If you just landed your first job in the insurance business, chances are that you’re focused on that new position, not necessarily on what comes next in your career. You’re probably plenty busy doing what’s necessary right now—learning the new job, adjusting to a new company culture and hustling to prove yourself. You’re giving 100% to succeeding in your new role. That’s smart, especially considering that most new hires have less than two weeks to prove themselves on the job, according to new research from Fullbridge and Harris Poll. One in four executives say that employers take only two weeks to decide whether an entry-level new hire will be successful. Other executives say that it will take longer, but all agreed that it takes less than three months. With stats like that, it makes sense that long-term career goals take a back seat to making a great first impression. But while you’re settling into the rhythm of your new gig, you should make time to outline a basic road map for the rest of your career. As your early career moves away from entry-level positions and into more specialized roles with more responsibility, giving some thought to your future goals and plans can have a huge impact on your overall career trajectory. See also: The Many Paths to a Career in Risk There’s plenty of traditional advice available for people early in their career. A lot of that information is good, but there’s also more current insight applicable to young professionals. Here’s our breakdown of four ways to chart a course early in your career and figure out what makes you happiest on the job. 1. Don’t job hop—department hop Young professionals today have a reputation for switching jobs a lot more often than previous generations do. Recent research shows that this characterization is largely unearned. Young people tend to switch jobs more often than older workers, but millennials aren’t switching at a higher rate than young adults of past generations did. Changing jobs early in your career has its benefits, including a chance to earn more money and exposing yourself to more aspects of the industry. But there are downsides, too. Switching jobs is hard work, and some of it may be unrelated to learning the insurance business. You’ll need to learn to adapt to a new company culture. You may need to relocate. You may have to build your network of work friends and go-to leaders all over again. In short, you’re almost starting from scratch each time you switch organizations. Many young professionals have found a happy medium in department hopping. With the right organization, young insurance pros can gain hands-on experience in a variety of insurance disciplines through shorter stints in different departments. This gives you an opportunity to talk to different managers about salary ranges and your career priorities, and you can learn more about the industry without starting over at a new organization. If you’re interested in switching departments, take a look at Lifehacker’s advice for having that conversation with your boss. 2. Don’t find just a mentor—find a sponsor There’s no doubt that finding a mentor early in your career is extremely important. Many of the insurance professionals profiled on The Community cite finding a mentor as one of the most essential components of their early-career success. Mentors play a key role in career growth, but the Harvard Business Review argues that there’s another supporter you need in your corner: a sponsor. While mentors take a comprehensive look at your career (and often your personal life), a sponsor is someone within your current organization who can act as your advocate. It should be an executive or another leader who offers career guidance “by making important introductions to senior leaders, expanding the perception of what you can offer the organization and offering powerful backing to help you soar and protection when you stumble,” according to author Sylvia Ann Hewlett. 3. Don’t just network—learn more about the industry So much of the focus on early career development is on networking. Make no mistake—growing your professional network is important. But for young professionals, pure networking events like happy hours and meet-ups aren’t the most efficient way to meet other insurance pros and find new opportunities. Early in your career, there are plenty of ways to learn about the industry that also offer networking as a key secondary benefit. Look into industry designations. (AINS is a great way to get a comprehensive look at the insurance industry to figure out which elements of the business interest you most.) Or you can register for an industry conference and bring a stack of business cards. You also have a much better chance of getting your employer to chip in for these kinds of experiences. As you work to gain greater industry insight and expertise, forging relationships with other soon-to-be designees or conference participants will come naturally. And those relationships will be rooted in the pursuit of industry knowledge and career interests rather than personal ambition and cocktail-party chatter. See also: Work/Life Balance … Your Tightrope to a Rewarding Career   4. Don’t just think about goals—write them down One last small piece of advice for charting your career: once you determine some concrete goals, write them down. Recent research from Dominican University of California found that individuals who write down their goals and share them with others are far more likely to achieve them than people who didn’t write them down or tell others about them. Writing down your goals and sharing them—perhaps with your sponsor or growing professional network—go a long way toward making you accountable for achieving them. As you advance in your career and take advantage of new opportunities in a quickly changing industry, make sure to refer to your written goals and update them regularly. Have you found success charting your career goals? Let us hear your best tip in the comments section below.

Some life insurers now use data from fitness trackers to lower premiums. But does a policyholder’s number of steps really improve his or her mortality? Despite the link between a sedentary life and the risk of heart disease or cancer being well known, there is no consensus on how many daily steps reduce this risk. A popular daily target is 10,000 steps, but just a couple of thousand, when taken at a brisk pace, confer health benefits. There’s a good chance that a combination of positive lifestyle factors (maintaining a low BMI, avoiding tobacco, limiting alcohol and getting adequate sleep) improve mortality when combined with regular moderate exercise. Perhaps people who walk 10,000 steps or more every day already have this positive combination. See also: Wearable Technology: Benefits for Insurers   However, not everyone will find appealing the request to use a tracker to monitor their progress toward the step target. One reason is data security. Also, cheap devices are inaccurate, and it’s not always clear how the data can be interpreted or integrated within existing processes at reasonable cost. Besides, not everyone can maintain or reach the target levels of physical activity. [caption id="attachment_25326" align="alignnone" width="500"] Concept of connected health and fitness tracker and devices such as smart phone, tablet and wearable for a digital lifestyle[/caption] In the U.K. in 2015, gym memberships grew to 8.5 million. While the fitness sector expanded that year, the number of people in England engaged every week in physical activity fell, and the keep-fit and gym sectors suffered the biggest drop. People stop attending the gym due to lack of motivation, time or just feeling out of place. There is also evidence that wearable tech is losing some allure. Analysts reported that by November 2016 smartwatch sales declined 50% year-on-year. Several manufacturers of fitness bands are rethinking their participation in the consumer wearables market while others are laying off staff. Insurers may be wary of attaching themselves to fads, such as the use of fitness trackers, but the concern about long-term health isn’t going away. The growth in popularity of consumer technology suggests the industry faces more fundamental change. Technology is affecting consumers' empowerment, making them better informed and more demanding. People accustomed to using smartphone apps to order taxicabs and manage their bank accounts expect insurance propositions to offer similar levels of simplicity, service and convenience. While most people may not care about life insurance, they do care about having a long and healthy life. See also: The Case for Connected Wearables   This explains why insurance programs linked with fitness tracking have proved popular. But individuals with mental health problems, poor mobility or chronic illnesses, such as diabetes, may not care to link their coverage with physical activity. Insurers can harness technology to add value for these customers as well -- by prioritizing their emotional and wellness needs. Providing policyholders with practical support in the form of tutorials and online help could help prevent their health from worsening and mitigate the impact when it does. © Reproduced with the permission of General Reinsurance AG, 2017.

