“The future is here, it’s just not very evenly distributed.” — William Gibson

In his 2003 book, “The Slow Pace of Fast Change,” author Bhaskar Chakravorti highlighted how powerful innovations in technology and business often suffer slow adoption. He illustrated how, in a networked world, individuals, companies and regulators are all interacting, watching each other, guessing and second-guessing which investment choice is right. Often, the conservative choice is hard to dislodge. But when alternatives reach a tipping point, change can be dizzyingly fast. Insurance, a traditionally slow-changing industry, has more than its fair share of headwinds to innovation. It is a fragmented industry, compounded by: state-by-state regulation; an extended value chain of retail and wholesale distributors through carriers; reinsurers and capital markets; and a plethora of orbiting service providers. This fragmentation has inhibited transformational change and led to a prevailing view that, through continuous improvement, industry players can always adapt and catch up to change. This fragmented marketplace has traditionally protected incumbents. However, predators are circling. Insurtech, Silicon Valley-backed software companies, are looking to deliver insurance solutions. They observe the structural inefficiencies in the industry — that agents and brokers work through every day — and see red meat, tantalizing opportunities for new and disruptive paradigms. How are traditional agencies to adapt and stay competitive in the face of this threat? Disrupting the distribution model You can see the signs of coming disruption. Usage-based telematics (Progressive), peer-to-peer insurance models (Friendsurance), e-aggregators (PolicyGenius) and Internet of Things (IoT) companies are offering insurance coverage embedded with their products (autonomous vehicles). In 2015, venture capital companies invested $2.65 billion in insurtech with the intention of, at the very least, shaking things up. See also: 2017: A Journey Toward Self-Disruption   Some see the traditional agency model as living on borrowed time. Debates rage about the unique role and value that agents and brokers provide. When they really want to scare us, potential disruptors talk about “the Uber of insurance,” promising to transform the role of the agent to create a completely different customer experience. This transformation is most advanced in personal lines where digitalization is facilitating straight-through processing and is reducing the need for human intervention in policy processing. By analogy, think of people doing their own taxes online, where data-drive technology and intuitive user interfaces supplant human-driven, client intimacy. But more complex commercial lines are not immune to disruptive transformation. Digitalization, automation, analytics, embedded devices and telematics provide powerful tools to be integrated into new service and business models that can considerably change the value proposition for insureds. How the customer defines “the job to be done” While highly attuned to these possibilities, I align with those who see the role of independent agents remaining relevant well into the future. But there is a caveat: agents must truly and expansively fulfill their core promise to provide “peace of mind” to their insureds. I am often struck by the notion that the “job to be done” by retail agents is to provide “peace of mind.” It is not enough to provide a piece of paper and a commitment to represent the client’s interests in the event of a loss. Increasingly, peace of mind means providing information seamlessly, when and where the client wants it, via a user-friendly interface, backed by data and tools to help prevent losses (rather than simply mitigate or retrieve them). One agency principal recently noted that it was imperative “to make the friction points go away” in the risk management process. But this is only the starting point. Consider your organization. How much of your employees’ time is devoted to increasing your clients’ peace of mind? Or even understanding what peace of mind really means for your clients? By contrast, how much time is spent on “compliance activities,” busy work and redundant processing? While most insurance professionals are highly service-oriented, most insurance activities are not — tipping the scale in the opposite direction. Developing client intimacy and institutionalizing that knowledge into daily practices is critical. This is because agents and brokers have what direct writers, software companies and device manufacturers will struggle to attain: trusted adviser relationships. This is the key asset to protect and enhance. How to make your organization future-ready You might think the first thing to do after reading this article is investing in new online systems, portals and user-experience consultants. This is secondary. The first thing to do is get your operational house in order. Look internally at your service operations and understand how aligned your business processes are to your business strategy. This may seem counterintuitive, but, to improve customer intimacy and deliver peace of mind, focus first on internal operations. Streamlining operations is the foundation of the most successful innovation programs. Simplifying operational complexity increases transparency and strategic focus. Reducing process variability eliminates waste and inefficiency. Most agency leaders don’t realize how much time producers and service teams spend on redundant and non-core activities. This time can be reinvested in deepening an understanding of client preferences, purchase habits and risk profiles that will ultimately have an impact on loyalty and retention and will enhance the new business value proposition. Creating internal capacity is not rocket science. It is achieved through operational best practices such as increasing strategic visibility so employees can better align priorities; segment accounts; standardize ad hoc tasks; source the right work to the right person; and improve the operational IQ of your people. Operational analytics additionally provide insights into which accounts or lines of business are profitable, which are dilutive and what to do where there are gaps. Where once employees were under pressure to meet client needs, compete on price, put out fires and clean up backlogs, new, internal capacity will be discovered and directed to writing more profitable accounts, improving customer intimacy and innovating around digital channels and data-driven risk-prevention business models. See also: Insurance Disruption? Evolution Is Better   While the threats of disruption from insurtech are real, the outcome is not a foregone conclusion. Today's agency will suffer decline, but tomorrow's agency is within our grasp — not by saddling an already-complex operational environment with more sales people and systems but by building an organization on a foundation of operational and process excellence. In doing so, the agents and brokers of tomorrow will assert their relevance and long-term competitiveness by delivering their clients the promise of peace of mind more expansively than ever before. What does peace of mind mean to your organization?

