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 Yet, for many, work life is a “trip back in time” due to old and frankly outdated systems.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.

I’ve often thought the most valuable interactions happen with the people at the edge of our networks. The people we meet serendipitously, through our more distant contacts. It’s here, on the edge, where the sparks of creativity really fly. Recently, I’ve been putting this theory to the test by taking the time to meet face-to-face with people I might more usually only connect with by email or LinkedIn. It’s a refreshing experience. One of the many benefits is frequent exposure to new ideas and new ways of thinking from people who view the world through a different lens. There are other benefits, such as getting to see the new musical “Bat Out of Hell” in the company of an American lawyer. But I digress ... It’s not just people who benefit from networking at the edge. Computers do, too, and there’s an interesting analogy to be drawn here with the emerging importance of edge computing. This is where processing and data are placed at the edge of our networks to have the maximum effect. Let me explain. Over the last decade or so, we’ve seen processing and data increasingly centralized in the cloud. This has been driven partly by the cost-effectiveness and scalability of cloud computing and partly by the growth of big data. Amazon Alexa is an excellent example of how this works. Voice commands are picked up by an Amazon Echo device, converted from speech to text and fired off to the cloud where natural language processing (NLP) and clever software are used to interpret and fulfill your requests. The results are served back to your Echo in less than half a second. Very little processing takes place on the Echo, and very little data is stored there; all the heavy lifting is done centrally in the cloud. See also: The Big Lesson From Amazon-Whole Foods   This model works well if the edge device (the Echo) is always connected to the cloud via the internet, the arrival rate of new data (your voice commands) is relatively low and the response time is not critical (we’re happy to wait half a second for Ed Sheeran to start his next song). But it doesn’t work so well if the edge device is not always connected, if the volume of real-time data streaming into the device is huge or if an instant response is needed. Imagine you’re being driven to the theater by your AI-controlled smart car equipped with hundreds of sensors gathering real-time data from every direction. If the sensors detect a child running out in front of the car, there’s no point firing that data off to the cloud for processing. It has to be processed and acted on instantly and locally by the car itself. There are many, many more examples where the edge devices (cars, traffic lights, fitness bracelets, microwaves, safety critical sensors on assembly lines… in fact, very many of the billions of devices that will be connected to the internet of things over the coming years) will need the ability to process their own real-time data. These edge computing devices will still connect to the cloud, but the location of the processing and the data will vary according to need — in the cloud for asynchronous machine learning insights and improvements; at the edge for real-time processing of real-time data streams to determine real-time actions. Developing the hardware and software for these devices will require new ways of thinking. It’s not about big data; it’s about small, fast data. And I’m sure we’re going to see dramatic improvements in battery efficiency, data storage and processing capability of these intelligent edge computing devices. The Internet of Things is actually going to become the Internet of Small Powerful Intelligent Things (although I doubt that acronym will catch on). See also: Major Opportunities in Microinsurance   Most interestingly of all, though, from a cultural and business perspective, is the innovation this edge computing will enable, such as:

• The insurance industry will be able to offer better deals and new types of policies driven by the intelligence embedded in the insured assets.
• The health industry will be able to provide preventative care supported by intelligent wearables monitoring everything from activity to blood sugar levels.
• The entertainment industry will be able to deliver interactive content without those annoying buffers and whirling circles.

And, who knows, maybe edge computing will also help us communicate more effectively with each other. Because spending time at the edge of our networks, as I have been discovering, is where the sparks of creativity really fly. Like the musical “Bat Out of Hell,” it’s one experience I can thoroughly recommend!

