As Congress looks at restructuring two national insurance plans — the American Health Care Act of 2017 and the National Flood Insurance Program — legislators must address the issue of fairness. That is the view of Wharton professors Howard Kunreuther and Mark Pauly, who co-wrote the book, "Insurance and Behavioral Economics: Improving Decisions in the Most Misunderstood Industry." In this opinion piece, they argue that considering the issue of fairness in designing these programs is not merely an exercise to aid the old and needy. Rather, it is also to make legislators think about what policies will make premiums less onerous to people with lower risk so they will not be discouraged about getting coverage. The U.S. is at a critical moment as Congress is attempting to determine how two insurance programs should be structured to help Americans who need protection from physical and financial risk. Both the reauthorization of the National Flood Insurance Program (NFIP) and the American Health Care Act of 2017 raise questions as to whether affected individuals would be treated more fairly under the new legislation than they currently are. For us, fairness in the context of new legislation means consideration of the impact that a sudden increase in premiums or unexpected changes in the terms of coverage will have on the well-being of the affected individuals. See also: Flood Risk: Question Is Where, Not When   When the National Flood Insurance Program (NFIP) was enacted in 1968, there was a concern that high premiums would significantly reduce property values and that this could become an unfair economic strain. For this reason, the NFIP specified that homeowners living in high-risk areas at the time the law was enacted would be charged a subsidized premium. The same potential conflict regarding fairness applies to health insurance. Is it fair that those with pre-existing medical conditions or those who unexpectedly acquire high-risk conditions might have to pay much higher health insurance premiums than when they were less at risk?  Yet this is what will happen if private insurers are allowed to charge risk-based premiums and politicians decide to provide limited subsidies to cushion those higher premiums.  However, is it fair to impose high premiums on individuals with low risks to finance such subsidies? And is it fair to offer no reward to those who take steps to improve their health status and thus reduce their future health spending risk? Elected representatives on both sides of the aisle continually espouse the principle of fairness across a wide range of issues, including trade, tax reform and jobs. If they truly want to extend that allegiance to the principle of fairness, they might wish to consider offering some form of financial assistance to help working class families who become high-risk for floods or to help them buy or continue coverage for health care. The choice of the right amount of support regarded as fair is ultimately a political issue where voters’ perspectives may differ. There are efficient ways to address the fairness problem for both insurance programs that might gain bipartisan support. With respect to health insurance premiums, it is easy to justify assisting low-income and older people who want to buy coverage. Empirical studies of Medicaid programs suggest that individuals care about other people’s health conditions. Many taxpayers are thus likely to support having the public sector cover part of the cost of health insurance for those whose health might be improved by having insurance. In the case of flood insurance, those subject to water-related damage should receive information on the cost of insurance that reflects their flood risk. If this risk-based premium exceeds a proportion of their income or housing costs, they could be given an insurance voucher or tax credit so they could afford insurance. A new RAND study recommends that those whose total housing costs — including flood insurance premiums — exceed a certain percentage of their income be provided with financial assistance. This would ensure that taxpayers are not subsidizing high-income individuals. It is important to encourage property owners in flood prone areas to invest in cost-effective, loss-reduction measures. Homeowners could be offered a long-term home improvement loan, tied to the property, to pay for cost-effective ways to mitigate future losses, such as elevating the house or moving utilities to a higher floor, so that the annual cost of the loan, paid all or in part by vouchers or tax credits, would be less than their savings from the reduced risk-based premium. This proposal is not only fair but also encourages property owners to reduce future losses from inevitable disasters. It also avoids using taxpayer dollars to assist uninsured and unprotected victims from hurricanes and floods who will demand and may receive federal disaster relief. See also: How to Make Flood Insurance Affordable   In summary, the proposed flood and health insurance programs should be designed with reasonable premiums for high-risk individuals so they will want to purchase coverage that protects them against catastrophic financial losses. At the same time, one needs to be concerned about not discouraging low-risk individuals from purchasing insurance by imposing the subsidy burden on them alone through premiums much higher than their risk rather than on the general population through a broad-based tax. By considering the issue of fairness as an important criterion in designing these programs, we will have taken a major step in enabling high-risk individuals to have coverage while at the same time maintaining the basic principles of insurance. Republished with permission from Knowledge@Wharton, the online research and business analysis journal of the Wharton School of the University of Pennsylvania.

After eight years of gains in stock markets and a nice pop following the election of a Republican president in the U.S. in November, an old friend of mine sounded a note of alarm in the Wall Street Journal this week that I think is worth noting—he was right in a big way before the internet bubble burst in 2000, and he's been my proverbial canary in the coal mine since then. Based on what he wrote, I think we should all confront a scenario where the Dow Jones Industrial Average tumbles 2,000 to 3,000 points and where the fallout spreads throughout the insurance industry, affecting not only client activities but also investment portfolios and even the valuations of insurtechs, as insulated as they might seem to be from the valuations of the Fortune 500.