I started my career in insurance at the same place where most of our millennials are starting theirs, in the call center. In my case, it was a Farm Bureau claims call center in the beautiful suburban campus in West Des Moines, Iowa. I didn’t know it at the time, but I got really lucky. That call center was very well run by enlightened leaders who realized they were training the future leaders of the company. As early as the interview, managers told me that this call center was different. They understood that most of the new talent coming into the company would start in this department, and they had been instructed to engage and train those young professionals, so they would grow into productive employees not only during but after their time in the call center. They said they wanted me to spend two to three years in the call center, while learning as much as possible about the company and the insurance industry in general. After that, I’d be expected to start applying for positions beyond the phones. The department also required each individual to obtain the Associate in General Insurance (AINS) and the Associate in Claims (AIC) within the first two years. Failure to comply with the educational requirement could lead to termination. The way the call center functioned on a day-by-day basis was also quite engaging. Reps were trained well and supported in their efforts to grow their career (even when it meant time away from the phones for a class). The call center answered all first notice of loss calls for both personal and commercial lines claims, so it was not overly specialized; there was lots of variety on the day-to-day work. You’d get to keep the simple claims and work them to completion, acting as real claims adjusters. This resulted in great customer service, as roughly 40% of all calls would be answered by the person ultimately handling the claim. The approach also resulted in lots of employee growth. Even the way that managers measured performance was not bad at all for a call center. While they did measure the amount of time you spent on “After Call Work” and “Unavailable,” it wasn’t the main thing they cared about. To the best of my knowledge, they didn’t measure the dreaded “Time on Call” that most call centers use as their main measure of productivity. The main thing that counted in this particular call center was the number of new claims you took and the percentage of those that you kept. At the end of every week, management would send out a list of the top 10 reps who answered the most calls and kept the highest of those calls. I was almost always in the top two for both categories, and enjoyed the friendly competition. Because the list only included the top 10, not the bottom ones, people weren’t offended by it; it was a very positive thing. Management also included in the weekly newsletter a congratulatory mention of everyone who had passed an insurance designation test. While at times the call center could get hectic, the overall environment was very supportive of employee growth, and nobody seemed to hate the job. Eight years later, most of the people I worked with in that call center are still in insurance, and none of them are still call center workers. Many stayed in claims. Many are still in the same company. That’s a successful insurance call center in our book! It was such a great place that I was sad to leave when I got an offer for a better claims position at Nationwide, which ended my call center days. Sadly, I would find out as I met many other young insurance professionals that great insurance call centers that focus on developing their people are rare. Most are simply awful places to work, and, while nobody seems to be keeping statistics publicly, we have found 20 horror stories for every positive one. There are many conferences about insurance, and none seem to be talking about our call centers. The CPCU Society Annual Meeting and Leadership Summit has not had a single session about call centers in at least the six years I have been involved. It’s almost as if those call centers didn’t exist! Or, more likely, the leadership just doesn’t view them as really being insurance. It’s like the call centers are the black sheep of the insurance family that nobody wants to talk about! A huge portion of young insurance professionals in the 2010s started their insurance careers in a call center type environment. Most of them already had college degrees (and the associated student loans). Like previous generations, they fell into insurance by accident, but, unlike previous generations, they won’t stay out of loyalty or out of having found great careers. If we do our job right and engage them in the industry, they’ll grow. If we don’t, they’ll leave the industry, and we’ll continue having a huge talent gap. We’re not saying that we should close all the call centers and go back to doing business exclusively in the old-fashioned way. We understand that our expense ratio will not allow us to do that in the age of price transparency and incredible competition for every insurance customer. What we are saying is that we need to realize that, in many cases, the call center is our only touch-point with the customer, and we should be making them love their time with us. Maybe even more importantly, the call centers are our new entry level point for new talent, and given the talent crisis, our bad reputation with younger generations, and the high expense of replacing any employee, we need that talent to grow with us. See also: How to Reinvent Call Centers   Based on the horror stories we’ve collected from conversations with fellow young insurance pros who survived some time in the call center and lived to tell the tale, here’s what many (but  not all) of the insurance call centers are like to work in: You have to be logged in to the phones every minute you are in the office and are not allowed to even be in the office outside of your work hours. There are rows after rows of grey cubicles, packed with unhappy 25-year-olds with their college degrees hanging precariously from the cubicle wall and the headset making a semi-permanent mark in their ear. Engagement is so low that it could better be measured in level of desperation. Turnover is high, with the great majority leaving not only the company but the industry and swearing they’ll never work in insurance again. The reps who haven’t quite given up on the industry yet are applying desperately to any open entry-level position that’s not a call center. It doesn’t matter if it's claims, underwriting, processing or subrogation. Anything will do just to get off the phones! There’s so many applying for the same jobs with essentially the same resume, college degree and one to two years of insurance call center experience, that’s it’s very hard to differentiate among them, so hiring managers mostly just reject them without an interview. Some have been told directly that “we don’t hire from the call center." They are measured on 50-plus different characteristics, so