Silicon Valley exemplifies the saying, “The more things change, the more they stay the same.” Very little has changed over the past decade, with the Valley still mired in myth and stale stereotype. Ask any older entrepreneurs or women who have tried to get financing; they will tell you of the walls they keep hitting. Speak to VCs, and you will realize they still consider themselves kings and kingmakers. With China’s innovation centers nipping at the Valley’s heels, and with the innovation centers that Steve Case calls “the rest” on the rise, it is time to dispel some of Silicon Valley’s myths. Myth 1: Only the young can innovate The words of one Silicon Valley VC will stay with me always. He said: “People under 35 are the people who make change happen, and those over 45 basically die in terms of new ideas.” VCs are still looking for the next Mark Zuckerberg. The bias persists despite clear evidence that the stereotype is wrong. My research in 2008 documented that the average and median age of successful technology company founders in the U.S. is 40. And several subsequent studies have made the same findings. Twice as many of these founders are older than 50 as are younger than 25; twice as many are over 60 as are under 20. The older, experienced entrepreneurs have the greatest chances of success. Don’t forget that Marc Benioff was 35 when he founded Salesforce.com; Reid Hoffman 36 when he founded LinkedIn. Steve Jobs’s most significant innovations at Apple — the iMac, iTunes, iPod, iPhone and iPad — came after he was 45. Qualcomm was founded by Irwin Jacobs when he was 52 and by Andrew Viterbi when he was 50. The greatest entrepreneur today, transforming industries including transportation, energy and space, is Elon Musk; he is 47. See also: Innovation: ‘Where Do We Start?’   Myth 2: Entrepreneurs are born, not made There is a perennial debate about who can be an entrepreneur. Jason Calacanis proudly proclaimed that successful entrepreneurs come from entrepreneurial families and start off running lemonade stands as kids. Fred Wilson blogged about being shocked when a professor told him you could teach people to be entrepreneurs. “I’ve been working with entrepreneurs for almost 25 years now,” he wrote, “and it is ingrained in my mind that someone is either born an entrepreneur or is not.” Yet my teams at Duke and Harvard had documented that the majority, 52%, of Silicon Valley entrepreneurs were the first in their immediate families to start a business. Only a quarter of the sample we surveyed had caught the entrepreneurial bug when in college. Half hadn’t even thought about entrepreneurship even then. Mark Zuckerberg, Steve Jobs, Bill Gates, Jeff Bezos, Larry Page, Sergey Brin and Jan Koum didn’t come from entrepreneurial families. Their parents were dentists, academics, lawyers, factory workers or priests. Anyone can be an entrepreneur, especially in this era of exponentially advancing technologies, in which a knowledge of diverse technologies is the greatest asset. Myth 3: Higher education provides no advantage Thiel made headlines in 2011 with his announcement that he would pay teenagers $100,000 to quit college and start businesses. He made big claims about how these dropouts would solve the problems of the world. Yet his foundation failed in that mission and quietly refocused its efforts and objectives to providing education and networking. As Wired reported, “Most (Thiel fellows) are now older than 20, and some have even graduated college. Instead of supplying bright young minds with the space and tools to think for themselves, as Thiel had originally envisioned, the fellowship ended up providing something potentially more valuable. It has given its recipients the one thing they most lacked at their tender ages: a network.” This came as no surprise. Education and connections are essential to success. As our research at Duke and Harvard had shown, companies founded by college graduates have twice the sales and twice the employment of companies founded by others. What matters is that the entrepreneur complete a baseline of education; the field of education and ranking of the college don’t play a significant role in entrepreneurial success. Founder education reduces business-failure rates and increases profits, sales and employment. Myth 4: Women can’t succeed in tech Women-founded firms receive hardly any venture-capital investments, and women still face blatant discrimination in the technology field. Tech companies have promised to narrow the gap, but there has been insignificant progress. This is despite the fact that, according to 2017 Census Bureau data, women earn more than two-thirds of all master’s degrees, three-quarters of professional degrees and 80% of doctoral degrees. Not only do girls surpass boys on reading and writing in almost every U.S. school district, they often outdo boys in math — particularly in racially diverse districts. Earlier research by my team revealed there are also no real differences in success factors between men and women company founders: both sexes have exactly the same motivations, are of the same age when founding their startups, have similar levels of experience and equally enjoy the startup culture. Other research has shown that women actually have the advantage: that women-led companies are more capital-efficient, and venture-backed companies run by a woman have 12% higher revenues, than others. First Round Capital found that companies in its portfolio with a woman founder performed 63% better than did companies with entirely male founding teams. See also: Innovation — or Just Innovative Thinking?   Myth 5: Venture capital is a prerequisite for innovation Many would-be entrepreneurs believe they can’t start a company without VC funding. That reflected reality a few years ago, when capital costs for technology were in the millions of dollars. But it is no longer the case. A $500 laptop has more computing power today than a Cray 2 supercomputer, costing $17.5 million, did in 1985. For storage, back then, you needed server farms and racks of hard disks, which cost hundreds of thousands of dollars and required air-conditioned data centers. Today, one can use cloud computing and cloud storage, costing practically nothing. With the advances in robotics, artificial intelligence and 3D printing, the technologies are becoming cheaper, no longer requiring major capital outlays for their development. And if entrepreneurs develop new technologies that customers need or love, money will come to them, because venture capital always follows innovation. Venture capital has become less relevant than ever to startup founders.

