Nature has taught us that climate and environment dictate ecology. When the right set of conditions come along, nature presents the opportunity for something unique to appear and take root in the world. Consider the platypus, a semiaquatic egg-laying, duck-billed mammal with the tail of a beaver. Its mere existence defied all conventional scientific wisdom concerning mammals when it was discovered in the 18th century. Yet, the platypus was a perfect adaptation for its climate and environment, where it had quietly thrived for thousands of years. Thanks to a confluence of circumstances back in the 1970s, the insurance industry experienced its own change in climate and environment: a hard insurance market characterized by higher costs and limited availability of coverages. Governmental agencies were hit particularly hard by the loss of available insurance markets. As insurance options shrunk, so did the public services that relied on them, forcing public entities to reconsider their risk management strategies to survive and evolve. The Darwinian outcome was something that looked and felt familiar in the world of insurance risk, but on closer inspection is found to be quite inimitable, and perfectly adapted to the new climate and environment. This was the dawn of the public risk-sharing pools. See also: How to Build ‘Cities of the Future’   Since that time, public risk-sharing pools (aka joint power authorities, or JPAs, and joint insurance funds, or JIFs) have been growing in their breadth and scope of operations. As a full-fledged risk management community unto themselves, these groups operate in unorthodox ways, combining multi-peril commercial lines insurance options for constituents across a variety of public entities, such as police, fire, transportation, city, special districts, county and state agencies. The variety and types of public risk pools are as numerous as are their distinctions in risk-sharing approaches, lines of coverage, underwriting methodologies and types of risks. This national network of public risk-sharing pools has emerged to create a unique ecosystem all their own. Today, more than 85% of the 87,000-plus government entities in the U.S. belong to a public risk-sharing pool. By their nature, this unusual self-insurance arrangement is under scrutiny by regulatory bodies, and, while they are not known to become insolvent, JPAs face constant actuarial challenges tied to pricing risk accurately and efficiently for their public entity members. This underserved group of non-policy insurers is challenged with budget pressures, legislative initiatives, staffing issues, changes in elected or appointed leadership and outdated systems that restrict efficiency of operations. Consequently, the average JPA struggles to deal with the layers of complexities inherent in the make-up of their particular realm. While many public risk pools labor to keep up with an ever-changing world of risk and politics, others are finding ease and opportunity in their operation by embracing new technologies and new methods of managing risk that work within the limited resource environment of their world. Public risk pools, such as Golden State Risk Management Authority (GSRMA), Beta Fund, the Montana Association of Counties (MACo) and the Texas Political Subdivision Joint Self-Insured Insurance Fund, are recognized leaders in their respective domains. They all have figured out the secret of how to deliver value to their individual members while working within their limitations. One clue to their success becomes apparent when talking with them. They all seem to share a growth-mindset, meaning that they tend to focus on the possibilities rather than the obstacles. Phrases like, “We can't,” “I wish I could,” “I don't have the resources,” or “It's never be done before” don’t tend to show up in their conversations. The people in these organizations are forward thinkers, innovators and early adopters of new ideas. For example, GSRMA, which has more than 258 member public agencies, such as cemetery districts, special districts (water, sewer and lighting), fire and school districts, counties and cities throughout the California, offers a full line of programs to cover the many exposures of its public entity members. During the Great Recession of the late 2000s, GSRMA recognized the need to create an internal infrastructure that can withstand the uncertainty of national or global events and protect its membership. As a result, GSRMA became an early adopter of cloud-based technology that was agile, robust in its enterprise offerings and easy on the budget. Not only did the investment in technology give them a workforce multiplier, it also gave them a process accelerator that saved them thousands of labor hours in the completion of seasonal and annual work-tasks. And because GSRMA retains a large amount of risk, it requires the ability to scale, underwrite with precision and respond quickly to members’ varied requirements. Equally important, like many JPAs, GSRMA must focus on budgeting/funding, so affordable technology that supports staff in all these endeavors is the highest priority for their executive team. It’s no mystery that GSRMA is experiencing success and has been “Accredited with Excellence” through the California Association of Joint Powers Authorities. See also: How to Outfox Our Brains About Risk   Against the backdrop of an uncertain economic climate, while living in the most political of environments, I believe the continuing success of public risk-sharing pools will largely be determined by their leadership’s mindset to embrace change, cultivate a smart staff and add supportive technology that serves that staff. Like GSRMA, MACo, Beta Fund and the Texas Political Subdivision, those with a future-proof plan will thrive in this complex climate and environment. Operating a public risk pool is no easy job by a long shot, and we should all take the time to thank them for their service.

