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What to Expect in 2020

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Happy New Year!

I figure we should dub this year "Hindsight." After all, hindsight is 20/20, right? So, let's imagine it's Dec. 31, 2020, and we're looking back on the year. What will we see that the industry accomplished?

Having read a bazillion forecasts over the holidays, I think lots of prognosticators are on the right track. Yes, there will be loads more AI, more use of big data/insurtech in underwriting, more chatbots and other technology in customer relations. Yes, insurance will become more modular, as companies figure out how to plug in the industry's best, say, claims technology and process rather than using just home-grown systems. No, Big Tech doesn't look likely to do a cannonball into insurance and splash all the water out of the pool, though Big Tech will probably continue to do deals like Amazon's move into distributing pharmaceuticals and pull away certain buckets of profits. 

But I think 2020 will be most notable because the industry will start to get better in an even more important way than has been described in the forecasts I've read. I believe the industry will begin to get better at... getting better.

I trace this concept back to Doug Engelbart, a monumental figure in the history of computing. In 1968, he held what has become known as The Mother of All Demos, which laid the groundwork for graphical user interfaces, hyperlinks (as in, the World Wide Web) and networked computers. He even hand-carved a scrolling device out of wood, which came to be known as a mouse because the wire running out the back of the little brown block looked like a tail.

Engelbart also contributed seminal thinking on a variety of topics, including what he described as A, B and C processes in corporations. Every company has A processes; they're how the business is run. Good companies, he said, also have B processes—ways of making the A processes better. Great companies, he argued, also have C processes—ways of improving the B processes that improve the A processes. In other words, great companies keep getting better at getting better.

(Quick aside: About 20 years ago, when I lived in Silicon Valley, I attended a birthday party at a neighbor's house and struck up a conversation with an elderly gentleman who seemed a bit left out. We got talking about innovation—that's what you did in Atherton in those days—and I mentioned that I had just published an article on A, B and C processes in a magazine I edited. He said, "But that's my idea." I corrected him: "No, that idea came from Doug Engelbart." He said, "And I'm Doug Engelbart." He was, too. He lived next door to my friend.)

I believe that 2020 could mark the year when the insurance industry makes a breakthrough in getting better at getting better. 

We've been in heavy innovation mode for several years now, so we're learning about what works and what doesn't. 

If you're an incumbent engaging with an insurtech, no, you can't operate on your normal planning cycle. By the time you pull together your annual technology road map and tee the insurtech up for your quarterly budget review to see what funds are available, that insurtech has gone belly up. It needed to make payroll by Friday. Seven months ago.

We've also learned about the sorts of tools, such as the cloud and X-as-a-service, that can speed innovation. We've become more attuned to what technologies are available outside our companies and maybe picked up a bit of experience on how to incorporate them. We've seen the need for small, focused innovation teams and for quick, inexpensive prototypes that can let us test customer reaction in the wild.

In Engelbart terms, we began several years ago with those A processes. Then we engaged B processes and began to innovate on those A processes. Now, we know enough about those attempts at B processes, those attempts at innovation, to set up ways to systematically improve on them, too.  

That's my hope, at least, as we embark on 2020. 

May the year treat us all well.

Paul Carroll
Editor-in-Chief 

Paul Carroll

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Paul Carroll

Paul Carroll is the editor-in-chief of Insurance Thought Leadership.

He is also co-author of A Brief History of a Perfect Future: Inventing the Future We Can Proudly Leave Our Kids by 2050 and Billion Dollar Lessons: What You Can Learn From the Most Inexcusable Business Failures of the Last 25 Years and the author of a best-seller on IBM, published in 1993.

Carroll spent 17 years at the Wall Street Journal as an editor and reporter; he was nominated twice for the Pulitzer Prize. He later was a finalist for a National Magazine Award.

4 Keys to Online Safety Training

Employers face challenges implementing safety training across their organizations, and technology has answered the bell.