Here is the article by Andy Kessler, who has been a friend since we became neighbors two decades ago. The WSJ has a pay wall, so the article won't be accessible to many, but it can be summarized briefly. The argument for alarm is essentially based on his experience both as a securities analyst on Wall Street and as a successful hedge fund manager in Silicon Valley. Andy writes:

"Are there any bells ringing now? How about a few months back when someone looked me in the eye and insisted—without cracking a smile—that Uber was a bargain at a $68 billion valuation? Or when, shades of AOL and Time Warner, Amazon bought Whole Foods for $13 billion—and then its stock went up by more than that amount? Or when Tesla missed its numbers again, and the stock rose anyway? Or when the price of a bitcoin, backed by nothing but the faith of devotees, hit $3,000, tripling over a year? Or when Hertz stock rose 14% on news of a deal with Apple for a self-driving car that is still vaporware?"

The article briefly cites his successful call in 1999 about the coming market collapse. He tells the story in more detail in his entertaining 2005 book, "Running Money: Hedge Fund Honchos, Monster Markets and My Hunt for the Big Score." The story goes like this:

He and his partner spent years trying to raise money for a hedge fund but were mostly frustrated by a Catch-22: If you had money, people would give you more, but if you didn't have money then you couldn't raise any. Andy and his partner finally raised enough money to be on the map and had one of the best years of any fund in 1998, according to public rankings. People started throwing money at them. In late 1999, a group asked to have breakfast around the corner from their office in Palo Alto, CA, and it was a memorable scene.

A stretch limo pulled up outside the restaurant. Huge bodyguards piled out. Two Middle Eastern investors quickly dispensed with the chit chat and said they wanted to wire $500 million into Andy's back account the following morning. Andy says he started calculating: The 2% carry, alone, would be worth $10 million a year to him and his partner, Fred, who operated out of a tiny office with just one assistant. That didn't even account for the 20% of any profits they would earn. Then Andy realized that Fred was turning down the money, because they wouldn't know what to do with it. Andy says he tried to kick Fred under the table but missed, and finally acquiesced. 

Only days later, the scene repeated itself. Another stretch limo. More bodyguards. Another pair of Middle Eastern investors. Another quick offer of $500 million. (Andy says he wondered whether $500 million was a unit of currency in the Middle East that he wasn't familiar with.) This time, Andy found himself turning down the money, because there weren't enough good places out there to invest it. On the short walk to their office, Andy and Fred decided that, just because they had turned down $1 billion didn't mean it wouldn't find its way into the market and add to the already unrealistic valuations. They decided that they should get out of the market, not take on new money. They did—at the crazy valuations still possible in late 1999 and early 2000, before the crash began in April 2000. 

So, when Andy calls the top of a market, I listen. I think you should, too. His piece doesn't mean the market will crash tomorrow. Or ever, in fact. The stock market operates at its own beat—during my days at the Wall Street Journal, a reporter threw darts at a dartboard quarterly and generally did just as well as the experts in predicting stocks. But it's worth remembering that stocks don't just go up. They can go down, too. And we seem to be in a frothy market where a relatively small shift in sentiment could have major implications. As long as we, as an industry, are the experts in risk management, now feels like a good time to think about the risks we'd face from a major downturn in the stock market.

Any downturn won't affect the fundamental changes happening in insurance. Disruption will continue apace. But contemplating a stumble in the stock market is an exercise I'd recommend. 