According to a recent survey of U.S. consumers, more than 32% of all respondents—and 50% of those aged 18–25—said they prefer to work directly with insurance carriers. We are also experiencing rapid changes in the amount of data that insurers are gathering and analyzing: The number of internet-connected devices and sensors is projected to reach 50 billion by 2020, providing real-time information that insurers can use for better pricing/underwriting. Meanwhile, drones are expected to have a $6.8 billion impact on the insurance industry. See also: Drones Reducing Accidents on Job   As a drone enthusiast myself, I’ve been lucky to use my drone to capture aerial imagery—footage I was unable to take a few short years ago. This is but one of the copious amounts of types of data unmanned aerial vehicles (UAVs) can obtain to support the insurance industry. Accordingly, I curated a list of the top five ways drones are affecting the insurance industry. 1. Drones already play an important part in the insurance claims process Customer experience is paramount, and the ability to shorten the claims timeframe is crucial. Today, one claims adjuster on-site and equipped with a drone can set up an automated flight plan around multiple insured locations; evaluate the properties using sensors; and capture images. According to Cognizant, drone usage is predicted to make claims adjusters’ workflow 40% to 50% more efficient. Drones can improve the speed with which customers receive settlements and give claims managers  a better sense of where and how many staff should be deployed. There is also less risk for claims adjusters, who no longer need to climb ladders or go on roofs to assess damage. 2. More precise risk management and tailored pricing Drones can be used to collect information about a property before a policy is issued, by capturing data on property features that make it less vulnerable, such as storm shutters. The data can facilitate personalized premiums. After all, insurance is all about measuring risk and accurately pricing it. 3. Better data, better catastrophe models Aerial imagery taken by drones enhances data for catastrophe model components and provides inputs for analysis. As discussed in this blog post, for catastrophe model developers and users there is mutually beneficial interplay between model development, engineering analysis and exposure and claims data quality. Improving the feedback loop between underwriters, claims adjusters and model validation can substantially increase a cat model’s performance in quantifying risk. 4. Lower losses from fraud According to the Insurance Information Institute, fraud accounts for about 10% of property and casualty insurance losses and loss adjustment expenses, which translates to about $32 billion each year. In addition, 57% of insurers predict an increase in this type of fraud by policyholders. How can drones help? After an extreme event, it is common for insurance companies to receive numerous claims for damages that existed before the event occurred. By using UAVs prior to an extreme event to capture images of insured properties, companies can protect themselves from such fraudulent claims. 5. Drones and artificial intelligence come together Artificial intelligence (AI) integrated with drones will allow for more independent functionality. IBM’s AI system, Watson, is able to automatically process aerial imagery, assess hail damage and calculate damage extent. Drones integrated with AI will provide an end-to-end solution that will allow for an expedited claims process, reduction in costs and increase in customer satisfaction. See also: What Is the Future for Drones?   An extreme event can devastate a region and affect thousands of lives. For the insurers and people affected, timing is everything. Organizations need to dedicate resources immediately, effectively and efficiently to help get communities and businesses back on their feet. In this era of rapid technological advancement, drones are one of the many new tools with which life, business and the global economy are being transformed.

Despite a generally soft market for traditional P&C products, the fact that so many industries and the businesses within them are being reshaped by technology is creating opportunities (and more challenges). Consider insurers with personal and commercial auto. Pundits are predicting a rapid decline in personal auto premiums and questioning the viability of both personal and commercial auto due to the emergence of autonomous technologies and driverless vehicles, as well as the increasing use of alternative options (ride-sharing, public transportation, etc.). Finding alternative growth strategies is “top of mind” for CEOs.  Opportunities can be captured from the change within commercial and specialty insurance. New risks, new markets, new customers and the demand for new products and services may fill the gaps for those who are prepared. Our new research, A New Age of Insurance: Growth Opportunities for Commercial and Specialty Insurance at a Time of Market Disruption, highlights how changing trends in demographics, customer behaviors, technology, data and market boundaries are creating a dramatic shift from traditional commercial and specialty products to the new, post-digital age products redefining the market of the future. See also: Insurtechs Are Pushing for Transparency Growth Opportunities New technologies, demographics, behaviors and more will fuel the growth of new businesses and industries over the next 10 years. Commercial and specialty insurance provides a critical role to these businesses and the economy — protecting them from failure by assuming the risks inherent in their transformation. Industry statistics for the “traditional” commercial marketplace don’t yet reflect the potential growth from these new markets. The Insurance Information Institute expects overall personal and commercial exposures to increase between 4% and 4.5% in 2017 but cautioned that continued soft rates in commercial lines could cause overall P&C premium growth to lag behind economic growth. But a diverse group of customers will increasingly create narrow segments that will demand niche, personalized products and services. Many do not fit neatly within pre-defined categories of risk and products for insur­ance, creating opportunities for new products and services. Small and medium businesses are at the forefront of this change and at the center of business creation, business transformation and growth in the economy.