While the traditional methods of in-person or classroom training will always have their place, obstacles related to geographic disparity, the emergence of telecommuting and other factors have added to the challenges faced by employers attempting to implement safety training across their organizations. Technology, of course, has answered the bell with one concept in particular: the learning management system (LMS). At its core, an LMS is software used to deliver and track online training. Below are four key considerations to consider when diving into the world of online safety training. 1. Keep an Eye on Content Paired with a good content library, an LMS can serve as an efficient and engaging method to train employees on a plethora of safety-related topics. Often available in multiple languages, some of the more popular course topics include blood-borne pathogens, basic first aid, personal protective equipment as well as the ever-relevant topic of slips, trips and falls. Course content is often developed with specific regulatory requirements in mind. While there is loads of content out there on all sorts of health and safety topics, not all content libraries are created equal. Before deciding on an e-learning provider, it is important to preview content, which in some instances can be drastically outdated and practically irrelevant. If the coursework features imagery from the '80s, how does that affect the credibility of the content being presented? How often are courses updated? Does the content offer imagery related to my specific industry or occupation? These are all worthwhile questions to consider. 2. Ease of Use and Customer Support If you cannot figure out how to use it, will you use it? The administrative side of an LMS will be the place from which training is assigned, tracked and reported on. Hence, the system’s ease-of-use is paramount. Without an intuitive system, an administrator could spend countless hours struggling with how to best populate rosters, assign coursework, build reports and notify trainees of pending assignments. While many companies will provide onboarding support initially, eventually service can stagnate, if not altogether disappear. And, if the group of employees trained to administer the system leave the company or change roles, another group will have to learn the ins and outs of the system. If the system is not somewhat easy to learn, you will be left with a system that no one knows how to use. While most LMS companies provide user manuals and other supportive material, it is still important to verify that the prospective provider is committed to excellence in customer support. As with any significant purchase, look for testimonials or seek the candid thoughts of current system users. See also: 7 Safety Trends for Today’s Workplace   3. Some Common Pitfalls “We apologize for the technical difficulties....” Heard this before? Technical problems arise. It is no fun to establish and launch a training curriculum, only to discover that the system-generated email that was supposed to inform employees of a training due date was blocked by a spam filter. Or maybe the notification goes out, but, as employees log in to take the training, the login page is undergoing maintenance. These things happen, and you must be prepared. Additionally, for some organizations, not all employees have adequate internet bandwidth or the minimum technical requirements to support certain systems. Challenges related to browser capability can also surface. LMS providers typically design content to run optimally on one specific internet browser (e.g., Google Chrome, MS Edge, Safari, etc.); if an organization’s preferred browser is a different than that of the LMS’s, there can be a headache for all users. 4. The Future of e-Learning Micro-learning and blended learning are hot topics in the field of e-learning these days. Both are being refined to more effectively train employees across organizations and are worth exploring. In July 2019, OSHA reiterated that online and video-based training is not enough to satisfy OSHA training obligations, so, for now, some mixture of old-fashioned hands-on training still has its place in the business world. Nevertheless, while training styles evolve, the numerous benefits and uses of digital platforms will continue to provide organizations with a great way to deliver safety training, foster a strong culture of safety and produce more engaged, effective employees.

Matthew Hesemann

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Matthew Hesemann

Matt Hesemann is currently a senior client services representative at Safety National Casualty. He works with insureds to introduce and implement the company’s robust online risk control resource platform.

Third Step to a New, Successful Program

Analyzing freely available competitor data can uncover the easiest points of entry into a market for a new insurance program.

Editor’s Note: This is the fourth in a series of posts in which CJ Lotter, a 15-year industry veteran, shares lessons learned in the form of guidance to MGAs on the steps required to build a successful program. The earlier articles are available here.  

By now, you’ve become familiar with our series of posts on program business. We’ve covered the processes for identifying a market to target and for validating the opportunity through research. Now comes one of the most important steps, analyzing competition. Much like the other steps, analyzing the competition can be boiled down to three things:

  • Gathering all available public data
  • Looking at the market on a macro level and determining which competitors own the space
  • Looking at individual players and their attributes and figuring out potential market entry points

Gathering Available Data 

After all your research, you should have a program plan narrowed down to a specific class code with a need gap. Now it’s time to do some research on the players already in the space. Insurance is one of the only industries in which your competitors must file their business plan, and anyone can pull the filings of anyone else. That’s exactly what we are going to do in this section. 

You have already selected an industry segment to target. Now, pull the filings of each competitor in that space, and all the product offerings. This will provide the raw information for your analysis in the next two sections. If, by chance, your competition is offering a non-admitted product, you will need to go elsewhere. 

Work with an industry focus group to ask about the type of insurance offerings available and gather information that way, or do market research on the product offerings available. Ideally, you will use the data you gather to answer several key questions. The most important ones will depend on your organizational goals, and we will cover those in the section on qualitative research. 

See also: 10 Steps to Successful Insurance Program   

Analyzing the Competition 

After gathering all the available competitive data, it’s time to develop the insights that will help us decide who our real competition will be. Figure out how much market share each major competitor possesses in your targeted industry. Consider these potential market share scenarios: 

 

Each scenario will require a different set of strategies. Which of these is more appealing? If you were to pursue “Scenario 1,” you would be attacking a single dominant player. In “Scenario 2,” you would enter a market with a variety of players offering a variety of solutions. 

What you decide depends on the attributes you are competing on. Traditionally, with programs, it is easier to enter a market with one established player. Ideally, this player is clunky, does business slowly and can’t react quickly enough. In this world, you can easily compete with better technology, better costs or better service, preferably all three. 

A word of advice if you choose to compete on cost: Unless the cost saving is 15% or more, it will be hard to get customers to switch from an incumbent. 