Cheers,

Paul Carroll,
Editor-in-Chief

Away from the noise in Washington, there’s a quiet movement to improve healthcare and lower costs, and it’s making progress. The movement is led by employers and other large purchasers of health benefits. This is the third in my periodic profiles of some of the best strategies in the private sector. One of the most promising innovations I’ve seen in healthcare does not come from Silicon Valley or an Ivy League incubator, but from the plain soil of practical Arkansas, birthplace of the world’s largest retailer. Walmart takes seriously its responsibility for stewarding the benefits it offers its more than 1.3 million U.S. employees and their dependents. I first heard about Walmart’s leadership from their former global benefits leader Tom Emerick, whose book Cracking Health Costs (written with Al Lewis) describes “Company-Sponsored Centers of Excellence (CSOEs),” a handful of hospitals Walmart picks for employees and their families whose doctors have diagnosed them with certain conditions and recommend surgery. While employees can always remain with the hospital of their own choosing, Walmart will pay all copays and travel expense for the patient and a companion if the patient consults with one of the centers of excellence. See also: Walmart’s Approach to Health Insurance   Emerick started the program by targeting one of the most invasive and risky procedures offered in hospitals--transplants. He selected world-class hospitals as centers of excellence, including big names like Cleveland Clinic. If an employee or covered family member is told by the doctor that he or she needs a transplant, the employee is eligible to visit a center of excellence, where a team of physicians examine the patient, recommend a treatment and, if necessary, do the surgery. What happened next astonished Emerick. As he explains in his book, “About 40% of covered plan enrollees were originally told they needed a transplant but were discovered to not need a transplant when sent to the top clinics in the United States.” Avoiding a transplant saves money, but, more importantly, it saves endless heartache and suffering for those patients able to find less invasive alternatives. A transplant is one of the most painful and difficult surgeries imaginable, and requires a lifetime of medical follow-up, including strong medications, many with serious side effects. Emerick’s successor at Walmart, Sally Welborn, expanded the CSCOE model to cover orthopedic procedures for knee, hip and spine, as well as certain common cancer diagnoses. She added a bold twist to the program: Along with her senior director Lisa Woods and the Walmart team, she negotiated a deal that upended the usual way healthcare does business. Each center of excellence signed two contracts: first, accepting a bundled payment for a treatment recommendation, and second, another capped bundled payment covering all aspects of the procedure. These were not the usual fee-for-service contracts. Instead, Walmart aligned the hospital’s financial incentives with the patient’s best interests. That sounds like common sense, but in healthcare common sense is the exception, and the deal is a breakthrough. Traditionally, in fee-for-service, hospitals are reimbursed for everything they do, regardless of whether the work helps or harms the patient. But with bundled payments, the hospital gets paid for accomplishing what the patient needs and wants. Like Emerick, Welborn was surprised by the results. About a third of the time, medical teams did not recommend the procedure the patient had been referred for. As many as half of those recommended for the cancer center of excellence had been misdiagnosed. Sally is leaving Walmart in July, and she departs with a powerful legacy. In addition to this program and some other innovative initiatives, she’s spread lessons learned throughout the employer community. She worked with Pacific Business Group on Health, for instance, to bring together other employers to launch their own centers of excellence programs, building on the Walmart model so they don’t reinvent the process from scratch. See also: Walmart Shows Way on Health Benefits   Scaled nationally, programs like Walmart’s have vast potential. Officials at the agency that funds Medicare have been developing bundled payment trials over the past few years. It remains to be seen whether deals like this from the private sector influence the new administration. But the need is urgent. A blue ribbon consensus panel at what used to be called the Institute of Medicine estimated that about a third of all health costs are wasted each year, often on inappropriate, unneeded procedures and errors. Those wasted dollars are enough to fund all of Medicare, Medicaid, CHIP and Obamacare subsidies, with a little left over to cover NIH or CDC, as well. In an era of frustration and fear over health care reform, Arkansas offers a promising moonshot worth watching. Congress, take note.

Despite a decade of prominence, the Age of the App may be over. The future of auto claims could belong to the chatbots. Equipped with AI and machine learning capabilities, these computer software programs can conduct natural language-like conversations with customers in real time. Already, Amazon’s Alexa and Apple’s Siri are working as personal assistants and shoppers, while others serve as bankers, officer managers, HR administrators, concierges and more. And it won’t be long before chatbots quickly expand throughout the insurance sector. They are already starting. Compared With Chatbots, Apps Are a Nuisance Because the insurance industry is traditionally slow to adopt new technology, apps are still considered “cutting-edge” by many insurance carriers. Compared with chatbots, though, mobile self-service apps may shortly be seen as the customer-service equivalent of a horse and buggy. According to Gartner, 20% of all brands will abandon their mobile apps by 2019. By contrast, Gartner forecasts that, by 2020, AI bots will power 85% of all customer service interactions. What’s behind this warp-speed transition from apps to bots? Speed, convenience and user-friendliness. See also: Much Higher Bar for Customer Service   While mobile self-service apps do represent a great leap forward for some policyholders, even those who love them were never thrilled about the time and patience required to download and install them and learn to use them. And many people have grown weary of their cell phone real estate being occupied by one-time apps. For every 10 apps downloaded by consumers, seven are uninstalled after just two weeks without ever being used. Interacting with a chatbot involves no user’s manual. Customers can message (24/7) to converse with an intelligent chatbot that, for all practical purposes, behaves like a human – one fully equipped to handle all their auto insurance concerns. In fact, chatbot-powered customer service could be even better than the “traditional” variety for mundane questions. For example, customers will no longer have to endure a menu of phone prompts before they’re connected with the appropriate person. Instead, the bot will be able to answer most questions or guide them through the steps needed to achieve the desired outcome in the format we’ve become accustomed to, text messaging. Improving the Customer Experience Imagine a self-service claim in which the vehicle owner interacts with a chatbot. The customer starts by verifying his identity and is then orally or text-guided through a series of steps to complete the entire process. The chatbot asks questions. The customer answers. The customer submits photos or videos of the damaged vehicle, and the chatbot either responds with additional questions or walks the policyholder through the next steps. Once the process is finished, the bot transmits the details of the transaction to the carrier, which determines the right outcome for the claim – e.g., whether an estimate needs to be written by a human, through an AI photo estimating solution or through having the owner bring the car to a repair facility. At some point, policyholders will even receive auto claim payments through the chatbot, further streamlining the claims process. This is already happening in some areas of insurance. And because chatbots can learn and acquire more knowledge with every transaction, they will make the customer experience better as they continually collect and process vast amounts of data. For customers, dealing with a chatbot for assessing vehicle damage will be like having an appraisal assistant standing right next to them. Of course, many people will realize that they are not, in fact, talking with another person, but communications will be so seamless and natural that they may eventually forget this. For insurers, chatbots will lower costs by allowing companies to replace many customer service personnel. For example, customers have a tendency to call their insurers multiple times to inquire about their claims and ask basic questions. Such interactions could be easily automated using a chatbot. See also: Hate Buying? Chatbots Can Help   Incorporating Chatbots into the Claims Department While chatbots have many applications, by no means is technology the right solution in every customer service interaction. There are many times when the human factor is far superior. Chatbots are one more tool in the toolbox. Here are two smart uses for them in a claims department: 1. Guiding customers, step-by-step, through the claims process using structured questions and answers. For example, if you want a vehicle owner to complete a mobile self-service claim, you could employ a chatbot to guide them through the verification process, as well as the submission of photos/videos and other documentation of the damage. Once this is done, the bot might transmit the claim to your company and an auto repair facility. An added benefit is that you will be collecting lots of data to help process not just this one claim but to enhance the customer service experience on all future claims. 2. Answering an array of FAQs submitted by policyholders – FAQs for which carriers currently deploy vast CS resources. Creating a human-like experience for managing thousands of customer inquiries could dramatically lower your customer service costs. Ironically, the biggest benefit of chatbots is enhancing the customer experience by providing services that are faster and more personalized – a machine-made level of personalization. So while apps still have a place in the insurance industry – for now – it’s likely that some of them will be out of a job, thanks to the rise of the chatbot.