A few weeks ago, I spoke to about 20 professionals attending a program about their future and the future of their organizations. I talked about tomorrow. They were more worried about today. I wanted to venture into tomorrow and look back to today. They just wanted to get through today. I discussed purpose: Why? They were more concerned about strategies and tactics: How? My metaphor was a blueprint. They wanted a to-do list. I was thinking effective (doing the right things). Their concern was efficient (doing things right). Leadership was my target. Management was their aim. I quoted Stephen Covey on leadership, “Begin with the end in mind,” because leaders focus on the horizon, a vision for the future. They were thinking management (“Begin with the beginning in mind"), because managers stare down at their desk, facing their challenges du jour and being constantly interrupted with issues about operations and people. THE MISTAKES WERE MINE! Not theirs. I misread my audience. I was there to discuss change management, to talk about solving problem and capitalizing on opportunities as we move from today through tomorrows. (Note the “s” on "tomorrows." You face a tomorrow every day – one at a time.) See also: The Entrepreneur as Leader and Manager   I should have realized that, as John Kotter put it, "management is still not leadership." He said: “In fact, management is a set of well-known processes, like planning, budgeting, structuring jobs, staffing jobs, measuring performance and problem-solving, which help an organization to predictably do what it knows how to do well. Management helps you to produce products and services as you have promised, of consistent quality, on budget, day after day, week after week. In organizations of any size and complexity, this is an enormously difficult task. We constantly underestimate how complex this task really is, especially if we are not in senior management jobs. So, management is crucial — but it's not leadership." He added: "Leadership is entirely different. It is associated with taking an organization into the future, finding opportunities that are coming at it faster and faster and successfully exploiting those opportunities. Leadership is about vision, about people buying in, about empowerment and, most of all, about producing useful change. Leadership is not about attributes; it's about behavior. And in an ever-faster-moving world, leadership is increasingly needed from more and more people, no matter where they are in a hierarchy. The notion that a few extraordinary people at the top can provide all the leadership needed today is ridiculous, and it's a recipe for failure.” Don’t repeat the mistakes I made with my audience. Be sure you know and understand the questions (both those being asked and those folks are afraid to ask) before you provide answers. Then make sure the answers you provide are correct and understood by the audience you serve. Communication is the negotiating of meaning. If the audience is not “catching” what you are “pitching” it might be well intended and thought provoking or ego or noise or a hope and a prayer but it is NOT COMMUNICATION! See also: The Need for Agile, Collaborative Leaders   As George Bernard Shaw stated so correctly, “The problem with communication is the illusion that it has occurred.” Are you providing the right answer to the right questions? If not, start again!

The word “digital” is most commonly associated with front-office transformation – client-facing activities, often in the service of acquiring business. This is for good reason, of course. Driven by their experience in other industries such as retail and banking, customers are demanding digital capabilities from their insurers, as well. Customers – individuals and companies both – expect that everything from access to information, to the ability to bind a policy, to initiating and managing a claim, to paying the bill should be easy to do and available digitally. Our consumer and SMB research reinforces this, indicating that net promoter scores (NPS) can swing 60-70 points when the entire journey is easy. With that in mind, I’m continuing on my promised theme of looking at all of the steps in the value chain to explore digital transformation across the customer journey. This month, I’ll take a look at billing and payments, an area that, at first glance, might not be an obvious choice for digital reinvention. But it is a great way to engage with customers, optimize a process that is often manual and present additional selling opportunities, as well. Not coincidentally, we also have a recently published thought leadership paper, The New (Digital) Face of Billing: Defining Multi-Line Insurance Billing Excellence, that takes a deeper look into digital billing. Thinking Beyond Transactions In my previous posts, I have talked about the need for a service mentality instead of the siloed, transaction-focused approach insurers have traditionally taken since the automation of business processes 50-plus years ago. To drive value from digital investments, insurers need to expand their thinking beyond transaction processing. Any interaction should be taken as an opportunity to develop and enhance the relationship with the customer, not as simply a means to an end. In other words, billing is not just about getting the premium paid, although that must be done efficiently and effectively. Billing is one of the rare opportunities insurers have to interact with their customers in a relatively benign situation (as opposed to the stressful, often contentious interactions associated with claims), and it must be embraced as such. See also: 4 Rules for Digital Transformation   This does not just mean cross- and up-sell, although that can be an element. Customers will be wary of this, particularly if done in a clunky way, particularly when offering a product that does not match the customer’s unique needs. The overall approach must expand from a basic indemnity mentality to one of service – and the billing approach must evolve beyond simply accepting a customer’s premium. It’s important to keep in mind that the customer engagement mentality is needed across all customer types – from individuals, to businesses, to agents, to third parties and other partners. The Customer Journey Digital transformation must always begin with mapping the customer journey. Identifying key touchpoints and “moments of truth” in billing is the first step to mapping interactions and defining the required capabilities. Journey mapping allows you to consider how to roll out capabilities incrementally, giving you the chance to experiment with different services for unique groups and to quickly see what works and what does not. Understanding your customers and their needs is key. Not every customer will benefit from an in-depth engagement at the time of billing. Some customers may be only interested in a hands-off billing experience, with, for example, a credit card being charged automatically on a monthly basis. Building an automated, paperless process for these customers is likely the right approach, while spending time and effort on building a deeper relationship may not result in a strong ROI. But even these customers can benefit from clear, natural-language explanations of such things as changes in their premium or renewal options. Other customers may benefit from a deeper interaction. The moment of truth for these users can be providing opportunities for them to lower their premium through product bundling or identification of local risk factors that they may be able to address. Although lowering premium payment may seem at first glance to be a negative, the improvement in customer engagement and satisfaction – with associated Net Promoter Score (NPS) – will more than pay for the difference. Still others may be interested in an interactive experience that doesn’t require them to speak with a human. AI and chatbots are becoming increasingly sophisticated in providing a human-like experience in a mobile setting, which can be a powerful way to prevent relatively costly calls into the call center as well as provide an engaging way to interact with customers. But only by taking the time to understand your customers through journey mapping will you be able to make the right investment decisions. And don’t just rely on your own experience – you need an outside-in perspective to do it right. End-to-End Journey The customer journey for billing does not end at billing. Billing is an enterprise process – it touches on many different parts of the business. For the advanced capabilities I’m highlighting to work, it may require a wider transformation to take place first. A 360-degree view of the customer – all of the policies, correspondences, claims, etc. – is needed to offer bundling options. Customer analytics will provide cross-sell options. Core system replacement may be needed to offer paperless processing. These are just a few examples. This is another reason why mapping the customer journey is key – it allows you to see where the process breakdowns and bottlenecks exist that need to be addressed to create an engaging customer experience. Our research shows that all generations (including the younger “digital natives”) use a variety of touchpoints for questions and service requests when it comes to billing. This is important to map in your customer journeys and important to build into your operating model – the people, processes and technology around billing that make it work. People may still want to pick up the phone and ask why their premium went up (our studies show at least 30% of calls are billing-related). But by providing clear information to customers around the billing process you can prevent a certain amount of those calls from coming through in the first place. Do It Right Billing is an opportunity to engage customers, but an occasional one at best. It is of primary importance to know how customers want to be billed and how they want to pay (electronically, with a paper check, via bank transfer, etc.) and how they will want to interact if they have a question or concern (self-service, call center, etc.). But the most fundamental need is to make sure the bills themselves are accurate. Cross-sell or risk management exposed through the billing process will not have much effect if the client is double-billed or if the payment was not correctly recorded. As Novarica sums up succinctly in a recent report The New Normal for P/C Insurers: 100 Data, Digital, and Core Capabilities, “errors can be costly.” And those errors are not only costly in the sense of having more people call into your call center, but also making it far less likely that those customers will become advocates. See also: 5 Cs of Transformation in Insurance   Mind the Gap In our thought leadership from earlier this year, Insurance in the Digital Age: Transforming from the Outside In, we mentioned the growing gap between customer expectation for digital services and the ability of insurers to provide them. Billing is a moment of truth for customers and a real engagement opportunity for insurers. While this makes it an excellent place to get started with your overall digital transformation, it is important to remember that you need to look at the end-to-end process as billing flows through many systems and data stores. This should not dissuade you from tackling billing, but don’t be surprised if there are some basic things that need to be done with the underlying technology (including considering retirement of old, inflexible core billing systems) and processes. It may seem intimidating, but the benefits in terms of longer-term cost savings, efficiency and customer engagement will be worth the effort … while bringing billing into the digital age.

