Easy question, simple answer: They don’t. The implication is that an agent "skims" 15% commission off the top, as if (1) agents STILL get 15% commission on auto insurance, (2) agents don’t do anything to earn their meager commissions (like exposure analysis, product selection, claim advocacy, etc.), and (3) GEICO has no acquisition costs like advertising, sales and service staff salaries and benefits, etc. See also: How Basis for Buying Is Changing (Part 2)   The Florida Association of Insurance Agents (FAIA), the state affiliate of the Big “I,” has a blog area where agents can comment on staff blogs. Here is an agent’s response to a recent blog post: "I certainly don’t put myself in the ranks of Warren Buffett, and we clearly have a different target client than his GEICO brand does, but it is very interesting to look at their recent financial reports. "GEICO’s recent disclosure notes that it wrote 974,000 new policies last year. Sounds like they are hitting us hard. They also spent $1,400,000,000 on advertising last year. That’s 1.4 BILLION with a 'B.' "If you do the math, that is $1,437 per policy in acquisition costs just for advertising, not including other underwriting expenses. Now remember, they have another 21 million customers on the books already. I wonder how they like subsidizing all those new policies….” So, all you agents out there, how many of you get $1,437 commission on each auto policy? If that represents less than 15% of the premium dollar, then GEICO’s average auto premium would have to be about $9,600. Of course, that 15% claim might be a little off, perhaps by 100% or more? See also: How Agents Can Tap the Gig Economy   Thirsty for more? Read my blog post from six months and a day ago.

Several well-meaning experts in this space have written about the unsustainability of usage-based insurance (UBI) programs due to high costs and low returns. They argue that, when you add up all of the acquisition, technology and administrative expenses, as well as premium discounts or other incentives, insurers would need to see a significant (read, unrealistic) decrease in loss ratios just to “break even.” I’ve seen figures as high as 25%. This line of thinking assumes that insurers are evaluating their UBI programs with the same criteria they use to evaluate any new business initiative, which is some variation of a return-on-investment (ROI) formula using future cash flow analysis and managing to a minimum required threshold set by the chief financial officer. Sound familiar? Optimally, the decrease in loss ratio will be supplemented by an increase in policyholder retention and market-share growth, which in time would allow you to manage to your ROI objective. However, by evaluating and measuring opportunity cost and leveraging other progressive metrics such as policyholder engagement, insurers struggling to grow their UBI programs should be able to get the continued support they need from executives to see their programs through to success. See also: Insurtech: How to Keep Insurance Relevant Setting UBI Up for Success The challenge with UBI is in building a large enough base of active policyholders over a long time (say, 3-plus years) to allow for meaningful measurement of the impact of loss ratio improvement. To offer perspective on this, I’m reminded of a well-made and still highly applicable argument made by Clayton Christensen nearly 10 years ago in the Harvard Business Review. His aptly titled 2008 article, “Innovation Killers: How Financial Tools Destroy Your Capacity to Do New Things,” argues that one of the most misapplied paradigms of financial decision-making relates to fixed and sunk costs. In most companies, managers are biased toward leveraging existing resources that are likely to become obsolete quickly, and therein lies the rub – the strategy group is often split from finance, when in fact the two should be fully intertwined and moving forward with the goal of ensuring the long-term competitiveness of the business. Because that’s not likely to happen any time soon in most organizations, what’s the next best alternative when you’re being challenged by your management team for continued justification of your UBI program spending? I’m going to give you a couple of ideas. First, measure the opportunity cost of not continuing to innovate and present market-validated data to back your case. You can accomplish this by researching and compiling data on future projections of declining auto premiums, shrinking demographics of traditional car buyers and rapidly increasing severity loss costs. CCC’s 2017 Crash Course report, for example, provides in-depth analysis of repair costs, telematics, casualty trends and myriad other factors that contribute to the performance of the industry. Other research you can leverage includes the success stories of national UBI market players via their annual reports, as well as recent research from analyst firms and reinsurers on the proven business impacts of telematics over time. To quote Christensen again in the above-mentioned article: “The projected value of an innovation must be assessed against a range of scenarios, the most realistic of which is often a deteriorating competitive and financial future.” I think that pretty much speaks for itself in terms of the potential value of moving your UBI program into high gear. It took less than 10 years for 95% of insurers to adopt credit-based rating variables, and there is no reason to think that the adoption of driving behavior variables via telematics should be any different. Second, focus on a shorter-term performance metric that is easy to measure and highly important on one or more long-term traditional metrics. A good candidate for this is customer engagement, measured simply as the number of times a UBI participant interacts with your mobile app or web dashboard on a monthly or weekly basis. This metric has been proven to have a direct correlation to higher retention and increased customer lifetime revenue. In fact, CCC’s case studies with its telematics customers have shown an average increase of 30% in retention rates for UBI policyholders vs. non-UBI policyholders, with consumers interacting an average of 2.4 times per month via mobile. See also: Is Usage-Based Insurance a Bubble?   To ensure continuing success in your program, you’ll want to determine which high-impact motivators are most successful in driving customer engagement. The ability to do A/B and multivariate testing in pilots or soft launches is key in helping you rapidly and effectively find which motivators are most effective for the segments you are targeting. Open telematics platforms that allow you to easily set up and administrate these types of tests via a user-friendly web interface is critical here. Furthermore, having the flexibility to rapidly test market sentiment among your agents across various segments of your business can yield greater insight and allow you to maximize your participation rates and Net Promoter Scores. By seeking out and finding valuable metrics to support traditional innovation business cases, you can help win the internal support you need to continue to scale and grow your UBI program. At the end of the day, you simply can’t afford to be anything but a  first-string player in this high-stakes game.