Profiling the Competitors 

With the market data pulled and analyzed, you can now move on to a qualitative analysis of the individual competitors and ultimately decide how and where to deploy your new program. Combining the data you’ve gathered, the “word on the street” from insureds in your target market and additional market research, you’ll build profiles of the major competitors. These are the attributes you should start with:

  • AM Best rating of the company
  • Size of the company in premium
  • Whether the company operates nationally or regionally
  • Types of products (from the filings, for admitted products)
  • The company’s market share in your targeted industry
  • Pricing for the product (from filings, focus groups or competitive research)
  • Distribution: Is the offering sold online or through agents?

The goal is to apply this data to understand which companies you will realistically compete with. Using the example we introduced in our prior post, the top provider of tow truck insurance may only serve the Midwest and Pacific Northwest, leaving open an opportunity in a Northeast market like New York. Or, perhaps there is a cost saving you can offer with a new product package. 

A four-quadrant (i.e. 2x2) matrix can be a good tool here, too. Pick two important variables, one for each axis, and place all the competitors onto the graph. For example, one axis could be company size, while the other represents geographic reach (from regional to national operators). 

Going as far as to do a full SWOT (strengths, weaknesses, opportunities and threats) analysis on each competitor may also be a good practice and will help illuminate the competitors you stack up against most favorably. A good resource for SWOT templates can be found here. 

See also: How to Improve the Customer Journey   

Final Thoughts 

Through diligent research, and a good measure of analysis, you should uncover a path for potential new business. Making the right decision on where to deploy, at what price point, with which distribution model and other vital issues can make or break a program launch. Some of these will be the topics of future blog posts. 

When planning a program, it is vitally important to have the conviction that you are bringing a product to the market that solves a problem better than the competition. Better pricing, better distribution or better product design are great examples of value that will improve your chance of success. 

Excerpted with permission from Instec. A complete collection of Instec’s insurance industry insights can be found here.

CJ Lotter

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CJ Lotter

CJ Lotter is the director of engagement management at Instec. He spent nine years as chief research and business development officer at the U.S. programs division of Willis Towers Watson.

Will IoT Upend Insurance? [Hint: NO!]

The IoT is supposed to be nirvana, but the reality is a tad uglier, of course, than the gurus tell us, as reality always is.

So many gurus and their ilk are looking for, hoping for, any technology or group of technologies to "disrupt" or otherwise upend the insurance industry. One of the latest hopes for transforming the insurance industry is IoT: the Internet of Things. Unlike mobility, social media, cloud computing, big data and associated data science-driven analytics, or blockchain, IoT will definitely upend the insurance industry. The IP-enabled sensors will help people stop or reduce losses before they occur or soon after the losses occur. Traditional insurers will run for the hills because their industry will be in shambles. Shambles, I tell you ! Nirvana achieved! The reality is uglier, of course There certainly are an expanding number of IoT devices appearing in homes throughout the country. A veritable panoply of devices popping up in the basement, the attic and every room in between. Even the front door bell ! (BTW, is anyone with an IoT door lock looking forward to the day when the cloud service maintaining the door lock goes down? Perhaps when you have bags of groceries in your arms or after a long day at work, and you just want to get into your OWN HOME?) The reality is a tad uglier, of course, than the gurus tell us, as reality always is. The IoT-laden Pom Pom wavers neglect to pay as much attention to the ugly realities. Don’t you just want to tell them what they can do with their Pom Poms? Ugly realities of IoT The panoply of IoT devices is actually an expanding zoo of varied species that are blind to the existence of the other species in the zoo. The IoT devices don’t ‘talk to each other.’ There are no standards, including data standards that would enable the IoT devices to actually be …., well, useful. (Yes, I know that Apple, Amazon and Google are working on this issue – but today's situation is like cooking some hot dogs and finding out that the mustard is on the shopping list but that none is actually in your refrigerator.) Beyond not being part of a coherent integrated whole for the homeowner, each of the IoT devices represents a wonderful opportunity for hackers to spy on the family, and the devices create opportunities for distributed denial of service (DDoS) attacks on other targets by using the IoT devices as cyber-zombies or for other sorts of havoc (if the IoT device can alert the homeowner about water leaking, why can’t a hacker cause the IoT device to actually start the water leaking?) This brings us to another superb attribute of the IoT devices: Their security truly sucks. (That’s the technical term, folks; what can I tell you?) Can you (easily) reset the password on each of your IoT devices? Will the IoT device use two-factor authentication? See also: Insurance and the Internet of Things   Big Tech is coming (NOT) But, hey, insurers should still fear the Big Tech companies coming into the loss-prevention space, right? Why not fear these non-insurance players? Assuming security, privacy and trust become commonplace with each and every IoT device (and how many decades before that happens?), the firms offering loss prevention bundled with the IoT device (i.e.. warranty on steroids) only have to, at a minimum:
  • Augment their devices with networks of vendors that can repair/replace the IoT device OR the appliance itself
  • Ensure the vendors are bonded or have other insurance in case they don’t show up when they say they will or don’t actually do the repair/replace job the homeowner expects
  • Instill confidence in the homeowners that the vendors can be trusted to come into their homes in the first place
I imagine there might be Big Tech or platform players who want to get into the loss-prevention business. (OK, I can’t.) They might erroneously believe that setting up a FAQ web site will do the trick. Have a problem with the IoT device/appliance? Not a problem – click to this FAQ web site. And let us know if the FAQ page(s) were helpful. Oh, and augment that FAQ web site with voice-recognition units (VRUs) or chatbots that stick to their scripts. Yup, that’s the ticket: Make it hard for someone with a broken IoT device/appliance to actually talk to a human. That will endear the customer to the firms providing the service. Moreover, I hope that firms realize that if anything goes wrong repairing/replacing the IoT device/appliance, they will be sued. Oh, wait, that’s another opportunity for traditional insurance – these firms will need to purchase liability insurance (drat it all). Why not upend the insurance industry? What has the insurance industry ever done except keep society, families, individuals and businesses operating in times of war, famine, plague and recessions? What a horrendous societal effect: helping clients manage or mitigate risk in a legal, regulatory manner through the centuries of civilization. See also: Global Trend Map No. 7: Internet of Things   Don’t insurers realize that an integral part of their value-add is helping VCs and other investors (and conference organizers) to generate revenue off the insurance industry? Why can’t the insurance industry accept that even these human vampires have a right to exist and profit? Oh, why?? What will happen? Really? Will IoT upend the current insurance industry? Will being able to prevent losses upend the current insurance industry? No. The league tables of P&C insurers (whether personal or commercial P&C) will remain as they are for many, many, many decades to come. I believe that traditional insurers will create or strengthen their own networks of vendors to repair/replace either IoT devices or appliances and potentially bundle lower premiums (where insurance regulators allow). So, sorry … no upending or disrupting of the insurance industry. Not an iota of upending. This article was originally published on Rabkin's Opinions.