Here is our second monthly list of "Six Startups to Watch," drawn from the more than 1,000 insurtechs we're now tracking at our Innovator's Edge site. They tackle some of the biggest issues facing insurers, and, while we all know that most startups fail, are unusually well-positioned for success, we believe. In the interests of variety, to make sure we expose you to an intriguing variety of startups, we don't repeat any of those we put on last month's list. 

Without further ado, we suggest you keep a close eye on:

Windward. The short description of this Tel Aviv company is: telematics for ships. There is a lot of ocean out there, and a lot of traffic on it, but there isn't always great information about what goes where. Sometimes, that is by design—ships will turn off their GPS trackers as they pass troubled areas, becoming what are known as "ghost ships." Well, if a ship registered in Iran goes dark as it spends a few days off the coast of Libya, then heads to a major population center such as London, an insurer might want to know that. It certainly would like to be sure that all relevant authorities can track any suspicious activity in this day and age. So, Windward pulls together a moment-by-moment history for each vessel that operates at sea, for use in insurance and a number of other industries.

In many ways, I've been waiting for Windward for a decade, since I met Mike Mullen at a conference where we both were speaking. Mullen was the chief naval officer for the United States at that point, soon to be appointed to the first of two terms as chairman of the Joint Chiefs of Staff, and we spent some time talking about a vision he had for a "1,000-ship navy." The U.S. has the world's biggest navy but doesn't come close to 1,000 ships—about 275 are in service—so Mullen was really talking about ways to coordinate the activities of most of the world's navies, to tackle problems like Somali pirates. More broadly, he was envisioning the sort of detailed mapping of ocean traffic that Windward is attempting. I wish it smooth sailing.

Ladder Life. The company has rethought life insurance from the ground up, to make the process simple and quick, to cut fees, etc.—basically to tackle all the problems that have made life insurance sales languish. It recently launched in its first market: California.

RiskGenius. The company uses artificial intelligence to analyze policies. It can spot coverage gaps, identify wording that has resulted in litigation and generally help insurers and brokers to find the best policy language to protect their interests.

Infinilytics. It provides analytics for handling claims, with two major benefits. Infinilytics fast tracks valid claims, removing frustration for customers during the process that insurers refer to as "the moment of truth." The analytics also spot questionable claims for more investigation.   

ViewSpection. This is a DIY digital inspection app that property owners can use to generate a complete tour as they apply for insurance, or that an agent can use. The app immediately gives underwriters the details they need, which removes the cost for an inspection and speeds the process, removing a frustration for the customer. (Yes, there is a theme here.)

RiskAdvisor. It provides a comprehensive risk profiling tool that brokers and insurers can use with corporate clients and prospects. The tool draws from a library of many thousands of possible questions to generate a list of risk issues, including enterprise risks, that are relevant to a company of that size, in that industry, in that geography, etc. 

I hope you find these insurtechs as intriguing as I do. If you are an insurance provider interested in what makes these companies worth noting, you should join Innovator's Edge for an in-depth look at these and other startups. We'll share more next month, from our ever-growing list.

Several of our startups to watch will be on hand at next week's Global Insurance Symposium in Des Moines, Iowa, along with my ITL colleagues Dave Dias and Paul Winston. If you are able to attend, you can learn first-hand about their innovations.