many that it’s impossible to actually focus on improving. Who can control that many different minor factors during each phone call? The most important measures tend to be Time-on-Call and Availability. The first one measures the length of the average call, with the goal of keeping it as low as possible, and the second one measures the percentage of the time they’re available to take calls. In some extreme cases, even mandatory team meetings count against you the same as time spent in the restroom counts against you. Performance evaluations are focused 100% on metrics and very little on your own growth or what you need to do to get out of the call center. Most of the supervisors are former call center reps themselves who only know the call center life. They often don’t know anything else about the company or the industry and can’t serve as good mentors even if they wanted to. Professional development is encouraged by the company, but development time allowed by the department is very limited or completely non-existent, leaving it to  the employee to do all growth activities outside work hours. A case could be made that a motivated employee can grow by investing his own free time into activities like insurance designations, Toastmasters and networking, but most have no previous insurance experience and no advice on what they should be spending their time doing to grow with the company. The only thing they know is that they don’t want to be on the phones, and they don’t want to become call center supervisors either. We have even heard stories of call center employees being denied support in getting their basic insurance designations because they’re not required for the call center job the employees are doing. Some are denied even the ability to participate in activities such as Toastmasters or a young professional group because those meetings are in the office, and Human Resources doesn’t want employees to be in the office outside of work hours. There are better ways to run a call center. Not only should others learn from the example of the Farm Bureau Financial Service center where I worked, but there’s even more that we can learn from the best-run call centers outside the industry. Look at Zappos, which was founded on the crazy idea of selling shoes online. Think about that one: Shoes are the kind of thing that absolutely has to be tried in person, and, when you go shoe shopping, chances are you try multiple shoes before you find a pair that fits just right. Zappos succeeded selling shoes online by doing two things differently: The company will ship you as many shoes as you want, and then you can try them and keep the ones you want, returning the rest. Zappos will cover the shipping both ways. The second thing Zappos does is provide amazing customer service. To provide that service, Zappos runs large call centers staffed by very happy employees. How does it keep call center employees happy? By doing things diametrically differently from most other call centers (including insurance call centers). The hiring process consists of several interviews, mostly looking for personality fit. The HR rep conducting the first interview tries to simply figure out if this is a person he would want to work next to for 40 hours a week. Skills are much less important -- skills can be taught. During the hiring process, Zappos makes it very clear that the great majority of positions are at the call center, and, if you take the job, you’ll be answering the phones for a long time. Every new employee, regardless of position, must go through the call center training. You can be hired for a vice president role and on day one you get to go to your new office to set your stuff down, and then you come back down to train for the call center with everybody else. After finishing training, everyone gets to work the call center for a couple of weeks before going on to the job they were hired for. This guarantees that all the leadership knows what the call center is like. Currently, in insurance, there are very few, if any, senior executives who came from the call center, partially because those call centers didn’t exist or were much smaller when those executives were starting their careers. After their first couple of weeks on the phone full time, all new Zappos employees get called into a huddle room with their manager. The conversation includes giving the employee real feedback about her performance in the call center. Then the manager reminds the employee that most jobs at Zappos are at the call center level and that it’s hard to move to a different area. Finally, the manager says something like “Charlie, I’ve got  a check in your name for $2,000. I want to pay you to quit. If you don’t love the job, take the money, and we can part ways, no hard feelings.” Zappos does such a good job in hiring, orientation and training that only 2% of people take the offer. The way Zappos measures performance is very different from others, too. It doesn't measure Time-on-Call at all. All Zappos cares about is making the customer happy. That may mean ordering a pizza for a customer who is traveling and doesn’t know where to get a pizza or chatting for seven hours with a customer about which shoes to buy for her prom. Zappos understands that happy employees lead to happy customers, and that, in a world where your only interaction with the customer is when she visits your website or calls your call center, a call is a huge opportunity to connect with the customer. Zappos understands that a call center is NOT a cost center; it’s a key touch-point with our customer. What could be more important than that? The insurance industry has a lot to learn from Zappos. As millennials become a bigger and bigger part of our customer base, and they are not fans of visiting an agent’s office, the call center becomes our touch-point with the 95% of our customers who didn’t have a claim in any given year. Also, if the majority of your new employees are starting at the call center level, it’s our only chance to get them to fall in love with the industry and to convince them to make a career here. See also: Insurers’ Call Centers: a Cyber Weakness?   For more about the Zappos way, I highly recommend the book Delivering Happiness by Tony Hsieh, the CEO of Zappos. This amazing book will give you a great intro to how Zappos runs its business, especially its call centers. The company also provides guided tours of its offices in Las Vegas. The company provides training and consulting for other companies through its consulting arm Zappos Insights. You can learn more here. We are strong believers that the first large carrier to figure out how to turn its call centers into talent mines will have a major competitive advantage in the talent wars. Combine that with student loan aid and maybe with opportunities to take sabbaticals every few years, and you’ll create an unmatched employee experience that millennials will not want to leave. This article originally published at InsNerds.com.