Bringing change within any organization is hard to achieve. Arguably, the larger the company, the more complex and difficult the problem is. Add to that geographic and cultural differences, and the waters are muddied further. Change encounters roadblocks. From the reticence of employees to change their working practices, to the difficulty of getting boardroom support on new market opportunities or ideas developed… change is challenging. So why should we persevere?  Because it is a matter of being relevant and competitive…and even ensuring survival. See also: Change Accelerates in Core Systems   With the rapidly evolving and disruptive business environment due to changes in people, technology and market boundaries, the requirement to alter insurers’ internal and external engagement operational procedures has never been more pressing. Most of us are familiar with the adage: “When change meets culture, culture invariably wins.”  Perfect. When change doesn’t materialize or happen quickly, we can blame the lack of dynamism/imagination in the company, workforce or (laughably) our customer base. For those working in or managing large, dispersed workforces, conveying a new idea is difficult at times, and bringing new ideas through takes time to get the full “buy-in” that one would ideally wish.  However, during the last five to eight years there has been a significant shift in where the balance of blame lies. Yes, it’s hard to win people over initially. But they do come over eventually. It’s frankly impossible if the core business systems are not up to the task. Core business systems can become the wall of resistance. There is a seismic change in the market dynamics, both internally and externally, in how we must engage prospects and customers. Prior to about 2000, most employees, prospects and customers were, at best, technology novices. The advent of the internet and the rise of e-business, coupled with the introduction of the smartphone, iPad and other innovative devices, rapidly altered the landscape forever, creating a new generation of digitally enabled individuals. Whether by adapting to digital technologies or being “born digital,” we entered a new age of insurance that is underpinned by modern, emerging technologies. In this new digital age, everyone has access to digital technology in his or her everyday personal lives. Yet, for many, work life is a “trip back in time” due to old and frankly outdated systems. Green code-driven screens may have, for the most part, been replaced with graphical interfaces, but core systems are typically very long in the tooth and do not reflect the art of the possible. But replacing these legacy systems is challenging. The insurance CIO bemoans the fact that requested work stretches out years into the future, keeping maintenance of legacy systems front and center; with the future vision no more than a vague dream. It is a major problem that cannot be solved as we did in the past, when we simply shifted more resources to maintain legacy systems. The insurance industry, as a rule, is miles behind providing capabilities or convenience like an Amazon, Uber, various travel sites and even (heaven forbid) most banks. Although there are differences in the products and the engagement lifecycle, customer expectations see no boundaries and expect the same “Amazon” experience from insurers. See also: Getting Culture Right: It Starts at the Top   In today’s digital age, technology drives and underpins every organization. If change is to be brought about, the CIO must lead the way and provide the requisite business and technology platform that is the foundation for a rapidly changing future. Unless the CIO is released from trying to maintain and enhance tired non-conforming legacy systems, which consume a high percentage of both people and investment resources, it’s hard to see how insurers will ever catch up, let alone get ahead of the game. It’s no longer just culture standing in the way of change. It’s legacy core business systems, as well. The disruption and changes that are reshaping industries, and the businesses within them, are creating unprecedented growth opportunities for insurers who can capture the opportunities in terms of new risks, new markets, new customers and the demand for new products and services. Cloud-first business solutions are the foundation for these insurers. They fit the fast-paced world where a new generation of startups, product launches and expansion into new market segments is creating a new age of insurance. This article was written by Mike Smart and originally appeared on Majesco.com.