Cheers,

Paul Carroll,
Editor-in-Chief 

When it comes to healthcare reform, it’s all about the math. The First Element: Trump and Winning President Trump hates to lose. He’s about winning until we’re all sick of winning. (His words, not mine.) The American Health Care Act, Republicans' attempt to replace the Affordable Care Act, also known as Obamacare, failed. Support was so scarce that Speaker of the House Paul Ryan and the president didn’t even bring it to a floor vote in March. The press said Trump lost. Given his vocal support and strong lobbying for the bill, this assessment was accurate, but one the president cannot, and, apparently will not, accept. He sent his team to try to salvage the bill before the April recess. They failed. Which was a bit surprising given that Trump seems more focused on passing a bill – any bill – than on the substance of legislation. This is the first number in our healthcare reform equation: Trump wants to win and doesn’t care how. The Second Element: Divided Republicans It takes a simple majority to pass a bill out of the House. With 434 current members (the elevation of Jim Price to Secretary of Health and Human Services leaves one seat vacant), 218 votes are required to pass legislation. There are currently 246 Republicans in Congress. Having already shut Democrats out of the process, Trump needs all but 28 members of the GOP caucus to pass a bill; a 29^th Republican “no ” vote, and the bill fails. There are about 40 members of the House Freedom Caucus, a group of the chamber’s most conservative lawmakers. The majority of the caucus united in opposition to the AHCA. In March, Trump blamed them for the bill's defeat. In April, he sent his emissaries to get their votes. The Freedom Caucus demanded elimination of some of the ACA’s most popular provisions as the price of their support. These provisions prevent carriers from excluding coverage for pre-existing conditions and require health plans to include certain essential benefits, like maternity coverage. The White House reportedly considered acquiescing to these demands. The problem, however, was that accepting the Freedom Caucus' demands resulted in (relatively) moderate GOP members abandoning the AHCA. Gaining conservatives votes doesn’t help if the cost is an equal number of moderate votes. There may be a path to pass the AHCA solely relying on solely on Republican votes, but, given the divide between conservative and mainstream Republicans, it’s hard to find it. Which provides the second number for our equation: Republicans can’t pass healthcare reform on their own. See also: The Math of Healthcare Reform   The Third Element: Democrats Want Repair Democrats believe the ACA has been good for America, especially for those who, but for the ACA, would have no healthcare coverage. Most liberal Democrats think the ACA doesn’t go far enough. They won’t be satisfied with anything less than a single-payer system. Many Democrats, however, think the ACA is generally fine, but in need of critical tweaking to keep it working. Some liberals will hold out for their dream of “Medicare for All,” but even many in their ranks will take a repaired ACA over a broken system or what Republicans are offering. Which is why Democrats united against the Republican plan. Not that it mattered. Republicans never sought Democratic votes for the ACA. Democrats want to fix the ACA. That’s the third and final number in our healthcare reform equation. The Math of Healthcare Reform Compromise If Trump wants to win, he needs to move beyond a purely Republican formulation. Otherwise, as shown above, the math doesn’t work. Republicans need the larger numbers that Democrats provide to pass healthcare reform legislation. How does this math work? Let’s say a healthcare reform package reaches the floor of the House that attracts 164 Republicans – just two-thirds of their caucus. However, it gains support from 54 Democrats – only one-third of their caucus. The bill moves on to the Senate. In short, it’s easier to find 218 votes among 434 members than from among 246. This path makes the challenge before the president straightforward, if difficult: find a legislative package that attracts enough Democratic votes to offset the Republican votes it loses. In the old days (before Washington because hyperpartisan), pragmatists from both parties would meet and hammer out a compromise. That’s what’s needed now. Significantly, there’s plenty of common ground to be found. There are ACA taxes that neither Republicans and Democrats like. Eliminate them. The Shared Responsibility Payments that penalize Americans for going without coverage are universally acknowledged to be ineffective. Fix it. Both Democrats and many Republican want to keep the ACA’s Medicaid expansion. Preserve it. The path to a compromise won’t be easy, but the equation is simple addition: Trump wants to win and doesn’t care how PLUS Republicans can’t pass healthcare reform on their own PLUS Democrats’ want to fix the ACA. The result: compromise. See also: Stigma’s Huge Role in Mental Health Care   Political Cover The biggest obstacle to achieving healthcare reform is not the math, it’s the politics. Incumbents in both parties dread being “primaried” – Republicans fear being challenged from the right, Democrats from the left. This is not paranoia. The extremes of both parties will seek vengeance on their less pure teammates. Party leaders and the administration will need to give these members extensive cover in terms of messaging, campaign money and resources to beat back these attacks. Or they will need to convince the public that failing to achieve healthcare reform is a worse outcome than the compromise. This is where Trump proves he deserves to win. He must demonstrate his self-proclaimed negotiating prowess and his proven marketing acumen to create a political environment where compromise on healthcare reform doesn’t doom incumbents. In other words, for Trump to win he needs to make sure that members of Congress win, too.  Otherwise, he loses. That’s politics—and math. For curated articles on healthcare reform, check out the Alan Katz Health Care Reform Magazine on Flipboard.

Having spent a number of weeks speaking at, or chairing, various industry events, I've seen how firms are nervous about the rise of fintech/insurtech and are convinced they should focus on digital and technology for growth. Is that right? Does success and sustainable growth come from that focus? In response, I want to share a two-part blog post, based on a talk that I’m giving to mutual lenders in London. The topic concerns where to focus as a 21st century business. I hope it will help leaders grappling with competing demands on their time and attention. Here is part one. Where to focus? (Winds of change) In our ever-changing world, where should you focus to succeed with improving performance and readiness for the future? Many social and business commentators will highlight key trends. These include:

• The rise in the power of consumers (including transparency and ease of switching)
• The erosion of trust in organizations (especially financial services)
• Increased regulation (including conduct risk)
• Rise in services expectations driven by experience from other sectors
• Emergence of technology disruption/innovation scene