Recently, an article was written on ITL (and published in the Six Things newsletter) that cautioned against the use of big data to change the customer experience when applying for insurance. The article demonized eliminating or even minimizing the plethora of questions required by carriers and, instead, using data from the public domain. In making his point, the author referred to a “startup called Aviva.” Aviva, in fact, is not a startup, but a FTSE 100 company that has revenue in excess of GBP50 billion, has 30,000 employees and has been around for more than 150 years given its Norwich Union and Commercial Union lineage. The article stunned me. The author's thinking seems to be of a different era. In no way am I suggesting that efforts by the insurance community to use data from the public domain to improve customers' experience is perfect, but the premise of the article showed little understanding for the depth and complexity of information sought by insurers to evaluate and price risk, and the burdens for customers and their agents to provide that information. The article also tried to simplify a complex subject into good versus bad because of specific instances of incorrect information sourced from the public domain. The evolution in this space is far more robust and advanced than the author seemed to understand. See also: When Big Data Can Define Pricing   As society has evolved, so have the sources and accessibility of information, and so has our decision making. We don’t rely on the first return by Google on a search engine or simply get a single return on a product search when seeking a product on Amazon. The same rules apply when humans make decisions – they seek input from multiple people. Insurtechs seeking to navigate the big data domain are addressing the challenge by applying this real world behavior -- reducing the demands for customer information by understanding the context and bringing data together from a variety of sources, often with a high degree of veracity. Terrene Labs, a SaaS provider to the carrier, MGA and broker community is among the most compelling examples. Terrene has managed to reduce the 150 to 200 questions required to place a property and liability, work comp and auto cover for small business customers (the $100 billion market of companies with as  many as 100 employees and $10 million in revenue) by requiring only four pieces of data. Terrene assembles data fragments from more than 900 sources (insurance-specific, non-insurance, private data sources, etc.) to generate all the information for a completed application (as well as additional relevant risk information not sought by carriers). Terrene does not have static rules of sourcing data (despite what the author suggested) but uses machine learning and artificial intelligence to dynamically source data based on algorithms that value veracity. The results are far more impressive and the process to achieve this far more complex, than the author of the referenced article seems to understand. A powerful example that illustrates the point is determination of NAICS or SIC code, which is the basis for all carriers' risk appetite selection and the basis for pricing. Terrene’s proprietary techniques are far more accurate than the process an agent CSR typically uses to determine class of business. A customer that identifies her business as a “cabinet store, maker and installer” could be properly categorized as a NAICS classification of 337 (furniture and related product manufacturing) or a NAICS code 444190 (kitchen cabinet store). The Terrene engine can properly determine which category is appropriate with an extremely high degree of accuracy. This accuracy ensures that appropriate carriers for this risk can be identified without the risk of rejection further into the submission/quoting process, frequently a pain point and a significant source of inefficiency and yield loss. Big data, if done well, can improve the quality as compared with a customer’s self-reporting, which typically has an element of bias. For example, in a surety context, over a large sample set from one carrier, none of the customers reported prior bankruptcies. The Terrene solution, in fact, determined that 16% had a prior bankruptcy. Similarly, powerful insights into risk profile that are typically not sought by carriers can now be generated. For example, Terrene profiles characteristics in the risk that are not consistent with self-reporting of profession or trade – one recent example was a home remodeler that carried an asbestos remediation license. See also: What Industry Gets Wrong on Big Data   The evolution of big data is a work in process, so companies are taking different approaches in their journey. One such example is a company that uses the Terrene capability to pre-populate an application that then can be reviewed and affirmed by a customer before a submission is made – a process that customers report is far more effective than self-completing a 200-question set (which typically takes two-plus hours), not to mention the substantial improvement in information veracity. Unfortunately, like the article referenced at the outset, not enough positive attention is being taken to understand these powerful advancements that leaders such as Terrene can deliver now.