Disruption in the market is threatening to isolate some insurers, keeping them on the outside of new opportunities. But many insurers are embracing the competitive pressures and shifting market boundaries to position themselves for growth. They are navigating their organizations through healthy changes as a part of an overall plan for transformation. We all know that change will often bring some painful challenges. To help insurers anticipate some of those challenges, we have been looking at preparations and steps insurers can take to stay on course. In our first blog in this series, we discussed the groundwork for leading change in your organization — with very practical advice on what leading change really involves. In our second blog, we looked at empowering change among the people involved in it. We discussed how change is personal and how insurers need to consider its impact down to an individual level. In Part 3, we’re going to step into the middle of managing change. What challenges are you likely to encounter once you have started? Are there ways to keep the organization on course, foster engagement and improve the odds of transformational success? We’ll start by looking at the changes within the organization’s business framework. Establish the right kind of foundation Organizational change management is often driven by the insurer’s need to build a new business framework that will operate as a cohesive, integrated and flexible unit. That framework may include new technologies, processes and products, items that are nearly always in flux. So it is important to establish a foundation that you can build on so that you can adapt and change whenever market shifts happen without changing the essential structure of the core. See also: How to Lead Change in an Organization   The foundation will be built to accept change as a fact of life within a dynamic marketplace. It will contain less rigidity and more resilience. It will prepare the organization to effectively handle quick course corrections when strategy shifts or the market changes — or even when teams uncover some detail they may not have envisioned at the outset. Once this foundation is in place, it means that discovery and innovation can happen on the fly, course corrections are no big deal and ideas are much simpler to test. Think of communication as a fabric Because change plans may not be firmly fixed, and because change can be difficult for people to understand, frequent communication is crucial. It needs constant attention to keep people engaged. You can’t communicate too much. However, when most leaders think of communication, they may tend to focus on formal communication, saying things like, “We are putting out a newsletter,” or “Every month we are holding a transformation update meeting.” These are good things, but they treat messages as broadcasts, with very little interactivity. In the real world, the best change communication looks more like a fabric that is woven with equal parts formal and informal communication, as well as both message threads and listening threads. It deliberately overlaps in areas so that a blanket of acclimation and understanding will bring the corporate culture and individuals along at the proper pace, all while acknowledging their value and the importance of including their perspectives. Formal communications — such as newsletters, e-mails and update meetings — ARE important. They are important for clarity. They act as signals regarding time and workload. They keep high-level messages in front of people, bringing the organization under a universal umbrella. Every effort should be made to communicate key messages through on-site meetings with executive leaders participating. Informal communications are also vital. Planned or unplanned one-on-one conversations are potentially more effective than newsletters because they are two-way and you can guarantee that the message was delivered. You can also listen carefully to any concerns or feedback. Tailoring high-level messages to points of individual impact is crucial to maintaining engagement. It is also helpful for managers to keep a journal regarding some of their more detailed conversations for later reference. What is important is that leaders and change agents think of communication, not as a supplemental component to the real work of transformation, but as a mission-critical part of any change effort. Actively manage risk We often hear within project methodologies that we are to expect some level of risk. That doesn’t mean, however, that we are to accept risk while sitting down, waiting and watching for the results of failure. The best way to treat risk is to actively manage it, and the most clear-cut methods for actively managing risk are to grade success and to catch errors quickly. Here, we employ some tried-and-true philosophies that deserve a more detailed understanding. Fast fail forward There is a common misconception in the term fast fail forward that having failures is actually a good thing. In reality, immediate success without failure is ideal. Fast failing forward simply acknowledges that failures are a fact of life, so the best we can do is to identify them quickly, embrace them and then move forward or around them. If there is an issue, it should be dealt with. The faster it is dealt with, the better your chances are for success. To identify problematic issues quickly, managers should time-base project milestones, saying, “In the next three months, we need to accomplish these five things.” After those items are accomplished or even while they are being accomplished, they should be measured. What is going right or wrong? Teams should provide feedback. If goals aren’t time-based, they can just keep rolling and aren’t likely to be measured. If some sort of feedback isn’t required, course corrections can’t be made. Projects with tight analysis, quick feedback and correction are unable to veer widely off course. Even if a transformation project is incredibly successful and if few issues are ever found, time-based milestones and measurements are valuable in the confidence that they can lend the team. Foster open communication The need for feedback returns us to the topic of communication because the wrong kind of feedback will simply damage and delay the process in ways that may be worse than ignoring the issues. Healthy feedback requires openness. First, you, as a change leader, need to resolve to be open in communication. This doesn’t mean losing tact in conversation and unburdening your gripes or finger pointing, but it means acknowledging clear issues without a focus on blame. Issues are a common place for fires to start. Personalities ignite. Invisible walls go up. Politics burden forward progress. Some personalities, for example, will fight against the failures while others will correctly understand that the struggle is against the issues that are at hand. If you guide everyone toward focusing on the issues, your teams will often unify behind the solutions instead of dividing and hiding behind roles and responsibilities. Meetings should be a place for open discussion, encouraging members to be open with each other and open with themselves and helpful in meeting issues head on. See also: The 4 Secrets to Managing Change   An effective leader will model openness by admitting course errors or mistakes and even by acknowledging the assistance given by someone else to make course corrections. Your efforts and words will help build a culture of quick accountability and decisive issue resolution. Instead of apprehensive team members who think, “We really ought to do something about that,” you’ll have a group of observant change leaders who say, “I see an issue. Let’s deal with it right now.” In my next blog series, we’ll take an in-depth look at why insurers need to consider customer experience as their primary motivator for modernization and change. I hope you’ll join me.