I don't ordinarily blog about my opinions, but permit me to depart from tradition today. I recently received a phone call from an IIABNY member (an agent whom I will keep anonymous) that still bothers me. The agent told me that he had a homeowners insurance policy covering a husband and wife. Recently, the husband died. At the widow's request, the agency sent a change request to the insurance company (which will also remain anonymous), asking it to remove the deceased husband's name from the policy. The company issued an endorsement to the policy, along with a bill for an additional $26 in premium. Like any good agent, our member called the company to ask why the widow was being charged $26 for taking her late husband's name off the policy. The answer: The company ran a check on her credit score and found that it was not as good as her husband's. Under the company's pricing system, this knowledge generated a higher premium. See also: Healthcare Needs a Data Checkup   This insurance company charged a new widow $26 because she was more of a credit risk now that her husband was gone. Please take a moment to reflect on the coldness of that decision. Now, I understand how this probably happened: The request came in, the insurer's computer system automatically ran a credit check, read the new score and issued the endorsement/bill. Insurance companies, which like to moan and groan about how auto insurance has become a commodity, now treat it like a commodity that comes off a production line with as little human involvement as possible. This process is more efficient than having underwriters review most accounts. The process also produces atrocious outcomes like this one. The American public does not have a high opinion of the insurance industry. People we interact with may like us individually, but they think our industry as a whole is a parasite, sucking gobs of ill-gained money from the economy. And why do they think that way? Because insurers pull crap like this. There are so many good people in the insurance industry. You and I meet them every day — agents and brokers who spend hours lining up quotes for appropriate coverage at fair prices. Claims people who work 16-hour days for weeks after a natural disaster, trying to get claim checks out to their insureds as fast as possible. Underwriters who struggle to arrive at prices high enough to please their employers and low enough to please their agents. Loss control engineers who spend long hours with clients to make workplaces safer. Thousands of people who show up for work every morning wanting to earn their paychecks fairly and who do the right thing for their customers. I could go on and on. And all that effort and all those good intentions get washed away in the public's mind when an insurer pulls an insensitive, stupid act like this. If this were an isolated incident, we could explain it away, but we all know that it's not. Things like this happen all too frequently. No doubt the insurer's employees will say that the system did it. Maybe so. You know what? I don't care. People program computer systems. People can override them. People who are paying attention can stop something like this from going out the door in the first place. Or they can charge a woman $26 because her husband died. If it were you, which action would you like to go home and tell your family about? See also: A Way to Reduce Healthcare Costs   The IIABNY member who called me asked me to research New York insurance law to see if there is any basis for telling the insurer that this action was illegal. I truly hope I find one. The agent did not tell the woman why her premium went up, but she paid it. I guess she felt it was the right thing to do. Too bad her trusted insurance company doesn't have that same sense of honor.

Before "insurtech" becomes the next over-used buzz-phrase to hate, let's step back for a moment and consider the truly unprecedented scope of opportunity for growth facing those in the various risk management sectors who embrace the inevitable reinvention of this trillion-dollar industry. As the whirlwind of start-ups and innovation occurring across insurance business models evolved into viral global gold rush, many existing insurers and VCs still struggle with how to participate. Many who understand the reality of disruption as a means of growth struggle even more with the most basic questions:

• Where do we start?
• Do we have the expertise?
• How can we pick the best among the thousands of startups and "smart-ups?"

Most of the established firms I coach are consistently surprised by two lessons learned that have been captured at some point after working through these key strategic questions. First, they are surprised at the ease with which they were able to answer the one question that can be truly paralyzing: "Where do we start?" Second, they often voice relief at how easily the rest of the core, up-front answers seem to just fall into place. These experiences can be distilled down to a rather straightforward single question: "How do we get unstuck?" See also: Insurtech and the Law of Large Numbers   Two timeless bits of wisdom can provide the first steps toward converting chaos into actionable clarity:

1. A picture is worth a thousand words. Frameworks and models do help create clarity.
2. A little education goes a long way. This is code for: check as many assumptions as possible at the door and ask, "What if..?"