As the insurance industry pushes ahead into the next decade, adapting to change and, in some cases, leading change, those committed to the industry and its purpose face an underlying tension that they all wish would just go away. They wish the industry were not so hated by the public. While "hate" is a strong word and potentially offensive, insurance definitely ranks toward the bottom relative to respect when compared with other industries, products and services. In my personal quest to end this problem, I find that you can learn a lot by examining the worst of the possible behaviors—that is, insurance fraud. Recently, my colleagues at Maddock Douglas and I engaged in some conversations with both LexisNexis and Swiss Re on this subject. Both organizations have some interesting lenses to look through. In fact, the three companies will be doing a webinar to share these views on Aug. 10. See also: Happy Producers, Happy Customers   First and foremost, it was surprising to hear how big the problem of fraud actually is. LexisNexis Risk Solutions, through a variety of sources, has reported that fraud costs the insurance industry more than $80 billion a year. There are many flavors of fraud, ranging from out-and-out intent to steal money from insurance companies all the way to “little white lies.” The ability to detect and size that behavior is very helpful in creating realistic expectations around costs and isolating areas for improvement. I find the white lies more intriguing and potentially helpful in understanding the problem because they are more widespread and harder to detect. I suspect that some of that behavior stems from a lack of understanding about how insurance systems work, with consumers not necessarily realizing that “misbehaving” has a cost. Swiss Re has some interesting insights about the behavior, as well. They've leveraged behavioral economics to learn that the context, order and style in which we ask basic underwriting questions can make a big difference in the truthfulness and accuracy of answers. I believe there is yet another lens that we can put on this challenge: social norms. Insurance is a social construct; however, we treat it like a product. Social constructs—such as electricity, cable TV, public transportation, public parks, schools and community resources—are shared. The behavior of a few with respect to those shared constructs affects the many. It is the many who have responsibility for their preservation, especially when they start to break down. However, that big picture is often lost after those social constructs age way past the people who invented them. So perhaps it’s time to reinject social norms into the insurance conversation, helping the public see how their behavior affects others. Some great role models for this type of shift would be:

• The Keep America Beautiful campaign from the 1970s
• Mothers Against Drunk Driving
• Quit-smoking campaigns

On the surface, it would seem like the common denominator is a giant advertising expenditure. While that may be true, there is another common denominator we can learn from—that is, a social label. Keep America Beautiful, best known for the crying American Indian, is the campaign that also created the term “litterbug.” “Don’t be a litterbug.” Litterbugs are socially unacceptable. But, prior to the invention of that term, it was socially acceptable to dump litter at a traffic light out your car window. Mothers Against Drunk Driving (M.A.D.D.) created the concept of the designated driver. The “DD” is a hero to those who like to have a good time but want to stay safe. Quit-smoking campaigns created the concept of “secondhand smoke.” Yes, scientifically proven, but, more important, the concept brought into focus the innocent victims, often children or nonsmoking co-workers. The result was ordinances and family rules banning smoking in many locations. Is there such a social label that can be created around “little white insurance lies”? The label could cast out the villains, glorify the heroes or spotlight a victim. My colleagues and I have done a little brainstorming on this subject, and there are some interesting ideas we will talk about during the webinar. See also: How to Get Broader View of Customers   The bigger question for the industry is whether this labeling is a job for a single brand or a coalition. In my opinion, either is possible with the right passion to make a difference. While the past examples all had large ad expenditures behind them, they were all invented before the internet existed, when ad spending was the lever that brands and coalitions would pull to raise awareness. However, today we have unlimited access to technology and social connectivity. Think about the success of the Ice Bucket Challenge. This social campaign raised $115 million for ALS research in just a few months. Why? It created millions of heroes. It let people, for a moment, feel what it was like to be a victim and then do something about it, either through raising awareness or raising money. Those who didn't participate were, socially, some level of villain. After all, couldn’t you sacrifice your comfort for a few seconds, or kick in a few dollars, for a good cause? Wow. Hmmm. Do you have any thoughts about how we could create that sweet spot within insurance? If so, I would love to hear.

Which sounds worse: getting shortchanged by a cashier at the grocery store or losing your life savings to a Bernie Madoff-type investment?The answer is obvious. Still, it’s a good metaphor for how to manage your healthcare investment and, more importantly, the glaring flaws in how healthcare is administered and delivered. First, some background. The Employee Retirement Income Security Act of 1974 (ERISA) was designed to protect employee benefits, including health plans. The person exercising authority over a health plan is a “fiduciary” and legally bound to act in the best interests of the participants. But, according to a recent article, chief financial officers (CFOs) are facing millions of dollars in personal liability suits due to a lack of “fiduciary oversight.” Whether the cause is negligence, omission or imprudent management, the result isn’t good: a potential lawsuit for the company and executive, mishandled or wasted money and shortchanged employees. Throw the Department of Labor into the mix (it's been keeping a close eye on 401k plan fiduciaries in recent years), and the choice is cut-and-dried: Most companies need to up their game. See also: A Way to Reduce Healthcare Costs   Here are the five biggest mistakes CFOs make when designing, purchasing and managing their health plans. 1. Taking a gamble. CFOs of middle-market companies are gambling with the organization’s healthcare by taking 19 to 125 times more risk than they should. Why would any organization risk $500,000 or $1 million when it can reduce exposure to less than $8,000? It’s even more shocking at large companies when the bottom line is exposed to unnecessary healthcare overspending. Healthcare managers wager millions of dollars by ignoring reducible risk, and the mistakes hurt the bottom line. C-suite executives are surprised when I explain why “best practices” don't work—until I show how many millions of dollars are trapped inside their healthcare budget. 2. Surrendering responsibility to unqualified departments and managers who don't have P&Ls. I always ask CFOs one simple question: "By a show of hands, who would hire a HR-level executive to lead a $100 million division of your company?" No CFO has ever raised a hand. Yet the company’s healthcare investment is often treated as an operating expense that’s delegated to operations managers who don't have the time or expertise to make the best-informed decisions. Too often, these decisions end up in the hands of consultants who, most often, will take a boilerplate path of least resistance by recommending "best practices" that only major in minor outcomes. 3. Not all healthcare costs are created equal. For many, health-plan management falls outside standard business supply chain cost-control strategies. So, shift perspectives: Negotiate the highest utility for every dollar invested in the healthcare supply chain. Hospitals, outpatient surgery centers, physicians and pharmacy account for more than 90% of claims, and all can be negotiated. Successful cost reductions must focus on four areas: wasteful spending, excessive fees, poor quality and non-transparent pricing. Who in his right mind would shop at a grocery store and fill up two carts, then leave knowing he’ll receive a bill 30 days later and only then be told how much everything costs? Well, that’s how most healthcare works. 4. Not involving senior executives. I always ask CFOs: "Which two 'best practices' are most effective in reducing the frequency and severity of your claims this year?" The CFO soon realizes that, despite a legacy of best practices, there has been negligible improvement, with millions left on the table. The CFO must be directly involved and recognize that healthcare investment is a capital allocation strategy—it requires the supervision of an executive with P&L responsibility. 5. Not knowing what you’re paying for. Most CFOs don't know whether their company’s medical plan pays retail, wholesale or institutional charges. Like with a 401k, it's a CFO's fiduciary responsibility to know the healthcare broker's and consultant’s total compensation. It’s imperative to ask the right questions to uncover where your dollars are going. Familiarize yourself with fees, commissions, bonuses, overrides, incentives, profit sharing, contingent fees, expense reimbursement allowances or performance-based compensation—because they all add up. See also: Healthcare Debate Misses Key Point   Being uninformed can cost your company a lot of money, or worse. When explaining in court that you consistently supervised and overpaid by as much as 10x for a poor-performing, low-quality medical plan, ignorance is no defense. So there you have it: five common mistakes to avoid when buying healthcare. Take ownership, talk to an expert and educate yourself on sourcing the best solution for your company. You really can’t afford not to.