For more than a decade, Americans have been trained to assess and buy insurance products as commodities. This is partly thanks to commercials by Geico, the biggest advertising spender in insurance for many years, which has pushed the concept that “Fifteen minutes can save you 15%,” portraying policies as “the same,” where the only differentiator is the price. Some have dubbed insurance's being viewed as a commodity as the industry’s biggest challenge. On top of price-centric buying behavior, most consumers who are required to purchase certain insurance products — such as medical and auto — expect to have a wide selection and may switch insurance carriers at a blink of an eye. With competition increasing, big data and associated technologies provide timely opportunities by reshaping the modern insurance landscape. The insurance business model typically comprises four parts:

• Underwriting — where insurance companies make money.
• Investment — where insurance companies invest money.
• Claims — where insurance companies pay out (the cost factor).
• Marketing — where insurance products and services are promoted and often advertised.

Insurance companies have always used data in each part of the business model — to assess risk, set policy prices and to win/retain consumers. Previously, insurers would formulate policies by comparing customers’ histories, yielding a simplistic and not-very-accurate assessment of risk. Today, our increasing ability to access and analyze data as well as advancements in data science allow insurers to feed broader historical, continuous and real-time data through complex algorithms to construct a much more sophisticated and accurate picture of risk. This enables insurance companies to offer more competitive prices that ensure profit by covering perceived risk and working within customers’ budgets. Such prices, or setting policy premiums, come from underwriting. In this post, we will focus on an underwriting use case in the highly competitive auto insurance space, where accuracy of risk assessment and rate setting ultimately drive the insurers’ profitability. Future posts will address other parts of the insurance business model. More accurate (and competitive) pricing for auto insurance underwriting Auto insurance may be the most competitive part of the insurance marketplace. Customers shop around (often marketed to by price-comparison services) and change insurers at will. To offer competitive premiums that allow profitability, auto insurers have no choice but to assess risk as accurately as possible. See also: Why Data Analytics Are Like Interest   In auto insurance, insurers use both “small” and “big” data. David Cummings explains the two as: “Traditionally, underwriters have developed auto insurance prices based on smaller data — such as the car’s make, model and manufacturer’s suggested retail price (MSRP). But ‘bigger data’ is now available, providing far more information and allowing insurers to price policies with a better understanding of the vehicle’s safety. From manufacturers and third-party vendors, insurers can learn about a car’s horsepower, weight, bumper height, crash test ratings and safety features. That big data helps insurers create sophisticated predictive models and more accurate vehicle-based rate segmentation.” As data increasingly becomes the lifeblood for insurance companies, the combination of big data and analytics is driving a significant shift in insurance underwriting. For example, faster processing technologies such as Hadoop have allowed insurers like Allstate to dig through customer information — quotes, policies, claims, etc. — to note patterns and generate competitive premiums to win new customers. The data and analytics movement has also made room for newcomers like Metromile to enter the market. Although the company started out with no proprietary data of its own, Metromile has quickly gained customers and collected data with a new model: auto insurance by the mile. This entrance of Metromile into the auto insurance space has both disrupted the industry and put pressure on incumbent insurance providers to make advances with their own models. In auto insurance underwriting, a number of ways to use new data to achieve more accurate pricing have gained attention:

• Using usage-based insurance (UBI)
• Leveraging external data
• Leveraging real-time data