It’s rough out there. In the world of marine insurance, syndicates are shutting down, losses are mounting and Lloyd’s is demanding turnaround plans for the worst-performing 10% of insurers’ business. According to Jim Mulrenan, a recently retired veteran of TradeWinds, from 2010 to the end of 2017 fewer than half of the 79 marine insurance syndicates were profitable. Over the past three years, just 16 out of 71 syndicates made money. Since June 2017, seven marine insurers have shut up shop. More may follow. For those that remain, though, we at Windward see a great opportunity that - if seized - could help marine insurers regain their collective mojos. Start with the syndicates that have left the building. They’ve reportedly trimmed marine underwriting capacity at Lloyd’s by $100 million, or about 5%. Fewer shops writing ships should lead to higher rates, as there would be less capacity. Swedish Club Managing Director Lars Rhodin says hull rates have already “bottomed out.” See also: Huge Opportunity in Today’s Uncertainty   The good news doesn’t end there. As ship owners find the insurer they’ve used for the best part of a decade is no longer around, they’ll be forced to take their business somewhere new. This poses a dilemma for insurers: On the one hand, they want the new business, as it should mean more profits; but on the other, they don’t know these “new” fleets and owners as intimately as their existing portfolio, and so they worry about taking on unknown risks. New business takes up the slack from renewals It’s an understandable concern and one that will likely grow as new business becomes a larger share of insurers’ portfolios versus renewals. We believe the best way to assuage these concerns is technology: Marine risk analytics bridges the gap in underwriters’ knowledge of new owners and fleets; it helps them efficiently evaluate potential new business and pounce on the risks they like. With budgets strained, chief underwriting officers and heads of marine are right to keep a firm grip on the purse strings, even in anticipation of higher profits. Investing in technology always throws up questions - will it work (yes, it’s already working), will we get a return on investment (yes, it’s already delivering value), will our team be able to work with it (yes, it’s intuitive) or will they worry about losing their jobs (they shouldn’t; they’ll now have a competitive edge)? See also: Insurtech Is Ignoring 2/3 of Opportunity   Ultimately, the marine insurers that survive and thrive will be those whose leaders seize the opportunities that technology can bring. We strongly believe that the time to act is now. Because if it’s not, it may be never.

I did a Google search on the number of project management methodologies that exist currently, and I kept getting results like "9 methodologies made simple" and "15 methodologies you must know." In the world of "methodologies galore" such as Waterfall, Agile, Six Sigma, Lean, Lean Startup, Kanban, etc., etc., with each body of knowledge or pundit preaching that they are the best and most effective, how might one "declutter" the jargon and really apply effective project management for their initiatives? As insurtechs, we also need to take into consideration client methodologies and what is being used in their organizations. Here are three key principles that I've applied to my nearly one-plus decade of project management, whether I’ve implemented Scrum, Lean, etc.: Keep It Simple: Don't overcomplicate your project management process. Simplicity is the ultimate sophistication. I have seen slides from companies talking about their project management approach that make me go take a Tylenol. Project management is not about methodology, process or tooling (they are essential -- don't get me wrong). The focus is about people and communication. Keep It Nimble: At Benekiva, how we manage internal projects and our road map is different than implementing a client engagement. We are nimble to adapt based on clients' feedback. If they want status reports, they are getting them. If they want an Excel output, they get it. Keep It Short: This relates to how we schedule iterations/sprints and work effort. Keeping them short allows us to respond to any change or "aha" moments effectively with minimal impacts. Keeping it short also eliminates procrastination, where things get pushed to the last minute. See also: How to Improve ‘Model Risk Management’   Applying these three principles to your project management practice will allow your company to do enough project management while giving you more time to communicate to your stakeholders and adding value where it needs to be added.