Just like Batman and Robin, strong teams are made up of complementary partners. In the insurance world, this partnership is often the human agent and a technology counterpart. Take a Geico agent and the virtual assistant Kate. Kate’s AI-enhanced offerings and "always on" abilities serve as the perfect sidekick to the local insurance agent. As customer expectations have evolved, the insurance industry has had to change along with it. We’ve seen this with the rise of digitally native insurance companies like Hippo that streamline the application and sign-up process for homeowners insurance, as well as with more traditional organizations like Amica Insurance, which is revamping its digital strategies by working with IBM to give adjusters stronger tools to fulfill routine tasks. See also: Hate Buying? Chatbots Can Help   Today, anything short of a flexible, convenient and digitally mature experience is behind the times. It’s important for insurance companies to recognize that, given these advances and the diverse needs of policyholders, they will need to scale their offerings and implement more advanced services to support human agents. Though humans will never be replaced by chatbots, chatbots’ unique ability to personalize and automate processes has enormous potential in enhancing the relationship between the insurer and the policyholder. How Can Chatbots Enhance the Insurance Experience? Customers are becoming more and more comfortable with user interface (UI) technologies like Amazon Echo and Google Home and are exhibiting a more diverse set of expectations for digital capabilities in every facet of their lives. Chatbots can help supercharge insurance organizations with their ability to simplify everyday tasks. These virtual assistants have the potential to enhance efficiencies for both the insurer and the policyholder, especially when it comes to researching offerings, purchasing a policy and filing an insurance claim. Policy Exploration Researching different insurance policies can be a daunting task. It’s difficult for buyers, especially first-timers, to know what the best policy might be for their needs and budget. When looking at the insurance equation from the top of the funnel, chatbots have the potential to help win a customer’s business with their intuitive interface and educational support. Getting the right information up front is important for customers so that they aren’t surprised by anything down the line. Chatbots can process data at extraordinary speeds and help to make sure that customers are getting the right policy and the necessary information so they feel comfortable with their purchase. With the ability to quickly scan through the wealth of information on the internet and recognize user patterns, chatbots can ensure that policy offerings are accurate and tailored to the needs of the customer, helping insurance organizations make a great first impression. Purchasing When it comes to purchasing a policy, the process can be clunky, filled with unfamiliar industry jargon and massive amounts of paperwork. Chatbots can make the quote process much smoother for buyers by helping customers quickly navigate the intricacies of the buying process, while also simplifying it by auto-filling difficult questions with the assistance of third-party sources and natural language capabilities. Insurers are freed to work on more complex customer needs and issues without being bogged down by endless amounts of paperwork, leading to greater internal efficiencies. Claims and Payments The situations in which policyholders file claims don’t always happen within traditional business hours. The 24/7 nature of chatbots makes sure that customers have access to assistance when they need it, whether that means information about their policy or guiding them through what to do in the case of a car accident. The payment and claims process typically involves multiple steps, and the automated nature of chatbots can help streamline this experience in a way that helps both insurers and policyholders. A large number of calls that policyholders make to their insurance organization are about the claims process. Chatbots can field these calls and provide users with a complete look at the status of their claim in real time, just as if they were tracking a UPS package. Given that calls are typically about the status of a claim, chatbots are particularly good at fielding them because they can access this information within their database. See also: How Chatbots Change Open Enrollment   Looking Forward The insurance industry still needs a drastic digital transformation as it migrates from policy-centric strategies to more customer-centric ones. In addition to updating their technology, insurers need to shift their antiquated mindsets and processes toward innovation, especially as younger generations with higher digital standards gain greater purchasing power. If these organizations want their digital transformation to be sustainable, they’ll need to integrate digital mindsets throughout the culture of their organization, making sure everyone understands the value of digital investments and will continue to implement them. As it stands, just 42% of insurance organizations support a seamless user experience. If insurers want to satisfy users, they’re going to need to emphasize their omnichannel offerings, like chatbots, to create a solid foundation for further technology advancements. As the needs of the digitally savvy consumer become increasingly important, each insurance company will need to figure out how to stay relevant to this new generation, and having a chatbot by their side is a step in the right direction.