Softening prices, little or no organic growth and increased competition have characterized most of the commercial insurance environment in recent years. These factors and a relatively benign cat environment continue to attract new types of capital providers (e.g., hedge funds, pension funds, foreign investors, capital markets) looking to diversify their investment portfolios with uncorrelated insurance assets. Limited organic growth opportunities also have led to a broad consolidation of distributors, with an increasingly large number of private equity-backed brokers looking for short-term gains and opportunities to reduce systemic inefficiency. In turn, this has led to significant carrier investments in automation to facilitate effective and efficient straight-through processing (STP). More specific responses to market conditions from commercial insurance constituents include:

• Distributor response – Distributors are increasingly looking for ways to (1) negotiate more aggressively on individual transactions (e.g., appetite exceptions, non-standard terms and conditions, pricing), (2) operate more efficiently (e.g., customized processes, only partial completion of applications) and (3) exert their bargaining power to gain higher commissions and other sources of revenue (e.g., access to market intelligence).

In addition, brokers are becoming increasingly organized. They are looking to 1) reduce the number of carriers with whom they place business in favor of ones that have a broad underwriting appetite and are easy to do business with and 2) exit the service arena, especially on small commercial accounts where margins are already extremely thin.

• Carrier response – Carriers are intensifying their efforts to compete for a “top three” position with distributors by attempting to (1) be easier to do business with (both in terms of technology and personal relationships), (2) increase product specialization and related underwriting expertise, (3) increase their appetite for more hazardous risk and 4) (as a less favored option) lower rates and pricing.

Although more and more carriers have invested in automated underwriting and pricing, broker/agent expectations are only increasing. They not only want to clearly understand a carrier’s underwriting appetite, they also want to get near-real-time quotes on the majority of standard risks without extensive manual data entry on their side. For now, carriers have avoided being “spread-sheeted” by using proprietary agent portals to increase ease of business interactions, rather than directly integrating with agency management systems and comparative raters. Distributors have not yet increased their demands for the latter two, recognizing that they could lead to a commission squeeze or even losing their appointment if the portability of their book declines with a given carrier.

• Customer response – Last but not least, customers’ behaviors and expectations are changing, too. They are becoming more comfortable researching business insurance online, and expect their shopping experience to reflect what they see in personal insurance. However, they are still turning to an agent (whether digitally or in person) to confirm their purchase decision and complete the deal. This is especially the case when businesses mature and risk management becomes more critical to their success.

See also: Seriously? Artificial Intelligence?   As all this has been happening, artificial intelligence (AI) has matured significantly, demonstrating that it can markedly improve existing STP. We describe below the AI technologies – including robotic process automation, natural language processing and machine learning – that can increase commercial insurance’s efficiency and effectiveness and thereby benefit investors, distributors and carriers themselves. Availability and access to large volumes of data, increasing processing power, cloud computing, open-source software and advances in algorithms have fueled the rise of AI from academic curiosity to commercial viability. The next generation of straight-through processing Although many carriers are already heavily automated, their initial focus has largely been on automated underwriting and pricing. This has left considerable manual intervention in the issuance process, post-bind audits and other downstream transactions. All of these can be streamlined to further drive down costs. Once carriers move to truly mechanized underwriting, the next step will be to embed third-party data feeds and advanced analytics to drive straight-through processing (STP) of risks. For example, imagine a small business owner being able to enter just four pieces of information (e.g., business name, business address and owner’s name and DOB) on a policy application and receiving a real-time business insurance quote with the option to immediately purchase and electronically receive policy documents. Furthermore, imagine this approach having no impact on underwriting quality or manual back-end processing requirements for the carrier. Integrating AI techniques and additional internal and external data sources into small business processing have the potential to make this a reality. A combination of leveraging internal data from prior quotes and policies, integrating external structured data feeds and mining a business’s website and social media presence could provide carriers with enough information to determine a business’s operations, applicable class codes, property details, employment and payroll and other key risk characteristics to underwrite and price low-complexity risks. In cases where more information is needed, dynamic question sets with user-friendly inputs could streamline the application process without sacrificing underwriting quality. How AI can improve straight-through processing In addition to immediate cost improvements, commercial carriers that leverage internal and external data resources and apply AI to commercial processing can benefit from reduced turn-around time, better and more consistent decision-making and improved agent/customer satisfaction. The carriers that are the first to adopt the latest in AI-enabled straight-through processing will be preferred by their existing agencies, as well as be able to pursue alternative distribution channels that feature a more streamlined, user-friendly acquisition process that accommodates less sophisticated users. Some of the most promising AI techniques that can help insurers improve STP include:

• Robotic process automation (RPA) is an area of AI that could increase STP efficiency and bring down costs at acceptable level of increased risk. RPA automates data entry, third-party data integration, form filling and data validation. More advanced process-mining techniques use machine learning to infer business processes from transaction logs, web and call center logs, email, and workflow logs. They profile the time it takes for different steps of the quote-to-issue process to be fulfilled and, to streamline the process, plot a distribution that enables the identification of outliers. They also track exceptions, and the reasons for them, thereby enabling greater efficiency. RPA is also tracking conformance and compliance with established standards, thereby leading to more consistent and compliant service delivery.
• Machine learning is building routing logic and underwriting-related models. For example, a detailed analysis of a commercial book of business over time can identify the need for no- touch, medium-touch or high-touch interaction models. This categorization enables better routing across multi-segment (i.e., small commercial, middle market and large commercial) insurers. In addition, machine learning can inform a wide variety of predictive models.
• Using open source technology, PwC has built natural language processing engines that continuously evaluate a large number of news and social media sources and report on key concepts.

Commercial insurers and brokers can use this ontology of “key concepts” to traverse the output, identify drivers of specific risks and refer to articles related to these risks. By indicating the relevance of articles (e.g., via a thumbs up or thumbs down) insurers can “train” the natural language engine to look for specific sources and type of articles. As the system learns over time, it can graph trending topics, the sectors and companies associated with certain risks and the underlying impacts if the risks develop adversely. We also have built a question-answer engine that allows risk experts to make natural language inquiries and retrieve relevant reports and documents to conduct further analysis. With natural language generation, the engine also can create risk profiles for senior management’s consumption. See also: 10 Trends at Heart of Insurtech Revolution   By coupling deep learning systems with natural language processing, PwC has been able to create powerful risk analysis enablers that enhance and speed up emerging risk analyses. When analyzing text from news sources or social media sources, the system needs to understand the context under which certain words are used. For example, a common word like “run” has more than 645 meanings according to the Oxford English Dictionary. “Deep Learning” or neural network-based machine learning systems can actually capture the context of words within sentences, sentences within documents and documents within a collection of documents. In closing, even with their increased focus on ease of doing business, there is still much room for carriers to improve. There currently is a clear opportunity for prescient and active carriers to separate themselves from the pack, but doing so will require a competitive mindset that has not traditionally defined the industry. Small and medium commercial carriers must find ways to improve their cost structures to compete profitably in the long term. AI-enabled solutions offer some of the most promising ways to do this. Implications

• New investors in the commercial insurance market are increasingly looking for short-term gains and greater efficiencies from the industry.
• Moreover, distributors are looking for greater ease of doing business with commercial carriers and have demonstrated a willingness to favor the ones that can meet their expectations.
• Commercial carriers have automated quoting in an attempt to facilitate effective straight-through processing. This has increased efficiencies, which has benefited investors and helped improve the distributor experience.