Here are some pictures that can be useful: [caption id="attachment_26765" align="aligncenter" width="500"] Source: Startupbootcamp, what is an insurtech? [Infographic], 2015[/caption] [caption id="attachment_26766" align="aligncenter" width="297"] The “4 Ps” model from Matteo Carbone and the Insurance Observatory[/caption] Insurtech Landscape by AGC Partners All three frameworks for understanding insurtechs are solid models by which an audience, subscriber group or client company can gain greater insights. But insurance companies, venture capitalists and regulators need to understand how to use them. The insurtechs in these models represent but the center of a much larger landscape of forces requiring consideration if you want to be an insurer that defines the rules that all others will have to follow. The reinvention of insurance is simultaneously happening from the inside-out (insurtechs) as well as from the outside-in (exponential technologies). In other words, insurtechs are revolutionizing HOW insurers will manage risk and consumers. Exponential technologies will fundamentally redefine the WHAT—i.e., the very risks that insurers manage. Now, this raises an important question: How do we define these larger external forces? One organization influencing many of these breakthrough, or exponential, technologies is Singularity University in Sunnyvale, CA. Singularity U coined the phrase "10^(9)” Opportunities." These are opportunities to leverage a technological capability, or domain, to improve 1 billion lives (9 zeros) within a single decade. Some may question whether this vernacular is more aspirational than attainable. But among the best-kept secrets in the insurance industry is the reality that exponential markets waiting to be discovered outnumber those currently being addressed by existing insurance product lines. So, here is a possible goal: "By year-end 2027, we will have grown by improving the lives of 1 billion or more people by creating products that leverage the technological application of___________________." Incumbent insurers must understand how these converging forces relate to discover clarity and scalable growth. A short list of essential questions leading to viral growth strategies needs to include: Which insurtechs will feed my strategy to grow _________ opportunities? These types of questions can map the insurtechs within the industry and near term to the longer-term, much broader landscape of opportunities. Clarity of these exponential forces—then mapped back to the products, services, and new business models among insurtechs—will open the door to achieving four significant deliverables:

1. Improve the solicitation, selection and vetting of new ideas generated internally and collaboratively;
2. Improve the returns on early-stage investments;
3. Improve the vision, focus and identification of M&A opportunities;
4. Improve the expectations and returns on new products and services developed and launch by internal innovation teams.

The world outside of insurance looks into this industry with skepticism with respect to innovation. What is so often misunderstood is that three of the most significant societal shifts of the past 200-plus years were essentially enabled by insurance innovation: homeownership in the late 18^th century, the viral adoption of the car and advances in medical treatments as an outgrowth of adoption of health insurance. The DNA for exponential innovation resides within this industry. Seeing insurtechs as a means to fulfill a longer-term innovation strategy is where the opportunities are being discovered by those who will lead this industry for decades to comes. See also: Insurtech Is an Epic Climb: Can You Do It?   To provide feedback, ask for additional information or learn how to apply these concepts, contact Guy Fraker, guy@insurancethoughtleadership.com. Do you want to follow Guy Fraker's commentary and insights, and be notified as new posts are added?