The U.S. insurance sector announced that deal value has more than tripled to $10 billion in the first half of 2017, compared with $2.9 billion in the first half of 2016. Activity remains robust in the brokerage sector. The largest announced deal in the period was the acquisition of insurance broker USI by an investor group including private equity firm KKR and Canadian pension fund CDPQ for $4.3 billion. Among insurers, megadeals have been affected by uncertainty in terms of the direction of tax and regulatory reforms, although some clarity has come by way of the implementation of the Department of Labor’s fiduciary rule. A healthy appetite for deals should continue in the second half of the year as insurers seek to divest capital-intensive or underperforming businesses, and newly funded PE-backed insurers continue to pursue U.S. insurance sector assets. Highlights of 1H 2017 deal activity Evolving nature of deals in 1H 2017 There were only three announced deals valued in excess of $1 billion, amounting to a total of $7.8 billion, in the first half of 2017:

• An investor group including private equity firm KKR & Co. and Canadian pension fund CDPQ completed a $4.3 billion acquisition of USI Insurance Services from Onex.
• In a separate deal announced in June 2017, USI agreed to acquire Wells Fargo Insurance Services in a transformational transaction. Terms were not disclosed.
• In May 2017, a special purpose acquisition company, CF Corporation, including funds affiliated with Blackstone and Fidelity National Financial, announced a $1.8 billion acquisition of annuities and life insurer Fidelity & Guaranty Life. The transaction followed the lapse of Anbang Insurance Group’s agreement to acquire U.S. Fidelity & Guaranty Life after failing to secure the necessary regulatory approvals.
• Canada’s largest P&C insurer, Intact Financial, acquired specialty insurer OneBeacon from White Mountains for $1.7 billion.

See also: Insurtech: How to Keep Insurance Relevant   Other significant deals emphasized interest in expanding digital capabilities, specialty offerings and small- to middle-market presence, as well as focus on managing capital, including:

• • An investor group including New Mountain Capital LLC, Achilles Acquisition LLC, acquired small to mid-size employee benefits agency One Digital Health and Benefits for $560 million.
  • Markel Corporation acquired SureTec Financial Corporation for $250 million and renamed its specialty and U.S. insurance segment Markel Surety Corporation.

Deals that did not meet our S&P screening, but are notable for their scale or intent, include:

• Travelers announced the purchase of U.K.-based Simply Business, a digital commercial broker, for $490 million.
• Aegon (Transamerica) offloaded its two largest U.S. run-off businesses, payout annuities and bank-owned/corporate-owned life insurance to Wilton Re via reinsurance.

Key trends and insights Sub-sector highlights

• Life and Annuity: The sector has been suffering through a persistent low-interest-rate environment that has weighed on insurers’ investment portfolios. Nevertheless, the U.S. Federal Reserve has raised the fed funds rate two times this year, and there are signs that other central banks are considering tighter monetary policies as inflation increases. Opportunities remain for insurers to exit capital-intensive or non-core businesses, with continuing investor interest in closed blocks and narrow concentrations. In a recent reinsurance deal, Canadian pension owned Wilton Re acquired two run-off blocks (annuities and COLI/BOLI) from Aegon/Transamerica.
• Property & Casualty: Deal activity declined in the first half of 2017, as companies continue to manage macro pressures. However, opportunities remain for small to medium-size companies to build much-needed scale through consolidation.
• Insurance Brokers: The segment continued to be the most active in terms of deal volume in 1H 2017. The most activity came from several serial acquirers buying regional brokers, further consolidating the market. The five most active acquirers were Hub International, NFP, Arthur J. Gallagher, AssuredPartners and Acrisure.

See also: Insurance Coverage Porn   Conclusion and outlook Even though announced deals have been light in the first half of 2017 compared with the second half of 2016, activity should intensify in the remainder of 2017 as insurers focus on cutting costs, achieving scale and enhancing and streamlining or consolidating dated technologies.