Barry Rabkin

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Barry Rabkin

Barry Rabkin is a technology-focused insurance industry analyst. His research focuses on areas where current and emerging technology affects insurance commerce, markets, customers and channels. He has been involved with the insurance industry for more than 35 years.

How to Thrive in Auto Insurance

Carriers with data-driven solutions that anticipate key life events can engage consumers at the right time, in the appropriate context.

When shopping for an auto insurance policy, consumers have greater access than ever to a quick and easy quote. Insurers continue to invest in improving the consumer experience, particularly the digital experience; a consumer can now get a quote from a mobile device while waiting in line at the grocery store! With the majority of insurers making improvements, it has become challenging for insurers to adequately compete for attention, let alone new customers. The secret is to understand and execute on a strategy that aligns with the shopping and switching habits and preferences of today’s customers. Shopping Habits During Renewal Windows A 2019 analysis of the U.S. auto insurance market by LexisNexis Risk Solutions has revealed that as many as 62% of policies are shopped off-cycle or outside the traditional renewal window. At every consumer’s fingertips is access to a slew of carriers’ price-comparison tools, mobile apps and websites that prepopulate with consumer data to expedite the quote process. With consumers empowered to shop for a better deal, it’s no surprise that 40% of U.S. auto insurance policies were shopped in the past year, and that 78% of policyholders have shopped their insurance within the past five years. See also: 3 Reasons to Use Online Marketplaces   To complement the LexisNexis Risk Solutions proprietary market insights, we recently commissioned a national study of over 2,000 auto insurance policyholders to better determine motivations for why consumers are shopping. The respondents were classified into three categories based on their auto insurance shopping habits over the past year – recent non-shoppers, shoppers and switchers. There were significant shopping differences among the respondent groups in how they research and purchase insurance. Recent Shoppers vs. Non-Shoppers:
  • Recent non-shoppers said they only pay some attention to their coverage and price at time of renewal and are more likely to research in-person, purchase through an agent and renew their policy automatically.
  • Shoppers, on the other hand, said they are more likely to review coverage and price very closely, research online, contact independent agents, purchase their policy online and renew their policy within 30 days of receiving notice.
These stark differences underscore why carriers need to pay attention to these behaviors and adapt their strategy to address these shopping and switching patterns to make sure they can retain their existing customer base. Price Is King and Tops Loyalty When it comes to insurance shopping, price was cited as the No. 1 reason consumers decided to switch insurance carriers, and the price difference doesn’t have to be as large as one might expect; a savings of $100 or less was enough incentive for 45% of all switchers across income levels. Even if a carrier offers a competitive price this year, it doesn’t mean the consumer will remain loyal. Half of shoppers in the study told us that they expect to shop again in the next year, with one in five expecting to switch carriers when they do shop. This data illustrates the impulse consumers have to shop to make sure that they’re getting the best deal. It’s only a matter of time before a consumer makes the jump to a carrier offering a better rate or easier application process. Knowledge Is Power If carriers don’t identify these behaviors and adapt their strategy to address these shopping and switching patterns, they will struggle to retain their customer base. We know price is the primary motivation for consumers to shop and switch, but carriers have an opportunity to use the data available to them about a consumer’s life events to engage and retain their valuable policyholders before they shop. Life events that generally have the most influence on auto insurance shopping include: adding or removing a driver, buying or leasing a vehicle, decreasing household income, buying a house, getting married or divorced and moving. With 65% of consumers expecting a life event to occur within the next one to two years, now is the time for carriers to review their book of business and monitor and anticipate when consumers are shopping. See also: The Insurance Lead Ecosystem   Carriers that implement data-driven solutions that monitor and anticipate key events can engage consumers at the right time and in the appropriate context to better accommodate their new or changing coverage needs. Without a robust, active risk management process, you may only know that a policyholder is shopping when it’s too late. An insights-based approach helps create opportunities to deepen loyalty and retention, even in a price-based, commoditized market. Consumer insights can put you in the driver’s seat with both prioritizing your most valuable policyholders for retention outreach and creating revenue opportunities with existing and potential customers. Download the Insurance Shopology Report here.