However, many manual processes and inefficiencies still remain. Once carriers move to truly mechanized underwriting, the next step will be to embed third-party data feeds and advanced analytics to drive straight through processing of risks. Recent developments in artificial intelligence (AI) can help carriers do this.

The business of property and casualty insurance—assessing risk, collecting premiums and paying claims—hasn’t changed much since 1861, when a group of underwriters sold the first policies to protect London homeowners against losses from fire. Recently, though, the insurance industry has embarked on a radical transformation, one spurred by a series of digital innovations whose widespread adoption is just a few years away. Bain & Company and Google have identified seven key technologies—namely, infrastructure and productivity, online sales technologies, advanced analytics, machine learning, the Internet of Things, distributed ledger and virtual reality—that have already begun to disrupt the industry and whose impact will accelerate in the next three to five years. These new technologies are likely to be a boon for consumers, bringing more choice, better service and lower prices. For those insurers ready to seize the initiative, digitalization presents an immense opportunity. The companies that stand to benefit the most are those that use the impetus of digitalization to rethink all their operations, from underwriting to customer service to claims management. The impact on both revenues and costs can be enormous. An analysis by Bain and Google shows that a prototypical P&C insurer in Germany that implemented these technologies could increase its revenues by up to 28% within five years, reduce claims payouts by as much 19% and cut policy administration costs by as much as 72% (see Figure 1). These pioneers in digital technology can gain an edge over their rivals by becoming more effective and efficient. They’ll be able to trim costs and pass on those savings to their customers, thereby winning new business and gaining market share. The digital laggards, by contrast, will find themselves fighting an intensified price war and scrambling to protect their competitive positions. Customers are pressing for change. They now expect their insurers to offer simple, transparent and flexible products and services—all online. And companies have begun to respond. In Australia, for example, you can use your smartphone to snap a photo of something you want to insure, such as a bicycle; upload the picture into an app called Trov; and then request a policy for a specific period, say a month. Trov uses available data about you and your bicycle and, within seconds, comes back with an offer. If you like the terms, you press the “I accept” button, and you’re covered. Claims are also handled online, with a rapid exchange of photos and texts. See also: Preparing for Future Disruption…   So far, companies have focused primarily on customer-facing applications. But some insurers are beginning to realize that digital means much more than cool and convenient apps for consumers; it is a force that will touch and reshape the very core of their business. Yet firms will reap the full benefit of digital technology only when they embrace its potential along the entire insurance value chain, including underwriting and claims management. Seven disruptive technologies To assess the impact of various technologies along the insurance value chain, Bain and Google identified and analyzed more than 100 digital use cases and focused on the 30 most likely to be disruptive within the next three to five years. Technologies that fall outside of that time frame, even potentially transformative ones like self-driving cars, biosensors and smart contact lenses, were excluded. The 30 use cases were grouped into seven broad categories and evaluated for the effect they would have on the revenues and profits of a prototypical German insurer—and by extension on the global insurance industry (see Figure 2):

• Infrastructure and productivity. A modern IT architecture is critical for digital innovation. Many insurers consider the cloud the best option for processing, computation and storage. They can also use productivity tools such as coauthoring and video calling, and they can connect with their customers through a seamless, omni-channel approach.
• Online sales technologies. Insurers can use cutting-edge techniques for targeting customers, identifying user groups and analyzing consumption patterns.
• Advanced analytics (AA). With AA, insurers can gain extensive insights into customer needs and preferences. Insurers can also draw on it to help fight fraud.
• Machine learning. With machine learning, insurers’ information systems can quickly adapt to new data, without the need for re-programming. Insurers can use machine learning to shape underwriting, price products and manage claims.
• The Internet of Things. Networked devices in cars and buildings can protect people and property and facilitate proactive, preventive maintenance, thus reducing accidents—and claims. By analyzing data from sensors embedded in vehicles and other equipment, insurers can gain insights into customer behavior.
• Distributed ledger technology. By arranging and documenting claims on distributed ledgers, insurers can greatly reduce processing time. A whole new field is opening up for smart contracts—that is, policies that are fully automated and updated based on a blockchain’s entire database.
• Virtual reality (VR). The global fascination with the smartphone game Pokémon Go shows VR’s popularity, but this technology also has the potential to transform the way information for underwriting is gathered, as well as the way claims are settled. For example, an insurer could use VR to create a three-dimensional image of a room or to reconstruct an accident in minute detail.