All these combine to make it ever more urgent for lenders to regain trust, by both meeting service expectations and communicating more appropriately. Both of those twin aims are informed by better customer insight: genuinely understanding your customers and the jobs they want to get done (including when), better than your competition. See also: How to Take a Bold Approach to Growth   Fortunately, alongside the societal and technology challenges I listed above, opportunities also present themselves. These include:

• Increased availability of wider range of data and computing power to analyze
• Growth in analytics tools/market (including data science and statistics)
• Improvements in marketing automation, service bots and personalization capability
• Evidence from disrupters (like Metro Bank and Aldermore) of service differentiation
• Financial Conduct Authority (FCA) focus on behavioral economics giving opportunities in "regulatory sandbox"

Based on my experience of both creating/leading such teams for more than 15 years and coaching leaders across the U.K. and Europe, I see tremendous commercial potential. However, too many firms rush into hiring data scientists without clear business goals. As too many have discovered to their cost, the real value comes from improved customer insight (not technology or data science for their own sake). On the encouraging side, a number of studies have shown that businesses that make extensive use of analytics can outperform their peers. But, just as has previously been seen with the "hype cycles" of data warehousing and customer relationship management (CRM), a lot of technology spending can also be wasted. How can businesses avoid that pitfall? Many lenders (and financial services firms more broadly) aspire to "customer-centricity" as a business strategy. Far fewer achieve both improved customer experiences and sustainable profit growth as a result. Insights 2020 findings A key global study focused on understanding why some businesses succeed at this challenge, while others fail, was Insights 2020. As reported in Harvard Business Review, this collaboration talked to more than 10,000 practitioners and 330 leaders across more than 60 countries. Insights 2020 identified three factors that distinguished those who achieved customer-centricity, measured through customer satisfaction, digital engagement and commercial return. These three priorities are:

1. Purpose-led, data-driven, consistent customer experiences (multi-channel/journey)
2. Embedded customer obsession in culture (decision-making, performance management and embracing experimentation)
3. Customer insight team is an active, equal business partner

Getting clear on customer insight What do I mean by customer insight? Different organizations will have different answers. Some appear to equate the term with research, others with analytics. A few relate it to targeted database marketing, and almost everyone can see the importance of quality data for any such work. Benchmarking best practice within customer insight, especially for financial services firms, has taught me that a more holistic approach works best. The most capable teams combine technical skills in data, analytics, research and database marketing. But, as the saying goes, it’s what you do with it that counts. Using those technical skills in concert, to achieve a deeper understanding of your customers that enables behavioral change, is where true customer insight lies. My own definition of customer insight is: “A non-obvious understanding about your customers, which if acted upon, has the potential to change their behavior for mutual benefit.” Key strengths needed (including soft one) To achieve that depth of insight and impact requires two key strengths. First, the use of the use of the four technical disciplines I mentioned above, in concert to produce synergy. I normally explain this through use of Laughlin Consultancy model for Holistic Customer Insight, a virtuous circle of how to operate in multi-disciplinary teams. The second strength needed is analysts who can speak to your business. There is no point discovering great insights into your customers if these remain on the shelf. For that reason, several leading customer insight teams have benefited by investing in softer skills training for their technical teams. The model I use is a nine-step model, from incisive questioning (to determine real business need) all the way through to following up to ensure insights are acted upon in the business (to achieve customer and commercial targets). See also: The Formula for Getting Growth Results   Your data foundation For most organizations, reaching that level of capability begins with a focus on data. When speaking with leaders from across many different sectors, I find that a perennial headache is either getting the data they need or being able to achieve a single customer view. Such a focus on data, as the foundation of customer insight and customer-centricity, makes sense. However, I would like to make a plea for a focus on two aspects that are too often neglected. Data models and metadata may sound too much like topics for technophiles or data geeks, but lack of both can have big business impacts. Faced with the challenge of capturing and using more data, egged on by technology suppliers, too many companies leap straight into a technology solution and technical build. However, with the pace of change and ever-growing list of data that may be needed (considering the growth of Internet of Things, for example), businesses need a more sustainable and technology-independent map. That is the role of the too-often-neglected conceptual and logical data models. These should be treated like blueprints for your business ecosystem. Alongside that data gap, another common lack for analytics team is missing metadata. That is data about data. In all the excitement to gather more facts about customer segments, or potential triggers for marketing campaigns, the basic need for things like a data dictionary can be missed. Many insight or analytics teams rely on what senior analysts hold in their heads. But the expertise about what different data items mean, which can be trusted and how to interpret different values – all this is too valuable to allow it to walk out of the door. What next? That’s it for part 1. Part 2 coming soon….

The inanimate world around us is coming alive, powered by smart things and AI. It is difficult to name an object for which there is not a smart version.

Garage doors, thermostats, doorbells, appliances? Check.

Shoes, belts, hats, shirts? Check.

Cars, trucks, boats, drones? Check.

Just about anything you can imagine, and some bizarre things that would probably never cross your mind, have smart versions that connect to the internet and can be controlled by mobile apps or even take action on their own. The potential is great, and the implications for insurance are many. But one thing about smart things that has a mixed record so far is how humans communicate with them. In some cases, the customer experience is well-thought-out and will contribute to adoption. In other cases, the experience is downright awful.

Without naming specific companies, here are a few examples of good and bad experiences with smart things.