The goal of artificial intelligence (AI) for an enterprise is to streamline business processes and improve customer experience to drive positive bottom-line results. It’s about moving enterprises into the on-demand economy by finding that magical balance of increasing customer satisfaction while reducing costs. But artificial intelligence is no silver bullet that works on its own. It’s an integral piece in a broader end-to-end solution that combines the best of technology with the learned behaviors of skilled humans. And the challenge of enterprise AI is finding a solution or approach that provides measurable results. There’s so much hype around artificial intelligence that it’s easy for enterprises to get lost amid the buzz. Many enterprises acknowledge they need to do something with AI, but they don’t know exactly what. This usually results in businesses deep diving into large-scale AI and automation programs without a thorough strategy for success. This approach is costly and relies on the artificial intelligence to learn, grow and perform the required business processes instantaneously. But, unfortunately, we’re not yet at the stage where AI is advanced enough to perform in such a way. What’s needed is a totally different approach that doesn’t place all the burden on the technology to work miracles and automate complex business processes upon launch. Enter the pragmatic approach to AI. Pragmatic AI Pragmatic AI leverages a systematic implementation that gradually increases automation and machine learning. In the context of enterprise implementation, there are three phases to Pragmatic AI. At the end of these three phases, the goal is to have an artificial intelligence program that learns and develops on its own. However, before we get to that stage, we must focus on highly repeatable business processes that can easily be automated. It’s important to note that pragmatic AI fits within a larger digital transformation strategy. AI is by no means a silver bullet that solves all organizational problems on its own. Rather, it augments processes and complements technology that are already in place across the organization. Contrary to the beliefs of many industry pundits, AI is still not advanced enough to work on its own. It needs human management, guiding and careful development. See also: Strategist’s Guide to Artificial Intelligence   “Long Tail” and “Fat Tail” Processes Central to Pragmatic AI is the delineation between “fat tail” and “long tail” processes. Processes that are generic, repetitive and common are classified as fat tail processes. Examples include basic customer service inquiries (technical assistance, account updates, etc.) or bill processing. In contrast, long tail processes are less frequent and require a high-degree of customization to resolve. The foundation of pragmatic AI is focusing first on solving the fat tail processes before progressing to the complex long tail issues. The 3 Phases of Pragmatic AI Phase 1: Automate Repetitive Processes The first phase of Pragmatic AI is analyzing all the fat tail processes and identifying those that can be easily automated by deploying an AI program. The benefit of starting with these fat tail processes is that there is already a vast amount of data available to leverage for faster engineering. This data means there is less need for the program to “learn” on its own. Instead, it’s programmed, or “taught,” with specific business processes in the development phase so that it's already functional upon deployment. Phase 1 includes a combination of Natural Language Processing (NLP) with guided user journeys. Consider that fat tail accounts for nearly 80% of customer inquiries, meaning the vast majority of inquiries are repetitive and highly common. With this in mind, you can get a sense of the cost reductions and the potential for bottom-line efficiencies when this fat tail of inquiries is automated. All the while, live agents and operators can still be used for the remaining 20% of customer inquiries, the infrequent long tail processes and a safety net for the AI. With this combination of AI and live agents, enterprises can enjoy the benefits of having always-on customer support without the additional cost of resources, thus delivering a responsive, on-demand and highly effective customer experience that drives satisfaction. Phase 1 of Pragmatic AI is often sufficient for both small- to medium-sized businesses and large organizations. The significant cost reductions and increases in customer satisfaction can provide significant ROI. Phases 2 and 3 expand the automation and include greater sophistication and more complex machine learning. Phase 2: Add Advanced Cognitive Services With AI already implemented to manage the repetitive, high-volume processes, Phase 2 moves further down the tail, addressing more specific processes. More advanced cognitive services are implemented to augment and widen AI’s capacity by analyzing the interactions and identifying patterns to be replicated. These additional services include language translation, image processing and video processing. Key to success in Phase 2 is the use of analytics to improve the automated processes established earlier. Improvements are made to failure points — i.e. when a bot has to transfer to a live agent for resolution — and fixed to increase the bot’s success rate. Gradually, the AI’s capacity to solve complex problems grows, increasing the utility for the end-user. In addition, NLP is improved to provide more freedom for people to interact with the bot using natural language. Phase 3: Building the Framework for Machine Learning The final stage of pragmatic AI is enabling an element of machine learning and growth. Leveraging a combination of cognitive services and pre-programmed business processes, the AI-powered bots learn from their interactions and adjust flows under the supervision of human operators. The machine learning is used to improve existing processes or to train the machine regarding new processes that are currently being managed by humans. Again, NLP is increased, allowing the bot to comprehend and process a wider degree of words and terms. At this point, the AI should be at a level of sophistication that the need to switch to live agents is less often. Throughout the three phases, the majority of failure points have been addressed and used to train the AI. The three-phase approach to pragmatic AI allows automation to be developed and deployed using a strategic process that’s unique to an organization. Each phase directly addresses specific challenges within an organization. See also: Robots and AI—It’s Just the Beginning   Why Pragmatic AI? Currently, there’s a gap between what enterprises expect of AI and what the AI can actually do. Instead of letting this gap drive costs higher through ill-fated AI programs, enterprises need to adopt a practical approach. The journey to enterprise AI is about pursuing what’s practical with clear ROI and readily available now and then building upon this foundation with large-scale, sophisticated automation and machine learning programs. Pragmatic AI’s strength is that it is embedded and grows from current business processes and that it can immediately deliver a positive ROI by increasing customer satisfaction while reducing costs. With these kinds of measurable results, AI programs move from a place of aspiration to an actionable strategy — and finally to a readily deployable solution.

In an April 14 LinkedIn Pulse post, I quoted an excerpt from Seth Godin’s blog that was related to the issue of online insurance buying. I got so much response to that LinkedIn posting excerpt that I asked, and received, Seth’s permission to reprint it here in its entirety. You’ll find it below. More recently, he blogged about “When Time Catches Up.” Here is an excerpt from that post: Bad decisions happen for one of two reasons:

1. You’re in a huge hurry, and you can’t process all the incoming properly. But more common…
2. The repercussions of your decision won’t happen for months or years. This is why we don’t save for retirement, don’t pay attention to long-term environmental issues and, tragically, tolerate (or fall prey to) irrational rants about things like vaccines. It might be engaging or soothing to promote a palliative idea now, but years later, when innocent kids are sick and dying, the regrets are real.