The common feature all these technologies share is their practical relevance. They are already in use today in differing degrees and will be widely available in three to five years. And more change is coming. Entirely new concepts in automotive insurance will be needed for driverless vehicles. Who is at fault in an accident if nobody was driving? 3D printers will unlock new possibilities for claims settlement. Imagine an insurer “printing” a new fender to replace the one bent in an accident. Even in the near future, though, insurance will look very different. Key question to ask: Is it good for the customer? Consider a car accident that occurs three years from now. New technologies will help the involved parties receive help quickly and efficiently. Immediately following an incident, software built into the vehicles can assess the damage and notify a towing service, if necessary. Assuming the drivers are not seriously injured, they can use their smartphones to record 3D images of the damage and then send the images, together with the electronic address cards of all the involved parties, to their insurance companies. In the future, insurers won’t need to dispatch human adjusters to gather facts and evaluate accident damage. Using machine learning, automated advisers will draw on virtual reconstructions of the accident and a wealth of background data. They’ll enter into a virtual dialogue with customers and immediately inform them where any damage can best be repaired. Insurers deciding which digital technologies to pursue can ask themselves a simple, and fundamental, question: Will it enhance the customer’s experience? Putting the customer first is more than a platitude. Simply put, an improved customer journey—one built on ultra-precise information, greater transparency, more flexibility and simplified interactions—is good for business. Each of the 30 cases that formed the basis of this study will enhance the customer experience—and, at the same time, help companies increase revenues and contain costs. See also: Mutual Insurance: Back to the Future?   Take the typical experience of a customer calling an insurer today. It’s likely an automated answering service will say to press buttons 1, 2 or 3 for various options. With machine learning, though, insurers will be able to serve a customer much faster and effectively, without all the button-pushing. The system will instantly analyze the customer’s flow of communications across all channels, including past phone calls, letters, emails and even public social media postings. When the customer starts speaking, the computer can analyze the tone of voice, determining whether the caller is confused or angry or both. Armed with all this information, a virtual agent can assess the customer’s needs and suggest a solution. By the time a real-life agent comes onto the phone—if that’s even necessary—the customer’s problem will likely have been resolved. Generally speaking, the moment of truth for every customer and every insurer comes when claims need to be processed. Digital technologies will be able to dramatically shorten the period between reporting and settling claims. That’s primarily because all relevant data will be collected within minutes and all parties involved will have access to the same information. Digital technologies will open up new vistas in claims prevention, thanks to the Internet of Things. In the future, for example, a sensor will be able to monitor a household’s water consumption patterns, detecting potential leaks and interrupting the flow before the basement is flooded, thus preventing major damage and a costly claim. The digital path to higher revenues and lower costs Digitalization will create fascinating new possibilities for insurers. But what actual implications will these have for revenues and earnings in the next five years? To answer that question, Bain and Google looked at a prototypical German P&C insurer that had adopted all 30 of the most promising digital use cases. Similar prototypes can be derived for specific business lines and for insurers operating in other countries, factoring in regional preferences. Across markets, insurers that serve individual consumers, as opposed to business customers, are likely to experience the earliest and biggest bottom-line impact from digitalization. Underwriting risk and processing claims for business customers are relatively complex operations, making automation more challenging. But commercial insurers will still be able to benefit from innovation—including the use of 3D technology to register objects and machine-generated data to calculate policies. Across the entire P&C sector, digitalization presents billions of dollars in opportunities to boost revenues and cut costs. To exploit these opportunities, the insurance industry needs a major rethink. Many insurers are focusing their digital efforts on product development and distribution, yet it’s underwriting and claims management that hold the biggest potential for change. It’s in those areas that machine learning, advanced analytics and the Internet of Things can have the biggest impact. Based on the Bain and Google analysis, the prototypical German insurer that consistently pioneers the use of digitalization can expect its premium receipts to rise by about 28% in five years, with most of the increase coming from gains in market share. By operating more efficiently, the insurer will be able to lower its costs, reduce its prices and thereby attract more customers. At the same time, the company will be able to use some of the money saved from its new technologies to invest in more digital innovation—forming a virtuous cycle. As rich as the potential is for top-line growth, the opportunities for cost reduction are even greater. By using digital technologies, a prototypical insurer can lower its gross costs by up to 29% in five years, with most of that savings coming from claims management. With digital tools, insurers will be able to more effectively underwrite risk, enhance preventions and minimize fraud. By deploying automated advisers and machine learning, they’ll save money on distribution and administration. To P&C insurers battling in a fiercely competitive marketplace, digitalization can be a multibillion dollar opportunity. The insurers mostly like to reap these benefits are those who give primacy to improving the customer experience. Digital tools that don’t make the customer’s journey more efficient, economical and satisfying aren’t likely to help the insurer’s top or bottom lines. Insurers can use digital tools to deliver added services, lower premiums and an all-around better experience. Companies that do this well will reduce costs and raise revenues—and they’ll be that much further along on the road to achieving a broad-based, customer-focused digital transformation. Signposts on the digital journey Take the customer’s point of view. Digitalization is not an end in itself, nor is it primarily a means of increasing profitability. Rather, it is a way to serve evolving and demanding customers. Design digital use cases that improve the customer’s experience and add value. Profits will follow. See also: Let’s Keep ‘Digital’ in Perspective   Expand your digital horizons. Insurers should establish a view now on those technologies that are likely to add the most customer value and differentiate them from their competitors. The biggest opportunities for gaining sway lie in underwriting and claims management. Launch and iterate. Rapidly evolving technologies and customer behavior present a challenge to long-term planning. Insurers should quickly bring new prototypes to market and continue to improve them. Companies should abandon those tools that don’t improve the customer experience, help cut costs or give them an edge over their rivals. Establish a digital culture. Digitalization means much more than technological change. Insurers should commit to new and improved ways of working and serving the customer, with employees who are trained and motivated to work in a digital environment. This article was originally published by Bain & Company.