Usage-based insurance UBI can be used to more closely align premium rates with driving behaviors. The UBI idea is not new — there have been attempts to align premiums with empirical risk based on how the insured actually drives for a couple of decades. In 2011, Allstate filed a patent on a UBI cost determination system and method. Progressive, State Farm and The Hartford are just a few examples of other companies that are embracing UBI methods in underwriting. Technological evolutions like the Internet of Things (IOT) and all its attendant sensors provide new ways to capture and analyze more data. The UBI market has flourished and is expected to reach $123 billion by 2022. The U.S., the largest auto insurance market in the world, will lead the way in UBI marketing and innovation in 2017. With UBI’s market potential, there has also been a rise in business models such as pay-per-mile insurance for low-mileage drivers using UBI methods in underwriting. Embracing UBI methods in underwriting is no small feat, because of the huge amounts of data that must be collected and integrated. Progressive collected more than 10 billion miles of driving data with its UBI program, Snapshot, as of March 2014. For the most part, the data focuses on mileage, duration of driving and counts of braking/speeding events. These are all “exposure-related” driving variables, which are considered secondary contributors to risk. They can be bolstered with external data such as traffic patterns, road type and conditions, which are considered primary contributors to risk, to create a more accurate picture of an individual driver’s risk. Leveraging external data The idea of using external data is also not new. As early as the 1930s, insurance companies combined internal and external data to determine the rate for policy applicants. However, more recently, the speed of technological advancements has allowed insurers to dramatically redefine and improve their processes. For example, customer applications for insurance today are significantly shorter than before, thanks to external data. With basics like name and address, insurers can access accurate data files that will append other necessary information — such as occupation, income and demographics. This means expedited underwriting processes and improved customer experiences. Some speculate that all insurers will purchase external data by 2019 to streamline their underwriting (among other things). Another consideration is that the definition of external data has been evolving. Leveraging external data in an auto insurance risk assessment today may mean going beyond weather and geographic data to include data on shopping behaviors, historical quotes and purchases, telematics, social media behaviors and more. McKinsey says, “The proliferation of third-party data sources is reducing insurers’ dependence on internal data.” Auto insurers can incorporate credit scores into their underwriting analysis as empirical evidence that those who pay bills on time also tend to be safer drivers. Better access to third-party data also allows insurers to pose new questions and gain a better understanding of different risks. With the availability of external data like social data, insurers can go beyond underwriting and pricing to really managing risks. External data doesn’t just go beyond telematics and geographic data; it may also have real-time implications. Leveraging real-time data Real-time data is a subset of the rich external data set, but it has some unique properties that make it worth considering it as a separate category. The usage of real-time data (such as apps that engage customers with warnings of impending weather events) can cut the cost of claims. Insurers can also factor data such as weather into the overall assessment at the time of underwriting to more accurately price the risk. In the earlier example of using external data to shorten the underwriting process, accessing external information in real-time and checking with multiple sources makes the information in auto insurance application forms more accurate, which, in turn, leads to more accurate rates. Underwriters can also work with integrated sales and marketing platforms and can reference data such as social media updates, real-time news feeds and research to provide a more accurate assessment for those who seek to be insured. Real-time digital “data exhaust” — for example, from multimedia and social media, smartphones and other devices — has offered behavioral insights for insurers. For example, Allstate is considering monitoring and evaluating drivers’ heart rate, electrocardiograph signals and blood pressure through sensors embedded in the steering wheel. See also: Industry’s Biggest Data Blind Spot   Insurers can influence the insured’s driving behaviors through real-time monitoring, significantly altering the relationship with each other. A number of insurance companies, such as Progressive — in addition to the pay-per-mile insurer Metromile — are monitoring their customers’ driving real-time and are using that data for underwriting purposes. Allstate filed a patent on a game-like system where drivers are put in groups. Those in the same group could monitor driving scores in real-time and encourage better driving to improve the group’s driving score. Groups can earn rewards by capturing better scores. Conclusion There’s no doubt that the risky business of insurance is sophisticated. The above examples of leveraging UBI, external data and real-time data merely scratch the surface on data-driven opportunities in auto insurance. For example, what about fraud? Efficiency and automation? Closing the loop between risk and claims? Because only 36% of insurers are even projected to use UBI by 2020, those that embrace data-driven techniques will quickly find themselves ahead of the game. While it’s outside the scope of this post, we should note that leveraging data and methods shouldn’t be done without careful consideration for consumers. As consumers enjoy easier insurance application processes, as well as having more products to choose from and compare prices on, increasingly they will want to understand how these data and analytics techniques affect them personally — including their data privacy and rights. As we pause and reflect on how data and analytics have driven changes in auto insurance underwriting, we welcome questions and discussions in the comments section below. In the future, we’ll examine other ways the insurance market is becoming more data-driven, including the changes that data and analytics are driving in auto insurance claims and the rising focus of marketing. This article first appeared on the site of Silicon Valley Data Science. 