Adam Pichon

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Adam Pichon

Adam Pichon serves as vice president and general manager of the U.S. auto vertical for insurance at LexisNexis Risk Solutions.

Need for a Dedicated Coding Language

A unified, dedicate language for programming will help big data and life insurance finally speak the same language,

Insurance is rooted in data innovation. Wide swaths of modern statistics and probability were first devised to accurately price, predict and manage risk. But insurance’s pioneering position has faltered in recent years. While today’s economy is ablaze with revolutionary advancements in big data and computation, the insurance industry has been uneven in its adoption and application of cutting-edge data technologies. One study found that just 20% of the data collected by insurance companies is usable for strategic analysis. Attempts to incorporate big data and machine learning into insurance products tend to occur on an in-house and ad hoc basis. High financial stakes and strict regulations already complicate adoption of big data. The lack of a formalized system or computer language for interfacing with the available tools, technologies and data can also obstruct progress. This is why the life insurance industry as a whole, and actuaries, in particular, are in dire need of their own unified, dedicated programming language. As the CTO of a startup working with big life insurance companies, my team recognized this pressing need and committed ourselves to writing a programming language to help fill the gap. To understand the distinct challenges of applying technical innovations to the insurance industry, it is essential to first peel back the complex layers behind computer applications in general. Computers have come a long way since their earliest days as room-sized mainframes with punch-card readouts. But, at their core, all modern computers still reflect this hard-wired legacy. Graphical interfaces and polished applications might make today’s computers more user-friendly, but every action and instruction must still be translated and abstracted into binary machine code to be computed on. See also: A Game Changer for Digital Innovation   Now, this is not to say that developers sit typing their code as zeroes and ones. Rather, modern programming languages use their own, distinct shorthand, which is then compiled into code readable by hardware. However, the particular output logic required varies by computer architecture. GPUs operate differently than CPUs, which operate differently than cloud computing frameworks. Therefore, the trend has been to write general purpose languages (GPL) that focus on accommodating the widest range of uses to a particular machine or architecture. Instead of optimizing for a specific problem or use-case, GPLs ask the programmer to learn a new language and apply it to their given domain. The unique contours of the life insurance industry add a layer of difficulty. Regulations governing insurance are among the strictest and most byzantine of any industry. And beyond the issues of compliance come the extraordinary financial and social stakes riding on the integrity of insurance products. Core pillars of the private and public sector are propped up by the accurate, reliable management of risk. Insurance models running on shaky code could turn a tiny software bug into tens of millions of dollars in losses, the eventuality of which is amplified by the enormous complexity of accurately calculating risk five, 10 or even 25 years into the future. Seeing these issues firsthand inspired development of the Atidot LIA (Language for Insurance and Actuaries). What my team and I realized when approaching this challenge was that what initially looked like one problem was actually three distinct but related issues. The first issue was the substantial technical demands of carrying out the tasks that actuaries would demand of big data. Cleaning and anonymizing raw data, modeling it properly, testing and executing on a laptop or workstation and ensuring all code passed formal verification – these intricate operations would be a baseline requirement of any function. After addressing the fundamental complexity of insurance operations, the next issue was simplifying the syntax and optimizing legibility for domain experts who might not be professional developers. By building in insurance-specific entities, data models and analytics models for several use-cases, LIA allows actuaries to speak the language of insurance instead of memorizing the arbitrary variables of Python, Visual Basic or C++. Lastly, the unification of all necessary functionality into a syntactically legible framework would enable frictionless integration with machine learning models and accelerate time-to-market for new actuarial products. In other words, actuaries could write, debug and deploy big data in terms they could easily understand. Harmonizing function and syntax would help resolve some of the major roadblocks facing data integration. The current tension between the enormous promise of big data for the life insurance industry and the difficulty of developing dedicated software contribute to a compromise worse than the sum of its downsides. Today, actuaries looking to incorporate big data or machine learning are forced to cobble together homegrown solutions using a patchwork of languages and tools. Otherwise, they must rely on dedicated developers who lack the domain expertise to fluently translate actuarial needs into proper code. This disconnect creates friction and stilts progress. See also: The Opportunities in Blockchain   However, by empowering actuaries to translate their domain expertise into instructions usable by cutting-edge technologies, a dedicated programming language will help align the existing talent in the industry with the untapped potential of data innovation. Modeling insurance is increasingly becoming a multi-disciplinary challenge, and a more precise, specialized programming language will help foster collaboration and jump-start innovation. In other words, our vision is to help big data and life insurance finally speak the same language