• Macroeconomic environment: The muted economic recovery, persistent low interest rates and geopolitical uncertainty continue to constrain insurers’ revenues and profitability. Life insurers have used both divestitures and acquisitions to manage the low-return environment and transform business models.
• Regulatory environment: Increased oversight and uncertainty have heavily influenced insurers’ business models and strategies, forcing many to exit businesses, often through divestiture. The current presidential administration appears to favor the easement of certain regulations, which could be a positive for insurers subject to the SIFI rule. Furthermore, the U.S. Department of Labor Fiduciary Rule has officially gone into effect, which may have implications for insurers that use exclusive agents.
• Technology: Insurers have been slower to adopt new technologies compared with banks and other financial services companies. But the times may be changing; insurers are increasing technology investments, including the recent acquisition of Simply Business by Travelers.
• Asian inbound interest: The past several years have seen Asian firms expand their footprint in the U.S. insurance market. While Asian investors maintain a global appetite, regulatory and shareholder skepticism remains a hurdle. A bid by Anbang to acquire Fidelity and Guaranty fell through in April, and China Oceanwide’s acquisition of Genworth has yet to close and is facing a new CFIUS review.
• Canada, too: Closer to home, there is evidence of increased appetite from Canadian buyers. In the first half of 2017, the second largest pension manager in Canada teamed up with KKR & Co. to acquire broker USI Insurance Services, and the largest P&C insurer in Canada, Intact Financial, acquired specialty insurer OneBeacon.
• Public offerings: Several major global insurers have responded to the low-growth environment in the U.S. with significant divestitures or restructuring. After receiving final approval in June, MetLife plans to spin off its U.S retail business, the new Brighthouse Financial, in August. A.XA announced in May its intention to exit its U.S. operations in a 2018 IPO. There is market speculation that other large insurance companies have similar divestiture or restructuring plans.
• Private equity/Hedge Funds/Family Offices: Insurance brokerage has historically been the most active insurance subsector for private equity given the limited regulatory environment, straightforward operating model and attractive, leverageable cash flows. However, private equity firms have been entering the life and annuity market with confidence that they are better investment managers than insurers.

At the 2017 annual PRIMA conference, Ariel Jenkins and Kevin O’Sadnick of Safety National led a conversation on the essential elements of school risk control programs. School visitor management consists of entrance hardening (add extra set of doors or windows, and visitors have to check in), criteria for visitors (parents, teacher visitors and grandparents), 100% use of photo ID for staff/visitors and use of security cameras. Violent, Combative and Disruptive Students De-escalation/assault cycle training should be able to recognize this behavior and early intervention and keep an event from getting out of hand. There need to be clear protocols that consist of restraint training and use of school resource officers. Violence against teachers needs to be reported and documented. See also: Future of Insurance: Risk Pools of One   Active Shooter Event Effective methods to reduce active shooters events are visitor screening procedures, school/district website content, training for staff (Run,Hide, Fight method), and lockdown procedures (general or emergency lockdown). Post-incident procedures include an emergency communication (is there a procedure in place and specific to each event?), PR/news/press releases and crisis and grief counseling. Controlling Special Education Risks

• 46% alleged discrimination against students with disabilities
• Claim of not receiving “free appropriate public education”
• Increased complaints related to retained and isolation

Is a special education teacher considered a high-risk job? Yes. There is more emphasis on motor skills learning activities. A student-assisted transfer requires hands-on physical assistance to move a student. The risk of these are biting, hitting and back injuries. The transfers are not normally voluntary. In a school setting, the safe patient handling policy should address the use of mechanical devices to the place of manually lifting and transferring students with disabilities. Training in positive behavior management and de-escalation. For a lift policy, best practices is 30 to 35 pounds maximum lift without equipment and no two-person lifts or transfers without using equipment. If a student cannot safely, reliably and cooperatively stand and pivot for a student-assisted transfer, use adaptive mobility devices. Social Media and Bullying There are different measures and different trends we can look at to create student and teacher interaction policies. Make sure to document any instances that occur. There are outside vendors that have training for monitoring social media. There need to be consequences and repercussions for bullying and social media intimidation. These policies and procedures need to be shared with parents. See also: Space, Aviation Risks and Higher Education   Risk management is ever-changing and evolving in K-12 schools. It is vital to stay informed and stay on top of emerging issues that can affect the safety of the staff and students in your school districts. It is important to create policies and procedures to ensure the safety of all involved.

Jeff Bezos just became the world's richest man. His creation, Amazon, is an incredible company. The consistency and breadth of innovation it has produced over the past two decades is awe-inspiring. Bezos is undoubtedly the force behind this relentlessness, and I find him fascinating to listen to and study. In the following 38-minute interview, he gives us a compelling glimpse into the mindset he’s created at Amazon that underpins its success. Some of the points struck a chord with me, so I’ve made a short summary below. The 3 principles of Amazon People see Amazon differently. Is it an e-commerce site, a retailer, an innovative tech company? Its products and services range from cloud computing, original content, direct publishing platform, Alexa and many other things. So how should we think about Amazon? Bezos sees Amazon more as an approach:

“We have a very distinctive approach that we have been honing and refining and thinking about for 22 years. It’s really just a few principles that we use, as we go about thinking through the different activities we work on.”

See also: Time to Rethink Silicon Valley?   Those few principles are: 1. Customer obsession This is the fundamental driving force behind Amazon’s business. Instead of, say, a competitor obsession, technology obsession or product obsession model. These other models can work just fine. A competitor obsession can be a very good strategy for some companies: You have to watch your competitors very closely. If they latch onto something that’s working, you duplicate it as quickly as possible. It means you don’t have to be a pioneer, and you don’t have to venture down many blind alleys. But there are disadvantages, and the customer obsession model is the one Bezos believes is right for Amazon, in combination with the following two principles. 2. A willingness, or even an eagerness to invent and pioneer This marries very well with the customer obsession. According to Bezos, customers are always dissatisfied, even when they think they are happy. They actually do want a better way; they just don’t know what that way should be yet. Customer obsession is not just listening to your customers, but it means inventing on their behalf. It’s not their job to invent for themselves, you must be the inventor and the pioneer for them. 3. Long-term oriented Bezos encourages his employees not to think in two- to three-year timeframes, but in five- to seven-year timeframes. People often congratulate Bezos on quarterly results, but for Bezos these results were actually baked in about three years ago. Today, he’s thinking about a quarter that’s going to happen in 2020. Next quarter, for all practical purposes, is probably already done and has been done for a couple of years. But the long-term mentality is not a natural way for humans to think. Bezos believes it’s a discipline that you have to train and build for.