• By 2020, more than 60% of small businesses in the U.S. will be owned by millennials and Gen Xers — two groups that prefer to do as much as possible digitally. Furthermore, their views, behaviors and expectations are different than those of previous generations and will be influenced by their personal digital experiences.
• The sharing/gig/on-demand economy is an example of the significant digitally enabled changes in people’s behaviors and expectations that are redefining the nature of work, business models and risk profiles.
• The rapid emergence of technologies and the explosion of data are combining to create a magnified impact. Technology and data are making it easier and more profitable to reach, underwrite and service commercial and specialty market segments. In particular, insurers can narrow and specialize various segments into new niches. In addition, the combination of technology and data is disrupting other industries, changing existing business models and creating businesses and risks that need new types of insurance.
• New products can be deployed on demand, and industry boundaries are blurring. Traditional insurance or new forms of insurance may be embedded in the purchase of products and services.

Insurtech is re-shaping this new digital world and disrupting the traditional insurance value chain for commercial and specialty insurance, leading to specialty protection for a new era of business. Consider insurtech startups like Embroker, Next Insurance, Ask Kodiak, CoverWallet, Splice and others. Not being left behind, traditional insurers are creating innovative business models for commercial and specialty insurance, like Berkshire Hathaway with biBERK for direct to small business owners; Hiscox, which offers small business insurance (SBI) products directly from its website; or American Family, which invested in AssureStart, now part of Homesite, a direct writer of SBI. The Domino Effect We all likely played with dominoes in our childhood, setting them up in a row and seeing how we could orchestrate a chain reaction. Now, as adults, we are seeing and playing with dominoes at a much higher level. Every business has been or likely will be affected by a domino effect. What is different in today’s business era, as opposed to even a decade ago, is that disruption in one industry has a much broader ripple effect that disrupts the risk landscape of multiple other industries and creates additional risks. We are compelled to watch the chains created from inside and outside of insurance. Recognizing that this domino effect occurs is critical to developing appropriate new product plans that align to these shifts. Just consider the following disrupted industries and then think about the disrupters and their casualties: taxis and ridesharing (Lyft, Uber), movie rentals (Blockbuster) and streaming video (NetFlix), traditional retail (Sears and Macy's) and online retail, enterprise systems (Siebel, Oracle) and cloud platforms (Salesforce and Workday), and book stores (Borders) and Amazon. Consider the continuing impact of Amazon, with the announcement about acquiring Whole Foods and the significant drop in stock prices for traditional grocers. Many analysts noted that this is a game changer with massive innovative opportunities. The transportation industry is at the front end of a massive domino-toppling event. A report from RethinkX, The Disruption of Transportation and the Collapse of the Internal-Combustion Vehicle and Oil Industries, says that by 2030 (within 10 years of regulatory approval of autonomous vehicles (AVs)), 95% of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by fleets, not individuals, in a new business model called “transportation-as-a-service” (TaaS). The TaaS disruption will have enormous implications across the automotive industry, but also many other industries, including public transportation, oil, auto repair shops and gas stations. The result is that not just one industry could be disrupted … many could be affected by just one domino … autonomous vehicles. Auto insurance is in this chain of disruption. See also: Leveraging AI in Commercial Insurance   And commercial insurance, because it is used by all businesses to provide risk protection, is also in the chain of all those businesses affected – a decline in number of businesses, decline in risk products needed and decline in revenue. The domino effect will decimate traditional business, product and revenue models, while creating growth opportunities for those bold enough to begin preparing for it today with different risk products. Transformation + Creativity = Opportunity Opportunity in insurance starts with transformation. New technologies will be enablers on the path to innovative ideas. As the new age of insurance unfolds, insurers must recommit to their business transformation journey and avoid falling into an operational trap or resorting to traditional thinking. In this changing insurance market, new competitors don’t play by the rules of the past. Insurers need to be a part of rewriting the rules for the future, because there is less risk when you write the new rules. One of those rules is diversification. Diversification is about building new products, exploring new markets and taking new risks. The cost of ignoring this can be brutal. Insurers that can see the change and opportunity for commercial and specialty lines will set themselves apart from those that do not. For a greater in-depth look at the implications of commercial insurance shifts, be sure to download, A New Age of Insurance: Growth Opportunities for Commercial and Specialty Insurance at a Time of Market Disruption.