It’s no secret that the insurance industry is going through an exciting time of innovation, growth, and transformation. This certainly poses risks for insurers if they fail to adapt to these changes, but it also offers significant opportunities. Changes are also occurring among American consumers, as more economic risk has begun to shift from government and business onto the shoulders of Americans themselves. Long gone are the days of income security through guaranteed pensions; defined benefit pensions have been replaced by 401(k) plans; health insurance costs put more responsibility on the employees and less on the employers; steady guaranteed income has given way to much more volatility in people’s bi-weekly paychecks; and employer-sponsored benefits are waning as more people rely on the gig economy for work. This “risk shift,” as political scientist Jacob Hacker calls it, provides a huge opportunity for insurers because they’re in the risk business. But it also presents a challenge. Do insurers understand what average Americans today see as their biggest risks? Do insurers know how to insure against the risks to provide the peace of mind that insurance is meant to provide? Is the insurance industry at risk itself of becoming irrelevant if it doesn’t take note of these changes and adapt products and services accordingly? These questions were asked in research we recently completed looking at the insurance needs of low- to moderate= income (LMI) Americans, defined as having household incomes of less than $60,000. Based on that research, there are three main takeaways for the insurance industry for how to stay relevant in today’s changing landscape. 1. LMI individuals largely rely on savings and borrowing to cope with shocks, even shocks that are insurable. (These shocks can range from relatively minor ones, like an unexpected repair or expense, to something much more serious, like a major illness or the death of a family member.) The risk here, of course, is that, while self-insuring with savings and assets may seem sufficient in theory, very few people have enough savings to self-insure adequately. 68% of LMI individuals report that it is very or somewhat difficult to build short-term savings, and 66% report similar difficulty in building long-term savings. Credit is equally problematic as potential over-indebtedness poses more risks to consumers. A major takeaway from our research was that consumers are unclear about when savings are an appropriate tool to use to weather a shock and when insurance is. The interplay between savings and insurance, and other tools like credit, to build financial resilience shows how interconnected and complex people’s financial lives are. See also: Innovation — or Just Innovative Thinking?   2. A significant challenge that all consumers face is the uncertainty of their insurance coverage and whether it will be sufficient in the case of a shock. The research clearly showed us that having an insurance policy in place does not necessarily mean that someone feels fully protected. Focus group participants in our research consistently indicated that they would not know if their policies, regardless of type, were adequate to protect them against a shock unless they had to actually use them. As one LMI focus group participant in Baltimore explained, “There needs to be some explanation. It is very difficult to know, except for a mandate by the state, how much is desirable.” This lack of confidence negates the peace of mind that insurance is meant to provide. This obviously has the largest implications for LMI customers, who may in fact be inadequately covered and therefore ill-prepared to cover costs not covered by their policies. 3. LMI consumers remain uninsured not because they don’t understand the risks they should insure, but because they have to prioritize the risks that they can insure. It really all comes down to price. Finding good value for money was the most important quality that consumers looked for in an insurance company. This quality ranked higher than other seemingly important ones, such as having products that best fit one’s needs or being easy to do business with. While shopping for the cheapest policy doesn’t necessarily mean having less insurance coverage, it may affect coverage by forgoing useful features that can provide added protection. Price is also a major influencer in the decision not to purchase insurance at all, even if people know they need it. Of those in our research without life insurance, 51% thought they needed it. This shows that LMI consumers are forced to make complicated financial decisions based on the risks in their lives and the resources they have. I remember one woman in Baltimore with a young daughter who chose to purchase disability insurance instead of life insurance with the disposable income that she had. I would have thought that life insurance would have been the most important protection she could provide for her daughter. Yet she reasoned that a loss of income would be a significant blow for her family. She had used her disability insurance in the past, it filled an income gap and she expressed glowing satisfaction. Life insurance was important, and she knew it, but it would have to wait for another day. See also: 4 Technologies That Are Changing Risk   This anecdote is an apt way to conclude. Consumers do not place their risks and mitigating strategies into product silos like insurers do. To stay relevant in the midst of significant societal changes, insurers should take a holistic view of someone’s financial life, and the risks they face, to better serve existing customers and, more importantly, attract new ones who are dangerously unprotected.