When dawn broke on the morning of Sept. 8, 1900, the people of Galveston, Texas, had no inkling of the disaster that was about to befall them. The thickening clouds and rising surf hinted that a storm was on the way, but few were worried. The local Weather Bureau office, for its part, gave no reason to worry; no urgent warnings were issued, and no calls were made to evacuate. But by late afternoon it became clear that this was no ordinary storm. Hurricane-force winds of more than 100 mph were soon raking the city, driving a massive storm surge that devoured almost everything in its path. Many tried to flee, but it was too late. By the next day, more than 8,000 people were dead, the greatest loss of life from a natural disaster in U.S. history. Fast-forward to September 2008 when Hurricane Ike threatened the same part of the Texas coast — but this time it was greeted by a well-informed populace. Ike had been under constant surveillance by satellites, aircraft reconnaissance and land-based radar for more than a week, with the media blasting a nonstop cacophony of reports and warnings, urging those in coastal areas to leave. The city of Galveston was also well-prepared: A 17-foot-high seawall that had been constructed after the 1900 storm stood ready to protect the city, and government-flood insurance policies were available to residents who were at risk of property loss. Unlike in 1900, Texas residents really should have had little reason to fear. On their side was a century of advances in meteorology, engineering and economics designed to ensure that Ike would, indeed, pass as a forgettable summer storm. See also: 5 Techniques for Managing a Disaster   It didn’t quite work out that way. Warnings were issued, but many in low-lying coastal communities ignored them — even when told that failing to heed the warnings meant they faced death. Galveston’s aging seawall turned out to be vulnerable; it was breached in multiple places, damaging roughly 80% of the homes and businesses in the city. The resort communities to the north on the Bolivar Peninsula, which never saw the need for a seawall, fared even worse, witnessing almost complete destruction. And among the thousands of homeowners who suffered flood losses, only 39% had seen fit to purchase flood insurance. In the end, Ike caused more than $14 billion in property damage and 100 deaths — almost all of it needless. Why are we underprepared for disasters? The gap between protective technology and protective action illustrated by the losses in Hurricane Ike is, of course, hardly limited to Galveston or to hurricanes. While our ability to foresee and protect against natural catastrophes has increased dramatically over the course of the past century, it has done little to reduce material losses from such events. Rather than seeing decreases in damage and fatalities because of the aid of science, we’ve instead seen the worldwide economic cost and impact on people’s lives as hazards increased exponentially through the early 21st century, with five of the 10 costliest natural disasters in history with respect to property damage occurring since 2005. While scientific and technological advances have allowed deaths to decrease on average, horrific calamities still occur, as in the case of the 230,000 people estimated to have lost their lives in the 2004 Indian Ocean earthquake and tsunami; the 87,000 who died in the 2008 Sichuan earthquake in China; the 160,000 who lost their lives in Haiti from an earthquake in 2010; and the 8,000 fatalities that occurred in the 2015 Nepalese earthquake. Even in the U.S., Hurricane Katrina in 2005 caused more than 1,800 fatalities, making it the third-most deadly such storm in U.S. history. In our book “The Ostrich Paradox,” we explore six reasons that individuals, communities and institutions often under-invest in protection against low-probability, high-consequence events. They are:

1. Myopia: a tendency to focus on overly short future time horizons when appraising immediate costs and the potential benefits of protective investments;
2. Amnesia: a tendency to forget too quickly the lessons of past disasters;
3. Optimism: a tendency to underestimate the likelihood that losses will occur from future hazards;
4. Inertia: a tendency to maintain the status quo or adopt a default option when there is uncertainty about the potential benefits of investing in alternative protective measures;
5. Simplification: a tendency to selectively attend to only a subset of the relevant factors to consider when making choices involving risk; and
6. Herding: a tendency to base choices on the observed actions of others.

See also: Are You Ready for the Next Disaster? We need to recognize that, when making decisions, our biases are part of our cognitive DNA. While we may not be able to alter our cognitive wiring, we may be able to improve preparedness by recognizing these specific biases and designing strategies that anticipate them. Adapted from The Ostrich Paradox: Why We Underprepare for Disasters, by Robert Meyer and Howard Kunreuther, copyright 2017. Reprinted by permission of Wharton Digital Press.