• Smart TVs: I am starting here because some of these are terribly frustrating. Many require interaction via remote control devices, pop-up keyboards on the TV screen and the down-down-over-over-over maneuvering on the keyboard for EACH LETTER. It reminds me of the early texting days with triple taps.
• Smart tags: Small devices that attach to keys, slide into wallets or get packed into suitcases are widely available. I’ve tried many of these devices and have discovered that some are simple, fast and easy to install and use, while others are a nightmare. One device I ordered was extremely hard just to get out of the package! Another one required you to slide it open to install a battery, but I almost gave up trying to pry it open. Alternatively, I have some that I use that took me less than a minute to set up, and they just work.
• Telematics devices: There seems to be a migration away from dongles, which is a good thing. In some cars, you have to be a contortionist to get your body into position to plug the dongle into the OBD port. Mobile-app-based telematics are easier to set up, and the user interfaces are usually modern.
• Wearables: I’ve had three different fitness wearables. Generally, the experience is good, although sometimes the data entry to set up a profile and do regular logging gets tedious.
• Vehicle information/entertainment systems: The ability to initiate a phone call or change the radio station with a voice command is great – when it works. There are some commands that are just never interpreted correctly, or never interpreted at all.

See also: How to Make Smart Devices More Secure  

I could continue with examples of smart home devices, virtual reality/augmented reality headsets and glasses and other smart objects. Many of you can relate from your own experiences: some are slick, easy and fun – and others tedious and frustrating. There are several lessons here that insurers should keep in mind in any venture where they are providing or leveraging smart devices to policyholders.

• Recognize that customer experience goes beyond the mobile app. The ordering, shipping, opening the box and reading the initial instruction booklet are all part of the experience. Some insurers discovered how important this can be after sending out dongles for telematics devices.
• Make sure it works! I have returned more than one smart item, including a bathroom scale that was supposed to synch with a fitness wearable that never worked, even after several calls to tech support. It is the ultimate poor customer experience when something does not work as advertised.
• Resist the urge to collect too much information. Especially during set-up, just collect what is minimally required to get it going, not extra information that you desire for marketing and other purposes. When an individual buys a smart device, he is anxious to get it up and running.
• Ensure that tech support is accessible. “Fill out this form, and we will contact you within the next 48 hours” is not a good way to go. Most people are excited about their new device and don’t want to wait this long for a response. At the very least, provide a live chat session.

See also: ‘It’s the Customer Experience, Stupid’  

The connected world of smart things is exciting and offers many possible ways to enrich our daily lives, improve business operations and make the world safer. The functionality of a smart device is very important. But don’t forget that the customer experience will play a large role in the adoption of smart things.

Uncertainty about several key variables appears to be causing U.S. businesses and insurance companies to move cautiously into the much-heralded, though still nascent, market for cyber liability policies. Insurers continue to be reluctant to make policies more broadly available. The big excuse: Industry officials contend there is a relative lack of historical data around cyber incidents, and they bemoan the constantly evolving nature of cyber threats. This assessment comes in a report from the Deloitte Center for Financial Services titled: Demystifying Cyber Insurance Coverage: Clearing Obstacles in a Problematic but Promising Growth Market “Insurers don’t have sufficient data to write coverage extensively with confidence,” says Sam Friedman, insurance research leader at Deloitte. But the train is about to leave the station, and some of the stalwarts who shaped the insurance business into the ultra conservative (read: resistant to change) sector it has become could very well be left standing at the station. Consider that regulations imposing tighter data handling and privacy protection requirements are coming in waves. Just peek at the New York Department of Financial Services’ newly minted cybersecurity requirements or Europe’s recently revamped General Data Protection Regulation. With cyber threats on a steadily intensifying curve, other jurisdictions are sure to jump on the regulation bandwagon, which means the impetus to make cyber liability coverage a standard part of everyday business operations will only increase. Meanwhile, cybersecurity entrepreneurs, backed by savvy venture capitalists, are moving aggressively to eliminate the weak excuse that there isn’t enough data available to triangulate complex cyber risks. In fact, the opposite is true. Modern-day security systems, such as anti-virus suites, firewalls, intrusion detection systems, malware sandboxes and SIEMS, generate mountains of data about the security health of business networks. And the threat intelligence systems designed to translate this data into useful operational intelligence is getting more sophisticated all the time. See also: Why Buy Cyber and Privacy Liability. . .   And while large enterprises tend to have the latest and greatest of everything, in house, even small and medium-size businesses can access cutting-edge security systems through managed security services providers. Meanwhile, big investments bets are being made in a race to be the first ones to figure out how to direct threat intelligence technologies to the task of deriving the cyber risk actuarial tables that will permit underwriters and insurers to sleep well at night. One cybersecurity vendor to watch in this arena is Tel Aviv, Israel-based InnoSec. “Cyber insurance policies are being given out using primitive means, and there’s no differentiation between policies,” observes InnoSec CEO Ariel Evans. “It’s completely noncompetitive and solely aimed right now at the Fortune 2000. Once regulation catches up with this, cyber insurance is going to be required. This is around the corner.” InnoSec was busy developing systems to assess the compliance status and overall network health of companies involved in merger and acquisition deals. It now has shifted to seeking ways to apply those network assessment approaches to the emerging cyber insurance market. At the moment, according to Deloitte’s report, that market is tepid, at best. While some have predicted U.S. cyber insurance sales will double and even triple over the next few years to reach $20 billion by 2025, cyber policies currently generate only between $1.5 billion and $3 billion in annual premiums. Those with coverage in minority As of last October, just 29% of U.S. business had purchased cyber insurance coverage despite the rising profile of cyber risk, according to the Deloitte report. Such policies typically cover first- and third-party claims related to damages caused by a breach of personally identifiable information or some derivative, says Adam Thomas, co-author of the Deloitte report and a principal at the firm. In some cases, such policies also might cover business disruption associated with a cyber incident. The insurance industry contends it needs more businesses to buy higher-end, standalone cyber insurance policies, until enough claims data can be collected to build reliable models, much as was done with the development of auto, life and natural disaster policies. But businesses, in turn, aren’t buying cyber policies in enough numbers because insurers are adding restrictions to coverage and putting fairly low limits on policies to keep exposure under control. “It is a vicious cycle,” Friedman says. “Insurers recognize that there is a growth opportunity, and they don’t want to be left out of it,” he says. “On the other hand, they don’t want to take more risk than they can swallow.” While the insurance industry gazes at its navel, industry analysts and cybersecurity experts say the big challenge—and opportunity—is for underwriters and insurers to figure how to offer all businesses, especially small- and medium-size companies, more granular kinds of cyber policies that actually account for risk and provide value to the paying customers. “What they’re doing now is what I call the neighbor method,” InnoSec’s Evans says. “You’re a bank, so I’ll offer you a $100 million policy for $10 million. The next guy, he’s a bank, so I’m going to offer him a $100 million policy for $10 million. It has nothing to do with risk. The only place this is done is with cyber.” Talk in same terms This is due, in part, to a lack of standard terminology used to describe cyber insurance-related matters, says Chip Block, vice president of Evolver, a company that provides IT services to the federal government. The SANS Institute, a well-respected cybersecurity think tank and training center, last year put out a report that drills down on the terminology conundrum, including recommendations on how to resolve it, titled Bridging the Insurance/Infosec Gap. And the policies themselves have been another factor. “If you compare car insurance from Allstate and Geico, a majority of the policies are relatively the same,” Block says. “We haven’t gotten to that point in cyber. If you go from one underwriter to another, there is no common understanding of the terminology.” Understandably, this has made it hard for the buyer to compare policies or to determine the relative merits of one policy over the other. Block agrees that cyber policies today generally do not differentiate based on risk profile—so a company that practices good cyber hygiene is likely to see no difference in premiums as compared with one that doesn’t. See also: How Data Breaches Affect More Than Cyberliability   Industry must get moving InnoSec’s Evans argues that even though cybersecurity is complex, the technology, as well as best practices policies and procedures, are readily available to solve the baseline challenges. What is lacking is initiative on the part of the insurance industry to bring these components to bear on the emerging market. “This is absolutely possible to do,” she says. “We understand how to do it.” Putting technological solutions aside, there is an even more obvious path to take, Friedman argues. Resolve the terminology confusion and there is little stopping underwriters and insurers from crafting and marketing cyber policies based on meeting certain levels of network security best practices standards, Friedman says. “You look at an organization’s ability to be secure, their ability to detect intrusions, how quickly they can react and how much they can limit their damage,” he says. “In fact, insurers should go beyond just offering a risk-transfer mechanism and be more aggressive in helping customers assess risk and their ability to manage and prevent.” Thomas pointed to how an insurance company writing a property policy for a commercial building might send an engineering team to inspect the building and make safety recommendations. The same approach needs to be taken for cyber insurance, he says. “The goal is to make the insured a better risk for me,” he says.