In an industry where experience matters, and where specific domain knowledge has traditionally been prized above all other things, startups are increasingly being included in strategic conversations, and given a seat at the insurance table. Insurtech startups are bringing important emerging technology innovations and smart business solutions to a stalwart industry, and interest and investment in insurtech is climbing steadily. With the pace of change and competition increasing, as well, leading industry incumbents are beginning to pursue collaboration with fresh partners and platforms. Age Is Just a Number There is no right age for launching a startup, or for undertaking an innovation initiative, but many naively assume that younger is always better. In fact, some mix of experience in the industry being targeted along with an innovative idea and entrepreneurial state of mind are likely the best combination. The Global Insurance Accelerator (GIA) in Des Moines, for example, provides support to insurtech startups worldwide through a mentoring system that matches industry professionals with startups for a chance to better focus product-market fit. The average age of program participants working from Des Moines has increased each year since inception in 2015. The average age was 35 in the first year. It bumped one year to 36 in 2016, and jumped to 40 in 2017. See also: Will Startups Win 20% of Business?   This mix of new voices and seasoned experts proves that innovation doesn’t have to come exclusively from one generation. Leveraging industry knowledge and experience with ideas from newcomers can lead to great things when attacking problems worth solving. Everyone Needs Mentors Over the course of three cohorts at the GIA, a shift has occurred in the amount of insurance experience the entrepreneurs had coming into the program. In 2015, only a couple of participants had worked in the industry. Now, in 2017, the pendulum has swung to the other end of the spectrum, and almost every member of the cohort has worked in insurance at some point during his or her career. However, this prior industry experience hasn’t diminished the impact the GIA’s mentors have on any given startup’s evolution. The amazing pool of mentors who have raised a hand and taken a front seat in helping these early-stage InsurTech startups navigate a complex industry remain critical to the program’s success. Although the mentor role is largely to guide and advise, almost all of the GIA’s more than 100 mentors have reported learning as much from the startups. Collaboration Is Key There are six companies currently participating in the 100-day GIA program from a combination of the United States, Canada, Germany, and Serbia. The ideas and products offered by these InsurTech startups differ, as do the technologies powering the innovation, but these startups are all entrepreneurs who understand the vast opportunities within the insurance sector. Moving to the main stage, GIA’s InsurTech startup cohort members gain a seat at the table this Spring during the fourth annual Global Insurance Symposium in Des Moines. Sitting alongside peers in one of the global hubs of the insurance industry, these startups will be able to both learn from seasoned industry experts and share wisdom as well. See also: 5 Challenges Facing Startups (Part 5)   The Global Insurance Accelerator experience will culminate in a panel discussion at the Global Insurance Symposium which will discuss lessons learned, and provide an opportunity to network with leaders from around the industry. This experience will allow GIA’s cohort to better understand the industry so transformation can continue from the inside out. Collaborative efforts like these will not only allow insurance industry players to remain relevant and competitive, but to transform the insurance industry by meeting customers’ needs through new and improved methods.

The Third District Court of Appeals has issued its decision in Ramirez v W.C.A.B., again upholding the constitutionality of the independent medical review (IMR) process for review UR determinations and providing, perhaps, some additional nuggets for potential challenges on the W.C.A.B. decision in Dubon II that concerns the authority of the W.C.A.B. to review medical decisions. Ramirez is the third in a series of cases where applicant attorneys have attempted to challenge the constitutionality of the IMR process on various ground. In two prior decisions (Stevens v W.C.A.B. and Margaris v W.C.A.B.), different districts of the Courts of Appeal had rejected constitutional challenges to the IMR process based on similar arguments presented by the applicant in this case. See also: Appellate Court Rules on IMR Timeframes   While the applicant’s arguments in this appeal were somewhat broader than either of the prior appeals, the court’s rejection was just as emphatic. Ramirez’ challenge to IMR was based on multiple arguments:

• He argued the underlying UR was based on an incorrect standard, in effect appealing the UR determination itself to the court. This argument was rejected by the court on the grounds that the attack was at the heart of the determination of medical necessity, a determination that Labor Code  4610.6(c) prohibits the court from making. The court noted the applicant attorney did not argue that the IMR reviewer used in improper standard and that was the only one the court could only review for nonsubstantive reasons as set out in Labor Code  4610.6(h).
• Ramirez also challenged the constitutionality of the IMR process arguing that it violates the separation of powers clause as well as state and federal principles of due process. Both of these arguments were rejected in much the same manner as the court in Stevens rejected a similar argument.
• Ramirez argued that the W.C.A.B. decision in Dubon II, which limited the W.C.A.B.’s authority to review UR determinations to the timeliness of the decisions, was incorrectly decided and that other flaws in the UR process should allow the W.C.A.B. to assume jurisdiction over medical treatment issues. The court specifically rejected the argument that the W.C.A.B. had jurisdiction to review an IMR determination on the ground that the UR determination did not use the Medical treatment utilization schedule (MTUS).

It is on this last point the court’s language becomes interesting. The court reviewed the history of the Dubon decisions and the progression from an expansive view of the W.C.A.B.’s authority to the much narrower result in Dubon II that limits the W.C.A.B.’s authority to review only timeliness. The court does note that in Dubon II, where a UR determination is late, the W.C.A.B. could determine the medical necessity for the proposed treatment.  After review the W.C.A.B.’s decision and Cal Code Regs Tit 8 §10451.2 the Court goes on to state:

“To the extent the Board has any jurisdiction to review a utilization review as provided by this regulation, it has jurisdiction only over nonmedical issues such as timeliness of the utilization review as stated in the Final Statement of Reasons and Dubon II. We are not presented with a nonmedical issue. Any question that has the effect of assessing medical necessity is a medical question to be conducted by a qualified medical professional by way of independent medical review.  (§ 4610.6, subd. (i) [“In no event shall a workers’ compensation administrative law judge, the appeals board, or any higher court make a determination of medical necessity contrary to the determination of the independent medical review organization.”].) Whether the utilization reviewer correctly followed the medical treatment utilization schedule is a question directly related to medical necessity, and is reviewable only by independent medical review.”

