everything I own, and, in the particular case of liability claims, I may have my income garnished for the next 20 years. Insurance is a complex process, not a single event where all that matters is a fast/easy/cheap convenient and pleasant customer buying experience. The true test of the insurance product is whether it covers a claim. Again, in the particular case of liability exposures, the value of the purchase may not be known for years. See also: Why Insurance Is Ripe for Disruption   Those who think they can disrupt a centuries-old industry with a phone app and an AI bot that extracts bad data from a county tax database without human intervention aren’t being innovative. They simply lack a valid historical perspective of the industry and a fundamental misunderstanding of what the industry is all about. What the insurance industry is all about is assisting individuals, families and organizations in identifying their exposures to loss and implementing the most appropriate risk management techniques to minimize the potential for serious or catastrophic financial loss. How many insurtech startups will figure this out before they run out of venture capital or ruin the lives of an unsuspecting public?

“Alexa, can you tell me the impact of the wholesale shift to voice search and voice communication over the internet?” Amazon’s wildly popular personal assistant, Alexa, probably cannot answer that question for you. And even she doesn’t perceive how she is making us dumber and taking our choices away. The world is surely moving from text to voice as the primary interface on the internet. The rapid rise of Amazon’s Echo (and its smaller version, the Echo Dot) personal assistant device was the biggest story of the 2016 holiday shopping season. As of September 2017, Amazon had sold 15 million Echos, and Google had sold five million of its own personal assistant device, the Google Home. This is impressive, for a category that just a year earlier had not existed. Even more significantly, we are switching to voice as the means of communicating with our smartphones. More than 20% of mobile searches were conducted via voice in 2016, according to Google: a roughly a 35-fold increase in voice search since 2008. Google also found that about two-thirds of its users conduct voice search via mobile phone several times per day and that roughly half of its users use voice and text search interchangeably. See also: Could Alexa Testify Against You?   Such growth has been enabled by dramatic improvements in voice recognition, through use of powerful artificial intelligence systems that use machine learning. We are now in a positive feedback loop for voice: As more people talk to their smartphones or home assistants, more data become available to companies such as Amazon, Google and Apple to feed to their personal assistant systems. As of May 2017, Google’s speech recognition error rate was 4.9%, down from 23% in 2013. Businesses have recognized the shift in accuracy and customer engagement, and are piling in. Amazon now boasts more than 15,000 Alexa “skills,” which are capabilities that allow customers to make personalized requests. For example, travel search providers let you plan vacations via Alexa using voice commands; Pizza Hut lets you order pizza; Nissan and Hyundai let Alexa owners start their cars’ engines and set their temperatures; Capital One lets customers check their bank balances; and Campbell Soup Company supplies recipe ideas. The shift to voice search and voice communication will surely make many things more convenient for us but will dramatically reduce our online choices. The reason for this is simple: When results are spoken back to us, we will receive only a few options, because humans cannot absorb 10 results in succession and adequately choose between them. We can’t remember them all. This switch in information density has profound implications, and voice search can subvert our purchasing choices in subtle ways. Prior to the advent of the internet, when we looked at the Yellow Pages, we had many pages of options. When we searched online, we had even more options but tended to only react to those on the first page. Increasingly, those first-page results are sold to the highest bidder. On mobile phones, the searches mean even fewer options, and the paid ones utterly dominate the screen. In the results of a voice search, we are usually down to only two or three options. People just can’t remember more information presented to them vocally. So your search for “best hotel in San Francisco” will yield only a few results. The response to “I want to find a pizza place in Palo Alto” might not show the pizza joint that is the best in town, because it has not bought its spot in the search results. Most worryingly, the shift to voice will further consolidate power in the hands of the big providers, such as Amazon, Google and Apple. When we ask Alexa to add olive oil to our shopping cart, we are ceding our choice to Amazon. Maybe we prefer Californian olive oil, because we know it is less likely to be adulterated. Or maybe we would rather buy the lower-priced of two favorite brands. With voice, which olive oil goes into the cart becomes Amazon’s decision. Unsurprisingly, research firm L2 found that Amazon is more likely to put its own proprietary products into your shopping cart. In theory, we could ask for more voice results to get richer searches. Or perhaps voice assistant systems will eventually be improved to include capacities such as following up to ask us whether we want, for example, a particular type of pizza. See also: ‘Alexa, What Is My Deductible?’   But even if that happens, the world of voice is taking us back a century in terms of information density. Talking to a voice assistant is a lot like asking a friend for restaurant recommendations, except that friend is a giant technology company that makes its money from the recommendations it provides us. That doesn’t sound very friendly. This article was written by Vivek Wadhwa and Alex Salkever.