Imagine having an expert mentor at your fingertips at all times. Someone who could answer questions, provide advice and move you in the right direction. For customer experience representatives at Allstate, that dream is a reality with Amelia, an AI-powered cognitive agent trained in the language of insurance. It’s just one way the company is using AI to power customer experience and lead the charge in a changing insurance industry.

As customer expectations have changed, Carla Zuniga, senior vice president at Allstate, has worked to modernize how the company interacts with customers. The goal is to make more out of everyday interactions with customers and to move more interactions to automated channels, including chatbots and AI-augmented human roles.

One of the major players in the AI game at Allstate is Amelia, a cognitive agent trained on more than 50 unique insurance topics and regulations across all 50 states. Allstate employees can quickly chat with Amelia to get concise answers about complicated insurance questions from customers. Not only does it allow customers to get the answers they need right away, but it allows employees to be ready to work much sooner by cutting down training time. Instead of having to sort through numerous articles and resources and make customers wait, representatives can now chat with Amelia while the customer is on the phone to get the most accurate information. In an industry where regulations and compliance are incredibly important, Amelia helps make sure every customer’s needs are met and are in compliance. Amelia provides the best of both worlds—the quickness and accuracy of AI mixed with the personal touch of human interaction.

See also: Why AI-Assisted Selling Is the Future  

Amelia handles more than 250,000 conversations each month and is used by more than 75% of Allstate call center employees. Allstate has plans to increase her workload and expand her scope to eventually interact directly with customers. Paired with other AI programs like automation and big data, Amelia has helped Allstate reduce its talk times and increase its first call resolution rates.

Zuniga believes AI will continue to grow and transform over the next five years as the technology becomes more robust. As Amelia and other AI services become more customer-facing, employees will be able to focus more on case management and the human aspects of customer experience.

No matter how the technology grows, personalization is still a key element of insurance companies. It can be easy for customers to just feel like a number when they get a new policy, file a claim or contact their insurance agent. To combat that, Allstate relies on data and creates detailed profiles of each customer. By leveraging this information and using AI to highlight trends and the most important data points, the company can help interactions feel more intimate.

See also: Strategist’s Guide to Artificial Intelligence

As the digital transformation continues and AI changes how insurers interact with customers, innovating and staying ahead of the curve is incredibly important. Modern customers want to feel empowered and engaged, and the best insurance companies must innovate to stay relevant. A major part of that innovation must be centered on AI, just like what is being done at Allstate.

You can find the article originally published here.

Impact Forecasting, the catastrophe model development team of Aon’s Reinsurance Solutions business, reports that many countries saw a worsening in drought-related and wildfire conditions during July, leading to hundreds of deaths and a significant financial impact globally – particularly on the agriculture, forestry, water management and fisheries industries.

Preliminary aggregated estimates of economic losses entirely due to harvest reduction and affected forestry exceeded multiple billions of dollars.

Northern Europe was hit by a long-term rainfall deficit that caused one of the deepest droughts on record, contributing to combined European drought losses in excess of $4 billion. According to various industry estimates, German farmers alone could face economic losses of $2.9 billion.

Other severe drought events affected agriculture in Australia and Central America, and an extensive heatwave killed more than 150 people in Japan and South Korea.

In California, the Carr fire became one of top 10 most destructive wildfires on record after being ignited near Redding, killing six people, destroying roughly 1,600 structures and damaging hundreds more. The total economic cost was anticipated to exceed $1 billion, with insurance losses also expected to approach or top that total.

Another Northern California wildfire, the Mendocino Complex fire, destroyed 143 structures and became the largest fire in the modern record (since 1932) in California.

The deadliest wildfire event on record in Europe since 1900 had a devastating impact in the Mati, Eastern Attica region of Greece, killing at least 92 people. The fire, and others in Attica, destroyed at least 905 structures and damaged a further 740.

Elsewhere in Europe, Sweden battled the most significant wildfire outbreak in its modern history, with damage exceeding $100 million.