Barak Bercovitz

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Barak Bercovitz

Barak Bercovitz co-founded Atidot following a 10-year career as an R&D technological leader in an elite intelligence unit of the Israeli Army. He was responsible for initiating and leading various projects in his unit with a focus on software development, artificial intelligence, machine learning and big data.

Insurtech 2020: Trends That Offer Growth

Consumers demand greater transparency, a higher level of service and on-demand solutions from their carriers and agents.

The insurance industry has undergone a transformation over the past five years. Once manual and paper-based, insurance professionals now recognize the overwhelmingly positive impact technology has had on efficiency and customer relationships. We can expect the acceleration of tech-enabled customer experiences that promote dynamic customer interactions and empower the insurance industry to deliver tailored solutions and products to meet customers’ personal risk advisory needs. Here are a few of the innovations we will see take off in 2020.
  • Pay-as-you-go car insurance. This unique approach to car insurance is especially appealing for urban consumers who own a car but rarely drive it. Rather than forcing occasional drivers to spend money on the same caliber of coverage as someone who drives every day, on-demand insurance means car owners can activate coverage only when they need it or pay per mile. The program requires a significant investment in technology that provides direct, self-service options for consumers, but we’ve already seen Liberty Mutual and Metromile offer this flexibility. We can expect many of the larger brands to begin offering similar options.
  • Self-service capabilities. Sometimes it’s just not feasible to call an agent when a need or question arises. Modern consumers increasingly want the convenience of DIY options to allow them to secure coverage or access information on their own schedule. To meet that demand, we’ll see self-service portals offer a wider range of features, including risk rating, on-demand premium quotes, home inventory solutions and claims processing. There’s also a growing demand for virtual adjuster technology and drone/satellite integration that help speed claims processes. Many agencies aren’t aware that their carrier partners even offer these tools, so be sure to ask.
  • Smart home claim avoidance/prevention tech. You’re probably already familiar with tools that track driving habits and offer discounts on auto insurance. A similar tech is emerging to help homeowners head off costly insurance claims on some of the most common mishaps. For example, a large portion of claims are related to water damage, such as a pipe bursting or an old water heater that fails. By implementing smart home sensors, automated controls and other Internet of Things devices, insurers can help homeowners mitigate the damage. For example, a sensor installed on a water heater can help monitor its structural integrity and remaining useful life, giving homeowners a heads up if it looks like a leak is imminent. In addition to offering premium discounts for participating in such a program, carriers might also provide incentives for replacing risky appliances ahead of time to avoid the risk of claim. Other solutions might involve installing a flood sensor or automated water control valve, which would send a mobile notification if a pipe bursts while no one is home, or even automatically shut off the water to prevent major damage. Some carriers already offer smart home kits for free to avoid these types of claims, and, while some homeowners might be a little concerned about privacy issues at first, I expect we’ll see this become table stakes soon.
  • Deeper data insights to drive business growth. With threats of a potential economic slowdown beginning to percolate, we’re starting to see signs of a hardening of the market in commercial lines. In many cases, premiums are rising, and business customers are looking at all options to save money and reduce costs. Agencies need quantifiable data and insights from smart analytics to help commercial customers strike the right balance of risk, coverage and cost.
That means the demand for industry-wide data analysis will grow substantially, as agents and carriers need measurable and accurate insight into what’s going on across industries — what customers in similar business sectors are buying, what the risks are and what are any potential gaps in coverage. Combined with their experience and knowledge, comprehensive industry analysis tools will enable agents to see the big picture and give business customers data-backed recommendations to ensure they receive just-right coverage. See also: Is Insurtech a Game Changer? It Sure Is   The future is tech-enabled In the coming year and well beyond, consumers will increasingly demand greater transparency, a higher level of service, and on-demand solutions from their insurance carriers and agents. This means adopting innovative technology will become a norm rather than a novelty as the industry digitizes to provide a more modern experience. The good news: A wide array of insurtech solutions are now available, providing accessible and affordable tools for even the smallest independent agencies. Adopting insurtech solutions can not only improve agency efficiency, allowing agents to spend more time with customers, but also help agencies spot opportunities for growth. This powerful combination can deliver substantial ROI for investment and position your agency as a modern, tech-savvy partner for both consumer and commercial customers.