Consumers are price-shopping insurance policies online in record numbers. According to 2017 JD Power research, the importance of price has surpassed that of a good past service experience when a shopper considers or quotes a brand. Though increasing price commoditization presents an enormous challenge for insurance agencies, our newest sales lead response research provides some hope. With so many insurance organizations falling short on sales lead response best practices, there is a major opportunity for agencies, regardless of size or type, to stand out from the competition and win new policyholders. The Impact of a Winning First Impression The first impression an agency gives a potential customer is very important – not only how quickly they follow up, but also what they say. Most potential customers see this first interaction as a leading indicator of a longer-term relationship with the agency. Effective follow-up that is timely, appropriately persistent, with a message that adds value for the recipient can increase the chance of conversion. Research shows that:

• Calling a lead within one minute of an inquiry more than doubles conversion rates.
• Leads who are left two voicemails on six missed calls are 34% more likely to convert than leads who don’t receive any voicemails at all.

Insurance agencies may be under the impression that their contact strategies and specifically their lead response efforts are timely and effective, but Velocify analysis of actual calls, voicemails and emails shows that, for many of them, sales response tactics are more likely to be in need of an overhaul. See also: 3 Great Apps for Insurance Agents   Here are some pro tips to help improve call and voicemail performance shortcomings identified in the Sales Lead Response: The Ugly Truth Behind Call, Voicemail, and Email Practices study. Call and Voicemail Timing and Cadence While there is no optimal, magic time of day to make a call, following up quickly and then at strategic intervals can improve outcomes. Our analysis showed that sales professionals are often miscalculating when it comes to the most effective communication cadence -- the right number and timing of phone calls and voicemails. Calling a lead within one minute of an inquiry more than doubles conversion rates, but only 7% of the prospects in the study received a call within one minute. Almost half of all prospects submitted didn’t even receive a voicemail. Of those who did, 40% received only one voicemail, and 34% received too many. One prospect even received 10 voicemails. PRO TIP: Velocify’s six-call strategy suggests leaving a voicemail on the second and fourth call attempt. Leaving the first voicemail on the second call results in a 31% higher conversion rate than leaving that voicemail on any other call. It’s important to weave voicemails into a company’s call strategy because missed calls can go unnoticed, and a voicemail is a good way to get a prospect’s attention. However, producers need to make sure to strike the right balance because research shows leaving too many voicemails before contact, as many as five or more, can actually be worse than not leaving any voicemails. The Impact of Message Quality Voicemail frequency can increase the chance of conversion, but agencies need to leave quality messages to maximize callbacks. Accordingly, the study evaluated voicemail quality on five basic criteria: context; clarity; length; personalization; and tone. Only 18% of prospects received “good” voicemails that included all five. Almost half (46%) of all voicemails were scored “bad to terrible,” meeting three of the five criteria or fewer. On the opposite end of the continuum, 8% of the voicemails received didn’t even meet one of the five criteria. See also: How Life Insurance Agents Can Be Ready   More Effective Phone Skills, Powered by the Right Tech Tools Insurers can avoid inadvertently throwing money away by responding appropriately and learning how to more effectively maximize every prospect interaction. There are a number of technologies and techniques available that help improve process so agencies can more easily and effectively make a better first impression.