Pushing at boundaries and challenging traditional notions is what innovation is all about. Rethinking something that people have taken for granted for too long can open opportunities for enhancing service, increasing efficiencies and generating revenue. Take claims. The idea that the claim settlement should reflect the insured loss has held sway for a great many years. Is it time for innovators to knock this one off its pedestal? It looks like that time has come, for insurers in the U.S. are starting to turn to claims optimization. To explain this, I should start with the perhaps more familiar concept of price optimization. The price version has the insurer setting the premium for insuring a risk according to what the policyholder is prepared to pay, rather than the level of risk that the policy is presenting. It involves using big data to work out the price at which particular types of customer will start to look for alternative quotes, and then progressively raising the premium to just below that amount. See also: Innovation Challenge for Commercial Lines   A leading figure in the U.K. insurance market recently described price optimization to me as “recognizing the true lifetime value of the customer and reflecting that in a better price.” It’s a nice quote, so long as you’re the insurer on the receiving end of that "lifetime value" and that "better price" and not the customer paying for them. I’ve yet to hear how that description fits in with the regulator’s interest in fair outcomes for customers. It would struggle to do so, for reasons I explain in this paper I wrote for the U.K.’s Chartered Insurance Institute last year. In short, the nature of insurance makes price optimization highly questionable on ethical grounds. It’s hardly surprising that a recent PwC survey found that 72% of insurance CEOs think it will be harder to sustain trust in a digitized market. With claims optimization, insurers would seem to be abandoning all remaining hope of sustaining trust in a digitized market. Claims optimization involves using big data to establish the amount that a particular claimant would be prepared to accept as settlement of the claim. So if all those algorithms pinpointed the claimant as someone in financially tight circumstances, then the settlement offered to that claimant would be optimized to reflect a greater and more immediate need for cash. This would involve tweaking the comparative speed of a cash settlement versus a replacement service and setting relative offers to achieve the optimized position. This still falls neatly within that description of optimization as “recognizing the true lifetime value of the customer and reflecting that in a better price.” Indeed, an insurer happy to optimize on price would hardly need to bat an eyelid at optimizing that other value determinant: claims expenditure. After all, the insurer would say, if a claimant is prepared to accept that lower settlement, why shouldn’t the insurer offer it? Let’s be quite clear: Claims optimization is an exploitation of the unequal balance of information and economic power between a consumer and an insurer. It is unprofessional, and it is unethical. Might this view perhaps point to me being a naysayer on innovation? Not at all – I have a postgraduate degree from one of the earliest courses in the U.K. on the study of scientific and technological innovation. That course taught me to recognize the multi-sided nature of innovation and to see that it is not some nature force of business evolution, but a mix of social, economic, philosophical and technological drivers. See also: The Great AI Race in Insurance Innovation   Despite what vendors of "big data solutions" say about optimization, it is not a natural next step for underwriting and claims. It is home to a number of quite radical assumptions about what insurance is there to do and how it should do it. It would be nice to see some of those assumptions brought out into the open and debated, but, unless Andrew Bailey at the FCA follows through on some of his hesitations about price optimization, then I fear such a debate is unlikely. I have heard some chief executives at leading insurers wonder whether price optimization was the right thing to do. If, as it would appear, they no longer have any such qualms on the pricing side, then it is but a small step to their being equally relaxed about using it on  the claims side. In that case, I look forward to listening to them explain their reasoning for doing so on a public forum like, say, the BBC Radio’s Today program.