Is Transformation Losing Steam?

In a word, no. Interest and application in personal lines are still strong because of UI and AI. But some scenarios are good news/bad news.

Technology adoption in personal lines has been going on for a long time. Because of the early advent of personal auto data standards, technology adoption has been fairly easy (always a relative term). Many insurers have staked their industry competitive advantage on data and analytics – Progressive comes to mind. Others have been early adopters of advanced payment technologies – USAA is a great example. So, is it time for transformational technology adoption to plateau or even dip in the personal lines segment? SMA has been conducting a survey on this very topic over the past decade. As one would expect, early results showed a good deal of learning and strategizing, with cautious investment. Over time, investment ramped up, as did implementations. But what about current results? Is the hype wearing down conviction? Without reservation, we can state that adoption is not losing steam. The recently released SMA report Transformational Technologies in P&C Lines: Insurer Progress, Plans and Projections reveals that transformative technology interest and application is strong. In particular:
  • New user interaction (UI) – Chatbot technology and text messaging technology are keeping this area high on everyone’s list.
  • Artificial intelligence (AI) – Given all the iterations of AI in the marketplace, the possibilities for adoption are almost limitless, and insurers are definitely keeping initiatives in motion.
Now, I don’t think that anyone reading this blog is stunned that UI and AI are still rolling in personal lines. They both will be for a long time due to the opportunities that keep arising and the strong bottom-line impact. However, the survey does show some noteworthy things – and not for their “rolling along” status.
  • There is a good news/bad news scenario developing in the UI/AI results. Many insurers are putting all their investment eggs into these two baskets and ignoring – or at best shortchanging – other transformational technologies. It is very hard not to run toward one or two areas that are delivering early value. However, insurers need to have an even view of all the transformational technologies that affect customers.
  • The SMA survey asks responders to identify the business areas that transformational technologies will affect. One of the choices is claims. Anyone who has read my recent blog Claims – Caught Between a Rock and a Hard Place – No More! will understand that I am a huge fan of claims workers. They have a super-hard job, one that is at the very heart of what insurance companies are all about. The troublesome thing is that survey results show that claims impact was sometimes fairly low in areas where it should not be.
See also: Commercial Lines Embracing Change   In all, the personal lines transformational technology report covers 11 technologies. It also provides a view of the impact of these technologies on 12 business areas. The trick is keeping the technologies and business impact areas in balance in terms of strategies and investment. Not every insurer will find business value in all 11 technologies; the key to keeping inertia at bay will be making conscious and well-considered decisions.

Karen Pauli

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Karen Pauli

Karen Pauli is a former principal at SMA. She has comprehensive knowledge about how technology can drive improved results, innovation and transformation. She has worked with insurers and technology providers to reimagine processes and procedures to change business outcomes and support evolving business models.

4 Trends in Insurance in the New Year

Brokers and agents must keep up, constantly looking for ways to interact in the ways that digitally savvy consumers want to interact.