While the court does not specifically indicate the W.C.A.B. was incorrect in Dubon II in its ruling that an untimely UR determination vests jurisdiction with the W.C.A.B. on medical issues; the above language certainly (at least) infers that any medical determination is beyond the W.C.A.B.’s authority. In the instant case, the court held there was not a basis to challenge the UR decision as it was timely and the other issues were not subject to W.C.A.B. review. The bolded language in the above quote certainly provides food for thought and perhaps some additional basis to challenge the W.C.A.B.’s holding in Dubon II, which, so far, has not been given a serious challenge at the appellate level. See also: IMR Practices May Be Legal, Yet…   Comments and Conclusions: That this court essentially followed the logic and reasoning of the prior appellate cases on this issue certainly suggests the options for challenging the IMR process are rapidly closing. While there are still a couple of additional challenges pending in the appellate courts (Zuniga in the first district challenging on one of the issues raised here — that the limitation on disclosure of the IMR doctor prohibited the applicant’s ability to challenge the doctor on bias, conflict of interest, etc. — and the Southard and Baker cases addressing the issue of late IMR as valid IMR as previously addressed in the negative in Margaris), so far the appellate courts have shown little interest in challenging the legislature’s authority to create and mold the workers’ compensation system. As one who has consistently believed the W.C.A.B. exceeded its jurisdiction in deciding it could address medical issues in Dubon II in spite of the strongly stated legislative purpose prohibiting exactly that conduct, I am cautiously optimistic that someone will challenge that decision; even the W.C.A.B. might have second thoughts about maintaining its ability to decide medical issues.

Disruptive innovation is not about technology Systems that are innovative at one time can become the “good enough” systems we need to overcome as they age and calcify. While it's inspiring to see new systems render old ones obsolete, this prescription of change creates a future where decisions about our collective future will be commercial engineering decisions and not social ones. Disruptive innovation comes at you fast. It is not about creating the best products and protecting profits. For example, with the launch of ApplePay, the whole world can do something Kenyans have done every day for more than 10 years. M-PESA, the mobile payment system offered by Safaricom, has been used by most adult Kenyans and is the model for hundreds of digital payment startups around the world today. See also: What Is the Right Innovation Process?   Kenyans don’t have bank accounts, making paper checks useless for all but the largest transactions. M-PESA was an appealing alternative to the status quo for transferring money from one city to another. Before you could transfer money through an SMS, it was common to give money to a taxi driver heading in that direction and ask him to deliver your payment for you. Safaricom, a leading mobile network provider in Kenya, captured consumers out of mainstream banking institutions and built customers — not the best technology. Disruptive innovation refers to the strategy that employs technology; the technology itself isn't disruptive, but rather the application of the technology can be disruptive or not. This depends on whether the technology is positioned with a disruptive strategy.

Big data has the opportunity to end discrimination. Everyone creates data. Whether it is your bank account information, credit card transactions or cell phone usage, data exists about anyone who is participating in society and the economy. At Root, we use data for car insurance, an industry where rating variables such as education level or occupation are used directly to price the product. For a product that is legally mandated in 50 states, the consumer’s options are limited: give up driving and likely your ability to earn a living or pay a price based on factors out of your control. Removing unfair factors such as education and occupation from pricing leaves room for variables within an individual’s control — namely: driving habits. In this way, data can level the playing field for all consumers and provide an affordable option for good drivers whom other companies are painting with a broad brush. In the lon term, everyone wins as roads become safer and driving becomes prohibitively expensive for irresponsible drivers. This is just one example where understanding the consumer’s individual situation deeply allows for more precise — and more rational — decision making. But we know that the opportunity of big data goes beyond the individual. For example, the unfair practice of naively blanketing entire countries, religions or races unfairly as “dangerous” is a major topic in the news. What happens if you apply the lens of big data to this policy? See also: Industry’s Biggest Data Blind Spot Causal Paths vs. Assumption-Based Decisions With the increased availability of data, we are able to better understand the causal paths between data generation and an event. The more direct the causal path, the better predictions of future events (based on data) will perform. Imagine having something as trivial as GPS location data from a smartphone on a suspected terrorist. Variables such as having frequent cell phone conversations with known terrorists or being located within five miles of the last 10 known terrorist attacks will allow us to move away from crude, unjust and discriminatory practices and toward a more just and rational future. Ahmad Khan Rahami, who placed bombs in New York and New Jersey, was flagged in the FBI’s Guardian system two years earlier. The agency found there weren’t grounds to pursue an investigation — a failure that may have been averted if the FBI had better data capture and analysis capabilities. Rahami purchased bomb-making materials on eBay and had linked to terrorist-related videos online before his attempted attack. Dylann Roof’s activities showed similar patterns in the months leading up to his attack on the Emanuel AME Church in Charleston, SC. The causal path between a hate-crime or terrorist attack and the actions of Dylann Roof and Ahmad Khan Rahami is much more direct than factors such as religion, race or skin color. Yet we naturally gravitate toward making blanket assumptions, particularly if we don’t understand how data provides a better, more just approach. Today, this problem is more acute than ever. Discrimination is rampant — and the Trump administration's ban on travel is unacceptable and unnecessary in the era of big data. For those unmoved by the moral argument, you should also know policies like the ban are hopelessly outdated. If we don’t begin to use data to make informed, intelligent decisions, we will not only continue to see backlash from discriminatory policies, but our decision making will be systematically compromised. The Privacy Red Herring Of course, if data falls into the wrong hands, harm could be done. However, modern techniques for analyzing and protecting data mitigate most of this risk. In our terrorism example, there is no need for a human to ever view GPS data. Instead, this data is collected, passed to a database and assessed using a machine learning algorithm. The output of the algorithm would then direct an individual’s screening process, all without the interference of a human. In this manner, we remove biased decision making from the process and the need for a “spy” to review the data. See also: Why Data Analytics Are Like Interest   This definitely provides a challenge for the U.S. intelligence community, but it is an imperative one to meet. If used responsibly, analytics can provide insights based on controllable and causal variables. The privacy risk is no longer a valid excuse to delay the implementation of technologies that can solve these problems in a manner that is consistent with our values. This world can be made a much better and safer place through data. And we don’t have to sacrifice our privacy; we can have a fair world, a safe world and a world that preserves individual liberties. Let’s not make the mistake of believing we are stuck with an outdated and unjust choice.