A bad decision isn’t only bad because we’re uninformed or dumb. It can be bad because we are swayed by short-term comfort and ignore long-term implications. A bad decision feels good in the short run, the heartfelt decision of someone who means well. But there’s a gap when we get to the long run. This is related to what many of the insurtech start-ups refer to as the “customer experience.” Their solution for what can be a painful process (purchasing insurance) is to just reduce it to a phone app with a two- to three-minute processing time. The problem is, as Seth puts it, we are often swayed by short-term comfort and ignore long-term implications. As an insurance professional, your responsibility is to educate consumers that shortcuts like this can result in financial disaster if they do not take the time to ascertain their exposures to loss and address them. See also: Smart Things and the Customer Experience   Seth characterizes himself as someone who “writes about the post-industrial revolution, the way ideas spread, marketing, quitting, leadership and most of all, changing everything.” I find that much of what he blogs about can be applied to our industry. If you don’t subscribe to Seth’s daily blog, I encourage you to do so. It is almost always interesting and often very insightful. Now, on with the original blog post I mentioned at the start above…. ‘Sort by price’ is lazy, by Seth Godin Sort by price is the dominant way that shopping online now happens. The cheapest airline ticket or widget or freelancer comes up first, and most people click. It’s a great shortcut for a programmer, of course, because the price is a number, and it’s easy to sort. Alphabetical could work even more easily, but it seems less relevant (especially if you’re a fan of Zappos or Zima). The problem: Just because it’s easy doesn’t mean it’s as useful as it appears. It’s lazy for the consumer. If you can’t take the time to learn about your options, about quality, about side effects, then it seems like buying the cheapest is the way to go–they’re all the same anyway, we think. And it’s easy for the producer. Nothing is easier to improve than price. It takes no nuance, no long-term thinking, no concern about externalities. Just become more brutal with your suppliers and customers, and cut every corner you can. And then blame the system. The merchandisers and buyers at Wal-Mart were lazy. They didn’t have to spend much time figuring out if something was better, they were merely focused on price, regardless of what it cost their community in the long run. We’re part of that system, and if we’re not happy with the way we’re treated, we ought to think about the system we’ve permitted to drive those changes. What would happen if we insisted on ‘sort by delight’ instead? What if the airline search engines returned results sorted by a (certainly difficult) score that combined travel time, aircraft quality, reliability, customer service, price and a few other factors? How would that change the experience of flying? This extends far beyond air travel. We understand that it makes no sense to hire someone merely because they charge the cheapest wage. That we shouldn’t pick a book or a movie or a restaurant simply because it costs the least. There are differences, and, sometimes, those differences are worth what they cost. See also: Key Trends in Innovation (Part 3)   ‘Worth it’ is a fine goal. What if, before we rushed to sort at all, we decided what was worth sorting for? Low price is the last refuge of the marketer who doesn’t care enough to build something worth paying for. In your experience, how often is the cheapest choice the best choice?

More than ever, chief security officers are being held accountable for keeping their businesses safe. Phishing attacks, data breaches, ransomware and the ever-increasing access by employees to technology and data are driving this accountability. But there’s only so much that technology solutions can do to protect against threats. What else should organizations do? It turns out that most breaches are the result of an employee mistake, so looking to their staff as their first line of protection is a critical success factor today. Security awareness training is now recognized as one of the critical components of a robust security architecture. But are employees getting the security awareness training they need and deserve? Unfortunately not. Too many organizations still choose to provide no security awareness training at all, or simply provide annual PowerPoint-based training program, or training that is dry and difficult to understand. See also: Quest for Reliable Cyber Security   Employees often think they’re prepared or think, “That’ll never happen to me” — until it does. Then the employee often is too ashamed to go to a boss or IT department after an incident occurs. Traditional training doesn’t work The information and best practices the employee received from training were never understood, didn’t seem relevant or just didn’t come back to him. What happened? Cyber attacks aren’t changing every five years — it’s more like every five months. Organizations can’t afford to fall behind on security training. Employees must be armed with the knowledge and skills to protect themselves and their organizations. Traditional, outdated training does little to prepare workers for the deluge of cyber attacks they face or the risks they create for themselves. There are ways to make a change in the workplace. Instead of training employees as passive observers, make training interactive and teach actionable, real-world skills. Recognize that hacks happen Instead of instilling a mindset that an incident must never happen, give employees the confidence to speak up, even if they make a mistake. Instead of focusing solely on security, focus on learning, too. Make training brief, fun and sticky so that it is always top-of-mind when needed. Instead of focusing on a single type of risk, prepare employees for the range of security threats they’ll face, whether from an external cyber attack or from their own use of technology or access to data. See also: Cybersecurity: Firms Are Just Sloppy   Hacks can happen even if the staff practices security procedures. Look at the victims of the Twitter Counter breach. No actual Twitter accounts were hacked, but a third-party application was, and the hackers left unnerving tweets on organizations’ accounts. Employees should be prepared for events like this. Practicing real-world scenarios can help prepare for the worst-case events. Training needs to keep up with the technology that employees are using and the risks they face. It’s time to stop using outdated training techniques and for organizations to invest in their employees and assets by providing security training that will make a difference and change the behavior of its staff. They can’t afford not to. This article originally appeared on ThirdCertainty. It was written by Marie White.