The pace of technical innovation continues to be top of mind in the insurance industry. About 96% of insurance executives say innovation at their companies has increased over the past three years. And global investment in insurtechs hit a record $3.26 billion through the first three quarters of 2019, according to Deloitte. It’s clear 2020 will see a continuation of technology advancement within the industry. Following are four trends we are seeing on the horizon: 1. User Experience — Carriers, agents and consumers all want the same thing: for the insurance buying process to be fast and easy. Consumers want to research plans, compare options and buy insurance products when they need them on the device(s) they choose, often on their mobile phone (more than half of all search queries in 2019 came from mobile, Google says). And consumers prefer a tailored experience. According to Accenture, 90% of insurance executives say that integration of customization and real-time delivery is the next big wave and competitive advantage. Additionally, nine out of 10 insurance executives believe a tailored approach will give companies a competitive edge. The firm says the ability to fulfill consumers’ needs at the "speed of now" will be the way to stay competitive, with the world available at consumers’ fingertips via smartphones. Digital expectations have evolved, and there’s an opportunity to deliver a much better customer experience in the insurance industry. Technology has enabled a world of extreme customized and on-demand experiences. The insurance industry must harness this technology to deliver the superior customer experience that consumers are quickly coming to expect, to stay competitive. This mobile-first, real-time delivery approach has influenced our marketing, design and development teams to focus on a highly mobile-optimized user experience in every aspect of our operation. We expect a mobile-focused push for the insurance industry in 2020, from both the carrier and broker/agent sides. See also: Insurance Innovation’s Growth Challenge   2. Analytics — Data analytics is growing across industries, given its potential to help businesses get ahead. Data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain them and 19 times more likely to be profitable, McKinsey Global Institute says. The insurance industry is no different. The one constant across all our largest and most successful partners is their obsession with data and reliance on specialized technology. One such example is with customer relationship management (CRM) companies. CRM companies (Salesforce, and others) are developing industry-specific integrations, such as conversion endpoints, to track performance metrics, allowing for more real-time recording of important metrics. Insurance companies that take advantage of these tools have a major competitive advantage over those that do not, due to their ability to accurately measure and track important metrics like customer long-term-value (LTV), conversion rates of lead data and marketing return on investment (ROI). 3. Sales Enablement — Increasingly, carriers and agents are seeking more information, content and tools to engage buyers and help them to move to purchase, as well as address future needs post-purchase. Use of sales-enablement tools is on the rise, with only 20% of organizations reporting using them in 2013 and over 60% using them in 2019, according to CSO Insights. Agents want to understand who the lead is, what the person needs and how agents can best help drive more effective communications and fuel analytics and future programs. Agents also need these systems to work with other technologies—from mobile app, to CRM—to enable access to real-time information and a more seamless process. 4. Compliance — Compliance will and should remain a top priority for the industry. As consumer data protection becomes more of a focus in the media, we can expect to see more states moving toward a more European GDPR type data protection policy. California is one of the first states to adopt such a policy with the recently adopted California Consumer Privacy Act (CCPA), which came into effect Jan. 1, 2020. With more legislation focused on protecting consumers, we expect a stronger push toward industry-standard software to verify a company’s right to contact consumers. See also: Blurring Boundaries Drive Innovation   In a world that is moving toward better technology solutions daily, it is important for carriers, brokers and agents to keep up with these changes and constantly look for ways to interact the way that digitally savvy consumers want to interact.

George Mueller

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George Mueller

George Mueller is VP, sales and operations for NextGen Leads, specializing in driving targeted and validated sales leads to carriers, insurance agencies and independent agents in the health, Medicare and auto insurance industries.

How Much Exercise Prolongs Healthy Life?

Wearables and self-reported data can provide Personalized Activity Intelligence (PAI), which measures cardiorespiratory fitness.

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I bought a new mountain bike this summer. I already had two perfectly good bicycles in the garage, but there’s nothing like a new toy to get you motivated. Hitting the trails these days involves monitoring my data. I’m interested to test myself using Personalized Activity Intelligence (PAI), a health score that measures cardiorespiratory fitness (CRF). PAI draws heart rate activity from wearables, such as Fitbit and Apple Watch. It uses that information, along with self-reported data, to guide me toward the most beneficial amount of exercise for my body. Using all that data, the weekly effort I put into physical activity is translated into a single PAI score. Maintaining 100 PAI reduces my risk of cardiovascular disease and early death. I might like to live longer now that I’ve spent EUR2,500 on this new bike…. PAI takes account of my resting and maximum heart rate over a seven-day rolling period, adjusted for exercise intensity to reflect my VO2 max, a measure of CRF. Cycling should increase my heart rate above a threshold, and into the CRF training zone, generating PAI points. Consistently maintaining 100 PAI will derive the health benefits. PAI requires several weeks of activity data to properly attune to my VO2 max, but my first five rides provide an indication of what’s to come (see Figure below). PAI uses the first ride data to begin calibrating the algorithm to me -- the score is irrelevant. My second ride ends abruptly with a puncture and a fall, but by ride four I’m back in the zone, and by ride five back in the woods. My average heart rate dropped over the first four rides, which suggests that my fitness reserve was decent and that I’ve quickly added some heart health to the equation. Although my average speed was consistent, the effort involved measured by heart rate and, ultimately, the points earned, trend downward. See also: How to Link Heart Health to Insurance   It’s clear that longer duration coupled with higher attained heart rate scores more points. I must up my game because the algorithm calibrates to my personal heart effort. With PAI, very low-intensity exercise doesn’t contribute to increased levels of CRF, while fitter people with higher heart rate reserve face a tougher threshold to accumulate PAI points. Now the PAI algorithm is adjusting to my profile, and I’m discovering the effort required to earn a protective score. I go back out on the bike for ride five and earn 75 points; the maximum possible in one day. This isn’t a surprise. The route is longer and more challenging, and I ride harder because I’m already feeling fitter (see Figure below). The algorithm will continue to adjust to my exercise behavior over the next few months. As my CRF increases, I will discover that running on a treadmill for 30 minutes is less fun and nets me fewer points. I will find that my daily brisk walking and average of 6,000 steps contribute but do not raise my heart effort enough to strongly influence my CRF. Running and walking will supplement my PAI score, but to score 100 -- enough to affect my long-term health and get good value out of this bike -- well, that simply requires greater effort. For further background. read my blog Heart Health - Why Linking It to Insurance Is a Winning Formula.