In today’s online shopping environment, lead sellers and lead-buying marketers alike work well together toward the same goal of delivering a great customer experience; however, they often struggle with an array of challenges along the way. The Evolution of the Lead Seller-Lead Buyer Relationship The relationship between online lead sellers and lead buyers began as a very simple one, in the late '90s. The lead seller was also the lead generator—who dealt directly with the lead buyers. But it wasn’t long before small- and medium-sized publishers realized they could make money by generating leads that they would then sell to the large lead generators that had direct relationships with the lead buyers. This resulted in lead generators that would also aggregate leads generated by smaller publishers. By the mid-2000s, the large generators and aggregators began to monetize individual leads further by sharing them with other large generators and aggregators that had unique end-buyer relationships. Initially, this transpired in a private, trusted transaction environment with strict rules in place that were easily enforced. Two companies worked together to maximize the monetization of each other’s leads. Collectively, they made more money, and the consumer had more options available. It was a win-win-win for everyone in the ecosystem. As more of these private sharing arrangements developed (driven by the additional monetization opportunity), the technology evolved to support it. Hence the ping post ecosystem, which publishers, aggregators and generators leverage to best monetize leads. Much like in a stock exchange, sellers and buyers come together to create an efficient market with a variety of options for the consumer, and the highest bidders are typically the entities with the best consumer offer. See also: Changing Business Models, ‘New’ ERM   The Present State of the Lead Seller-Lead Buyer Relationship In insurance, the relationship between sellers and buyers is generally strong, as long as the publishers, aggregators and generators play by the rules. For example, leads should only get sold to a certain number of buyers in a shared-lead world, and exclusive leads should only be sold to one buyer. Other examples of rules include:

• No manipulation of the consumer data
• No recycling of leads later
• No fake leads
• No non-TCPA-compliant leads
• No incentive-driven leads
• No unauthorized sales to stated end-buyers

It is the “bad actors” that don’t play by these rules in the ping post ecosystem that can cause significant problems. We can look to the evolution of the mortgage and education verticals to learn how to solve these problems. Solutions for Today’s Lead Seller Challenges TCPA Compliance. One of the most stressful challenges that lead sellers face today is TCPA compliance. Given that TCPA case filings increased more than 940% between 2010 and 2015, coupled with the fact that consumers are being encouraged to file suits by some law firms, the TCPA has become a huge hurdle for sellers to overcome. Both lead sellers and buyers must avoid exchanging non-TCPA compliant leads and make sure they have persuasive evidence of consent in the event they, or end-buyers, face a complaint or lawsuit. Measuring Consumer Intent. Another challenge sellers face is gaining the ability to measure the intent of each consumer. With insights into the individual consumer journey, you gain the ability to measure the intent—and therefore the value—of each lead. There are technology solutions available that enable you to measure consumer intent. Those Bad Actors Not Playing by the Rules. Many lead buyers are actively leveraging technology to validate consumer data as “good data” and some using de-duping solutions to minimize buying the same lead twice. In the ping post ecosystem, much of the data on the origin and history of a lead is “contributed data." The challenge of eliminating old or recycled leads, dupes, fake and no-intent leads stems from a lack of ability to verify that “contributed data” as fact. For example, an insurance lead aggregator buys a lead from another aggregator or from a generator and agrees to only sell the lead once and only to one, specific insurance provider. This is contributed data, but there is no way to validate it as fact. What sometimes happens is a bad actor will sell that lead to other insurance providers or hold it for a week or so then sell it again—a recycled lead. There is no transparency and little accountability. To validate contributed data as factual, you have to establish a “chain of custody” to verify that each lead seller participating in the ping post system is playing by the rules. Then, if there is ever a problem or complaint, you have data to help the lead generator or buyer that is experiencing a problem identify where in the chain the problem occurred and expose the bad actor. The Most Crucial Area for Improvement Improving Lead Value - To continually improve relations with their buyers, sellers always seek ways to cultivate greater value in their leads. The simplest solution is for sellers to distribute the highest-intent leads possible and do everything possible to eliminate selling “no intent” leads to their clients. To best accomplish this, sellers must require any upstream publishers and generators to adhere to the simple rules that sellers and buyers have established and have a mechanism in place to verify any contributed data surrounding exchanged leads. If anyone is still following the antiquated practices of a bad actor, it’s going to catch up to them eventually. See also: Developing Programs for Shifting Channels   Bad actors are bad news for the entire ecosystem, leaving a bad taste in the mouth of buyers, that can cloud relationships with reputable sellers and result in a deterioration of value to all participants. By exposing the bad actors, sellers can avoid a race to the bottom, ensure they deliver a great consumer experience and deliver high-intent leads—and the resulting growth opportunities—to buyers. Technology is available to the lead-gen industry today to enable the chain of custody and associated data trail. We encourage everyone to join this insurance industry initiative.