“If you start thinking this way, it changes how you spend your time, how you plan, where you put your energy. Your ability to look around corners improves. Many things just get better.”

In conclusion, Amazon is an approach and a collection of principles that they embed into how they think and work. Failure and the importance of experimentation Despite being the world's richest person, and Amazon being wildly successful, what keeps Bezos sharp and focused? It’s the fear of Amazon losing its way in one of the key areas mentioned above. Or that they become overly cautious, or failure-adverse, and therefore become unable to invent and pioneer.

“You cannot invent and pioneer if you cannot accept failure. To invent, you need to experiment. If you know in advance that it’s going to work, it is not an experiment.”

Failure and invention are inseparable twins. But it’s embarrassing to fail. If you have a 10% chance of a 100x return, you should take that bet every time, but you will still be wrong nine times out of 10, and you’ll feel bad about every one of those nine failures, even embarrassed. Overcoming this fear is vital, particularly in the technology business. In technology, the outcomes can be very long-tailed, with an asymmetric payoff. This is why you need to do so much experimentation. As an illustration:

“In baseball, everybody knows that if you swing for the fences, you hit more home runs, but you also strike out more. But baseball doesn’t go far enough [as an analogy for technology]. No matter how well you connect with the ball, you can only get four runs. The success is capped at those four runs. But in the technology business, every once in a while you step up to the plate, and you hit the ball so hard you get 1,000 runs.”

This asymmetric payoff makes it obvious to experiment more, increasing the chances of that 1,000-run hit. It’s important to make this distinction on failure, though: The right kind of failure is when working on an invention, an experiment that you cannot know the outcome of. The wrong kind of failure is when you have some operational history in the task, where you know what you’re doing, but you just screw it up. This is not a good failure. An example from Bezos:

“We’ve opened 130 fulfillment centers now; we’re on the eighth generation of our fulfillment center technology. So if we opened a new center, and just messed it up, that’s not an experiment, that’s bad execution.”

Defining your big ideas Any entrepreneur, organization or governmental institution should identify their big ideas that encapsulate what they’re trying to do. There should only be two or three of these big ideas. The main job of a senior leader is to identify those important ideas, and then to enforce great execution on them throughout the organization. The good news is that the big ideas are usually incredibly easy to identify, and in most cases you’ll already know what they are. For Amazon’s consumer business, the three big ideas are:

• Low prices
• Fast delivery
• Vast selection

“How do we always deliver things a little faster? How do we always reduce our cost structure, so that we can have prices that are a little lower?”

See also: The Key to Digital Innovation Success   The big ideas are stable. They will most probably be the same in 10 years. Customers will still like low prices and faster delivery. No matter what happens with technology, these things will still remain true.

“When you have your big ideas, you can keep putting energy into them. You spin up flywheels around them, and they’ll still be paying you dividends 10 years from now."

Bezos also discusses machine learning, renewable energy and space exploration, but not once in the entire discussion does he mention the word "innovation." A reminder that those who really do innovate don't talk about innovation.

Just from casual observation, if “disruption” is the hot topic in industry media, self-driving or autonomous vehicles might not be far behind. I’ve read predictions that a proliferation of autonomous vehicles will be among us (or vice versa) in five to 10 years. Is that likely? I have my doubts, though I’m increasingly persuaded that the day is coming, even if it’s not clear how or to what extent the transition to autonomous vehicles will transpire and what impact it might have on our industry. Fortune magazine published an article titled, “What’s Taking So Long for Driverless Cars to Go Mainstream?” The article notes that “significant technical challenges remain unsolved" but opines that “societal friction” will be the greatest impediment to adoption, delaying full autonomy “for at least a decade.” I think that length of delay is highly optimistic. There is a LinkedIn discussion about this here if you want to join the dialog. The article discusses three societal impediments that could slow adoption:

• Ethics. If the vehicle recognizes that a wreck cannot be avoided and the choices are limited to running off a cliff and killing the vehicle occupants or ramming through a crowd of children, how will that decision be made, and who is going to be legally responsible for the consequences, if anyone?
• Job Losses. The article says there are four million jobs involving the transportation of people and property, not counting all of the support positions, along with other businesses that are transportation-related and dependent on human operators.
• Hacking. What are the possibilities of “weaponizing” wired vehicles? I’ve been writing about this for several years. Given the media attention to hacks of wired vehicles already taking place to illustrate vulnerabilities, what would happen if terrorists hacked into a gasoline tanker truck and sent it at 70 mph into an elementary school? With the “Internet of Things” (perhaps #3 on the list of industry hot topics), we well know the many vulnerabilities of everything from smart phones to internet-connected HVAC controls.