In the early ’60s, Roger Maris and Mickey Mantle hit a remarkable number of home runs — including famous, back-to-back four-baggers that, according to Yogi Berra, were the reason he famously quipped, “It’s déjà vu all over again.” While spring training is still a bit away, we’re in the thick of tax season, where legions of scammers are swinging for the back wall. According to the IRS, there was a 400% increase in phishing and malware incidents during the 2016 tax season. With the April 15 filing deadline still feeling as far away as the Green Monster from home plate in Fenway Park, Berra’s other dictum — “It ain’t over till it’s over” — has never been more true. My book, “Swiped: How to Protect Yourself in a World Full of Scammers, Phishers and Identity Thieves,” goes into great detail about the various tactics cyber criminals use to lure you, but the most important thing you can do to keep yourself scam-free this tax season is educate yourself on the most prevalent risks out there. As ever, the best advice is to file your taxes as early as possible. Tax-related identity theft is primarily aimed at grabbing your tax refund, and scammers are creative, sophisticated and persistent and move very quickly once your information is in hand. Armed with your Social Security number, date of birth and a few other pieces of your personally identifiable information, which if you have been involved in a data breach (you can check here to see warning signs and view two of your credit scores for free on Credit.com) is likely available on the Dark Web, people are furiously filing fraudulent tax returns online. See also: Implications for Insurance Taxation?   Here are three scams to bear in mind as the tax season is upon us: 1. Phishing There is no bigger threat than phishing. By now, it is a home truth that there are phishers out there. Catfishing is a regular part of the popular imagination, and phishing emails hit our inboxes with the same regularity as the various promotional emails we get from retailers and media outlets. Phishing emails take many forms, but they are most commonly pointed at getting enough of your personally identifiable information to commit fraud in your name (identity theft). They also commonly contain a link that places malware on your computer. These programs can do a variety of things (none of them good), ranging from recruiting your machine into a bot-net distributed denial-of-service attack; to placing a keystroke recorder on your computer to access bank, credit union, credit card and brokerage accounts; to gathering all the personally identifiable information on your hard drive. Here’s what you need to know: The IRS will never send you an email to initiate any business with you. Did you hear that? NEVER. If you receive an email from the IRS, delete it. End of story. Oh, and the IRS will never initiate contact you by phone, either. That said, there are other sources of email that may have the look and feel of a legitimate communication that are tied to other kinds of tax scams. 2. Criminal tax preparation scams You learned how to do homework in school for this reason: Not all tax preparers are the same, and you must vet anyone you’re thinking about using well before handing over a shred of your personally identifying information. Get at least three references, check online to see if there are any reviews and call them. Here’s why: At this time of the year, tax prep offices that are actually fronts for criminal identity theft tend to pop up around the country in strip malls and other properties and then promptly disappear a few days later. Make sure the one you choose is legit. 3. Shady tax preparation Phishing emails may not be aimed at stealing your personally identifiable information or planting malware on your computer. They simply may be aimed at getting your attention and business through enticing (and fraudulent) offers of a really big tax refund. While these preparers may get you a big refund, it could well be based on false information. Be on the lookout for questions about business expenses that you did not accrue, and especially watch out for signals from your preparer that you are giving him or her a figure that is “too low.” Other soft cons of shady tax preparation include inflated deductions, claiming tax credits to which you are not entitled and declaring charitable donations you did not make. Bottom line here: We’re all connected these days, and chances are you will get caught, so just make sure you are working with someone who follows the instructions. (Yes, they’re complicated, and that’s why it’s not a bad idea to get help.) See also: New Worry on ID Theft: Tax Fraud   As Berra said, “You can observe a lot by watching.” Tax season is stressful even without the threat of tax-related identity theft and other scams. It’s important to be vigilant, because, to quote Berra all over again, “If the world were perfect, it wouldn’t be.” Full disclosure: CyberScout sponsors ThirdCertainty. This story originated as an Op/Ed contribution to Credit.com and does not necessarily represent the views of the company or its partners.

The insurance industry is on a collision course. As in the 1933 science fiction novel "When Worlds Collide," a small number of individuals with insight have recognized this fact and are preparing for a new and different future, while many others are blissfully unaware of the impending danger. Okay, maybe that is a bit dramatic, but the traditional world of insurance is threatened by the rapidly encroaching digital world and insurtech. At SMA, we foresee a convergence of the traditional and the new that will create an updated generation of the industry rather than the disruption (and perhaps destruction) of the industry that some predict. Very few of the new entrants want to go it completely alone when it comes to meeting regulatory and capital requirements, underwriting the risk and managing the end-to-end insurance value chain. Instead, they tend to create value in specific areas that might mesh nicely into areas in need of enhancement at existing insurers. Thus, the emergence of convergence — or the bringing together of the new, innovative companies and capabilities with the traditional elements of established businesses. See also: A Mental Framework for InsurTech What is this convergence likely to look like? And, more importantly, what should insurers do to position themselves for success? If there is a single word that describes how convergence is playing out in the industry, that word is "partnering." One way to look at the partnering opportunities is to combine the best of the old with the best of the new in five key areas.

• Distribution: About 30% of all insurtech startups are, in some way, connected with the distribution space. These companies are born digital; often create an innovative customer experience; and leverage mobile, artificial intelligence, gamification and other technologies. Distribution is a prime area for partnering, and all of these new distribution firms are looking for insurer partners.
• Risk: The rapidly expanding availability of data on perils (especially real-time data) offers new possibilities for improved risk selection and pricing. New predictive models and scores; more location-based data with greater levels of precision; and new real-time behavioral data all create differentiating opportunities for insurers. Much of this new capability is available through firms that could be great partners.
• Product: Innovation is the name of the game with products. There are many insurtech firms that are creating ideas for micro-insurance, usage-based insurance, behavior-based insurance and parametric insurance. Many innovators are seeking insurers with underwriting capacity and a solid distribution network.
• Customer service: New options are emerging for areas such as billing, claims and other areas related to customer service. New and emerging technologies are especially relevant here, with drones, blockchain, mobile payments, AI, wearables and other tech creating new options. Many of the insurtech firms have innovative offerings in very specific areas and look for proof-of-concept and piloting opportunities with insurers.
• Operations: Many tech companies — both incumbent and new firms — offer solutions to take operational efficiency to the next level. Robotic process automation and other AI techs lead the way, but other technologies offer improvements, as well. Video streaming and smart glasses for claims can improve claim operations. Again, the companies that are creating these new solutions are eager to partner with insurers.

See also: Why AI Will Transform Insurance The future doesn’t have to be a disaster scenario for the insurance industry. In fact, the potential is here for the industry to reach new levels of profitability and societal impact. Partnering to leverage emerging technologies, new business models, innovative products and new ways to reach customers can result in the best of both worlds for everyone, delivering new value to customers and growth for the industry.