These are just three among many, many issues that must be addressed before ANY significant autonomous vehicle traffic is permitted. The article also cites reports that an Uber driverless vehicle ran a number of red lights last year. Aside from the loss potential, when that happens, who gets the law-enforcement citation? The vehicle? If someone is injured or property is damaged, who gets sued? Today, the vast majority of claims are due to driver error. When the inevitable autonomous vehicle claims occur, who gets sued…fleet owners, vehicle manufacturers, mechanics, software programmers or others we can’t even conceive of now? How will this change our legal system? See also: Driverless Vehicles: Brace for Impact   Another article that challenges predictions that we are no more than a decade away from significant autonomous vehicle use is “Self-Driving Cars: Flawless Ride? Carmageddon?” Questions it raises include: Does the entire roadway system need to be re-engineered to accommodate both autonomous autos and human-operated autos? How will millions of miles or roads and an inventory of conditions, signs, laws and special situations be kept up to date and communicated to vehicle systems? How will decisions be made when accidents are inevitable? What about software bugs? Questions I’ve raised in past writings include: How will an autonomous vehicle “know” that a traffic light is out? How will it detect a red light if the direct glare of the setting sun washes out the color? Will traffic equipment need to be re-engineered, and at what cost? How will it be tested and maintained? How will driverless vehicles respond to unanticipated road construction or weather conditions? How will they respond to circumstances not contemplated by their programming? With regard to software bugs, “rebooting” your car, unlike your PC or tablet, while moving at 70 mph may not be an option. Fellow insurance nerd Mike Edwards told me about driving through his neighborhood one day and noticing, by glancing under the chassis, several sets of little feet behind a mini-van parked in a driveway near the street. Although the posted speed limit was 30 mph, he slowed almost to a stop just in case a child ran into the street…which happened. Fortunately, he was able to just stop in time. Could an autonomous vehicle be programmed with that kind of awareness? I’m certainly not an expert, but I have my doubts. Multiply this kind of incident several million times a year. Finally, one of the more interesting commentators on autonomous vehicles is Thomas Frey, futurist at the DaVinci Institute and, according to his bio, Google’s top-rated futurist speaker. Here is a LinkedIn Pulse article he wrote: “25 Shocking Predictions About the Coming Driverless Car Era in the U.S.” His predictions include four million autonomous cars replacing 50% of all commuter traffic. In a city of two million people, only 30,000 autonomous cars might be sufficient to handle transportation needs. It’s still not clear to me how 150,000 people leaving the vicinity of an Ohio State vs. Michigan football game will be able to access a limited number of largely single- or dual-passenger autonomous vehicles in Columbus or Ann Arbor. I’m not even convinced that autonomous vehicles can effectively handle rush hour transportation without there being tens of thousands of vehicles idle during non-peak hours. Will people willingly share vehicles with strangers at close quarters, and how might that contribute to crimes against persons? Will people be OK with taking twice as long to get somewhere with slower traffic and possibly multiple drop-offs like airport shuttles today? Under most current laws, as much as 40% of state and local sales taxes could be lost if individual auto sales become a thing of the past…what are the funding alternatives? The same issue surrounds state and federal fuel tax revenue. Remarkably, Frey predicts that, within 30 years, fully 25% of current jobs will be lost due to autonomous vehicles (e.g., he says 80% of police manpower goes to traffic control and will largely be unnecessary). New York City would allegedly lose more than $2 billion in income from traffic fines alone. Airport revenues would plummet, given the claim that 41% of it comes from parking and ground transportation fees. On the upside, according to the author, we would save $500 BILLION annually in healthcare costs (though two other sources site the negative impact of fewer organ donations due to fewer auto accidents). The list, good and bad, goes on and on…take a look at his predictions at the link above, including one for the insurance industry. Are we moving not to a “sharing” economy but to a “hiring” or “renting” economy where there is little in the way of ownership of high-ticket items like homes or autos? Perhaps, though I’m not sure any of us can predict what is going to happen with any degree of certainty or say how soon it will happen. The closest large-scale implementation of semi-autonomous vehicles so far is probably our aviation system. Air transportation is highly automated, from take-off to landing, but the pilot(s) are able to take control if necessary. Even so, traffic control of aircraft is only marginally automated. Humans often prevent tragedy through the oversight, coordination and intervention of air traffic control centers all over the country with individual aircraft. This system has demonstrated itself to be quite effective, given the very low incidence of casualties associated with commercial flight. See also: The Evolution in Self-Driving Vehicles But this centralized, coordinated control aspect may be largely responsible for the success of the system. Unlike autos, no one is currently advocating that individual aircraft become autonomous. That’s interesting given that the number of aircraft in the air at any given time is tiny compared with the number of vehicles on the road, and probably no one would argue that there are a lot fewer structures and people to hit in the sky vs. a congested city. So, what makes the pundits believe that tens of thousands of individual autos can coordinate themselves effectively without some sort of centralized control or the ability to communicate between each other? Currently, when a driver makes a mistake or wrong decision, the adverse results are limited to a single accident, usually with one or a few vehicles involved. If a programmer makes a mistake or wrong decision, the adverse results could be astronomically higher. Are autonomous vehicles inevitable? Probably. Are they imminent? Probably not, at least on a widescale basis. What do you think? As always, feel free to add your thoughts in the Comments section below.