Small- to medium-sized insurers that want to remain relevant should heed the call of innovation. There has been a lot of press lately about how innovation can help insurers overcome growth obstacles. It’s no secret that the insurtech startups of the world, for which digital innovation is the hallmark, are garnering the attention — and funding — of venture capitalists and larger carriers, but how is that innovation affecting small- to medium-sized (SMB) insurers? In some ways, SMB insurers are vulnerable to a fate like what is being experienced by department stores such as Kmart and JC Penney or the local bookshop, all of which hang on by a thread as the online and big-box retailers take control of the market. Market demographics contribute to this pressure, as emerging generations of customers — with demands for anytime, anywhere digital access to policy, claims and account information — put an additional burden on carriers. It’s no wonder that SMB insurers may feel overwhelmed at the thought of keeping up with the likes of IoT, machine learning, business intelligence or robotic process automation. But many SMB insurers assume (incorrectly) that they don’t have the resources necessary to climb aboard the innovation train. See also: Top 10 Insurtech Trends for 2017   Consider the business culture in which SMB insurers (small mutual insurers, commercial workers’ comp carriers, municipal risk pools, captives and self-insured groups) operate. These carriers work within a known and predictable entity where budgets are firm — often the result of a formalized, collective group mandate. Smaller self-insured pools — such as public entities, under the scrutiny of their not-for-profit, state-controlled state insurance departments — are also frequently held to a more stringent set of business performance and accounting standards and metrics. But, like their larger counterparts across all lines of business, these smaller self-insured pools are expected to be efficient, productive and successful in every aspect of their operations, including core systems (underwriting, billing, claims), financial management and CRM/workflow. Unique Challenges Because of the financial and cultural boundaries under which they operate, many of these insurers — as well as many other types of small insurers — still must rely on Microsoft Office products or cobbled-together, aging, home-grown legacy solutions to support day-to-day business functions. This may mean that a single technology solution provider (or perhaps the insurer’s own, in-house IT staff) is responsible for the health and well-being of the organization’s technology footprint, architecture, back/front office, distribution, networking, communications and security. And, lately, those that rely on outside help for their IT function are faced with confusion and potential service delays as the surge in vendor merger and acquisition results in their trusted partner being gobbled up by a technology behemoth. The service-level agreement (SLA) may remain intact, but the larger vendor will undoubtedly start pressuring the carrier to rethink outdated hardware and software. This pressure, along with the potential drop in personalized service that typically accompanies a large M&A deal, add to the SMB insurers’ challenges to remain competitive. In addition, the talent pipeline is drying up because of a retiring workforce. To replace these workers, what’s the likelihood that SMB insurers will be able to recruit top technology talent to manage an outdated AS/400 linked to a client/server front end? If it sounds like I’m insinuating that smaller insurers should assume a victim mentality, that’s not the case. These carriers play a critical role in risk management, so they need to remain relevant. But these SMB insurers will not be able to overcome innovation-related growth obstacles until they better understand and embrace affordable technology innovation options that will make their jobs a lot easier. The first step is gaining an understanding of what’s possible — such as an affordable pay-as-you-go, as-needed migration of core systems and data to a software-as-a-service (SaaS) hosted environment, a gradual sunsetting of existing hardware and the gradual move to a digital platform that pulls all necessary functionality together for reliable, secure, front- and back-end operations. From there, SMB insurers can implement predictive analytics for use in claims, communications and even cross-selling. Even at a small scale, machine learning and artificial intelligence can help these carriers improve their claims function, customer service capabilities and more. See also: 4 Hot Spots for Innovation in Insurance   Risk-management changes within our marketplace — such as legislative issues, changing (read: younger) demographics, the advent of the sharing economy and the growing presence of disrupters -- will affect all lines of business and all sizes of insurers. The SMB insurers that will remain relevant will be those that hear the wake-up call and understand the path to innovation, that choose a stepped approach to business and technology relevance and that greet the future with an openness to what’s possible.

To sell an idea to stakeholders, buyers and users, we not only have to change what they think but how they think. Without the right mental model, they won’t see the problem, understand the benefits or choose to change. Mental models are like sorting hats; they are how our minds make sense of the world around us, the vast amount of information we process and intuitive perception of our actions and their consequences. They filter the signal from the noise.

For example, consider the mental model: "Life is like chess." If you believe this mental model, you’ll see life as a strategic game with winners and losers following set rules, and you may set the goal of winning. But if your mental model is that "life’s a beach," then you may see life as more fun, with no winners and losers and no rules. You may expect that forces beyond your control like the waves of the ocean can influence you but that you can use them to have fun.

See also: Innovation Happens at the Edge  

Often dubbed as the “Monaco of the East,” Singapore the red dot has beaten a path to steady economic progress and prosperity since the 1970s. Much of the success can be attributed to the vision of one man, Lee Kuan Yew, Singapore’s first prime minister, who reigned for more than 30 years, making him the world’s longest serving prime minister. He was unafraid of challenging popular ideologies. Right up to the end of his life, Lee believed in constantly adapting to the changing realities of the world and refreshing his mental map. He sought the views of experts in industry, academia, politics and journalism. But having processed their arguments, he did not let himself be swayed if he absolutely believed something else was in the best long-term interest of Singapore. I was drawn to his vision and chose to move to Singapore to experience the economic miracle. I have seen first-hand how one man has changed how people think and as a result transformed Singapore from the "third world to the first world in a single generation."

   

See also: How to Master the ABCs of Innovation 

Innovations that change the world need to be explained before they can be accepted. Brands that successfully sell their innovations have been able to change how we think, feel and connect with not only their products but ourselves and the world around us.

One of the most dangerous jobs in America is power-line maintenance. More than 330 people were killed last year due to falls and electrocution while working on power lines, and thousands more were injured. Now one energy company is employing sophisticated drones to monitor power lines, allowing workers to trade the sometimes-scary task of climbing way up a swaying tower in possibly lousy weather to check out a junction for a ground-based drone control and monitoring job. According to an AES exec: “We find that using drones, we can reduce the number of hazardous hours that it takes to do certain types of maintenance. And we can also enhance the efficiency of the business.” And AES is not just focused on aerial drones to reduce occupational risks. It recently announced a program seeking unmanned methods of evaluating energy production and transmission equipment. The risk here is intense heat; when something goes awry, it often takes considerable time for the site to cool down enough for a human to enter and figure out what’s happened. AES is looking for ways to use “unmanned technology” to get in quickly, assess the problem and fix it. See also: What Is the Future for Drones?   Measure is the company working with AES; Measure is deep into multiple ways to use drones in heavy industry. For example:

• shipboard workers using drones to check on container stability, possible fuel leaks, wiring and hoses
• firefighters using drones' heat-mapping capabilities to identify hotspots, vulnerable areas and trapped people
• tower workers using drones to keep nesting birds at bay

What does this mean for you? Fewer accidents, lower risks for workers, reduced workers' comp premiums.  And this is just the start.

The Japanese firm Fukokui Mutual Life Insurance has replaced more than 30 office workers with artificial intelligence (AI), in this case the famed IBM Watson. Watson, or one of its doubles, is in fact affecting nearly all industries in multiple ways. Eliminating workers is a major goal. But could Watson replace workers in workers’ comp? AI has been around for decades, but now with advanced technology it has fully caught on, and its applications are widely varied. AI is what drives driverless vehicles and operates machinery sans human involvement. More practically, AI enhances worker productivity, accuracy and efficiency. But AI should never reach workers’ comp if more pragmatic, technology-based strategies are implemented now. Replacing workers’ comp professionals with Watson is not feasible at this point or, I hope, ever. Yet, it is a wake-up call to the industry. See also: 10 Questions That Reveal AI’s Limits   Imagine injured workers navigating the workers’ comp system without claims adjusters and medical case managers. Picture Watson managing claims. It could make payments without difficulty and even review the bills effectively. Watson could also determine which claims are the most challenging and refer them to medical case management. Stop there! Envisioning Watson as medical case manager is a real stretch. Human interaction is central to effective medical case management. Likewise, Watson delivering claim management services without dialogue with the claimant would be spotty and unpleasant at best. Accuracy and efficiency under Watson management could be nearly perfect, but claim adjusting relies heavily on human interaction. Injured workers managed by Watson would feel victimized in a heartless system. The only recourse would be to litigate. Watson might have trouble with that. While replacing professionals with technology like Watson is going too far, it should prompt workers’ comp payers to engage current technology to improve processes and outcomes—just to keep up. Clearly, the momentum in every industry is more technology to gain efficiency, and workers’ comp cannot afford to lag. To stay in the game, technology designed to assist workers with task-relevant knowledge and decision support that makes them more accurate, more efficient and, yes, smarter is crucial. Watson will replace health insurance industry administrative workers fairly easily. Essentially, bills are paid if they match the benefit plan and the treating doctor is in the PPO. However, the workers’ comp industry is very different from general health and much more complex. The question is how can the workers’ comp industry optimize efficiency and productivity without discarding its professionals and alienating injured workers? The answer is to apply currently available predictive analytics technology to make WC professionals smarter, more accurate and highly efficient. Of course, that also spells profitability for the organization. Apply predictive analytics to understand historic data and the cost drivers inherent in it. Monitor the data continuously to identify risk conditions as they occur. Create apps that inform claims reps of conditions and events in claims that need attention in real time so action is taken early. Assist claims reps by providing information for decision support such as the probable ultimate medical reserve amount for a claim. Time and effort are saved, while accuracy and efficiency are gained. Rather than labor with decisions such as adjusting reserves, you can present a timely and accurate projection, optimizing efficiency. See also: Next Big Thing: Robotic Process Automation   Similarly, relevant information should be available for medical case managers so they can avoid searching for claim information and status. Timely alerts and shared information promote collaboration and integration of efforts between claims and case management decision-makers in the organization. Watson is thwarted.