See also: How to Fight Growing Risk of Wildfire  

Michal Lorinc, an analyst within Impact Forecasting’s Catastrophe Insight team, said: “The month of July was marked by record-breaking heat, deepening droughts and destructive wildfires in areas all around the globe. Nearly every major continent recorded some type of peril impact that will lead to a major cost to agricultural interests. In Northern Europe alone, the cost to local farming interests is expected to result in a multibillion-dollar loss in harvest output. All eyes are on the looming possibility of an El Nino return by the end of the year, which could exacerbate these types of impacts.”

Further natural disaster events to have occurred elsewhere during July include:

• Historic rainfall in Japan caused significant flash flooding and mudslides, leaving at least 230 people dead or missing. Nearly 50,000 homes were damaged or destroyed, with the General Insurance Association of Japan reporting 48,000 insurance claims being paid, at a preliminary cost of $711 million.
• Notable flooding occurred in Arizona and the U.S. Northeast, Nigeria, Russia’s Far East, India and multiple countries in Southeastern Asia, including Myanmar, Vietnam, Laos, Cambodia and the Philippines. Seasonal flooding in China prompted aggregated economic losses nearing $1 billion.
• Multiple typhoons in the Western Pacific Ocean Basin left notable damage in parts of China, Vietnam and Japan. The costliest was Typhoon Maria, which caused nearly $500 million in economic damage in China. Other storms that tracked across Southeast Asia were Sonh-Tinh, Ampil and Jongdari.
• Several outbreaks of severe weather led to widespread damage across parts of the U.S., Canada, France, Germany, Italy and China during July.
• Major earthquakes caused severe damage and injuries in Iran (July 22) and Indonesia (July 28).

See also: Insurers Grappling With New Risks   To view the full Impact Forecasting July 2018 Global Catastrophe Recap report, please follow this link.

Profitability is getting harder. Agencies, brokers, MGAs and carriers have seen major shifts in all aspects of their businesses over the past two decades – from what customers expect to how their competition operates. Distribution patterns have changed, mergers and acquisitions are increasing and automated insurance options are eating into margins. In addition, the globalization of insurance markets is becoming more evident every day. Sound bleak? Yes and no. The fact is, the insurance distribution industry faces many of the same challenges as other industries such as retail and travel -- markets that have had to completely transform how they do business in the face of new customer expectations and nonstop innovation. The common denominator in meeting the challenge is data. More specifically, the answer is data monetization: the process of not only accessing the rich information inside customer and business data but also converting it into actions and business decisions that drive profits. Customer data is quite literally an additional income source that every agent already has at his or her fingertips. And it can, with the right tools and organizational changes, be used immediately to increase revenues, margins and overall profitability. Indeed, it’s hard to overstate the potential value of the data that already resides inside outdated agency management software. It represents not only billions of potential dollars being left on the table, but, for many brokers, it is also the only path to survival. The technology lockbox Why the insurance industry lags behind others in data monetization is largely a matter of culture and technology. People-oriented and traditionally built on relationships, brokerages have been slower than other industries to adopt and subsequently upgrade their agency management systems. As a result, many agents still use legacy software that houses data but does not then release it in usable form. While growing competition and shrinking commissions are driving insurance agents to lean harder on technology to compete, those agents will also tell you it’s next to impossible to extract useful data from their systems -- let alone glean value from it. Principals can’t see what’s going on with their producers, producers can’t see opportunities for growth and customers aren’t getting the value they expect. The unfortunate fact is, data alone can’t tell you what products to recommend or which clients to up-sell. Legacy software is, in fact, a monumental barrier to extracting and monetizing data. Few agents are trained to tap into this vast income-generating resource. Executive teams have too many complex third-party reporting options from which to choose. And there is no defined go-to-market strategy to take advantage of this data even if it is extracted. See also: Why Data Analytics Are Like Interest   Automating data monetization Insurance professionals need the ability to turn data into revenue through all areas of the business, including sales to new and existing customers, operations, policy management, claims and customer service. Brokers must be able to easily, quickly and confidently understand what data means and is telling them to do. Dashboards and reports must reflect the current state of the business to power better decision making. And brokers must be able to access the system and data any time and from any device (and offer the same experience to their clients). The gold standard for data monetization is end-to-end software that can manage daily operations AND automatically provide insights into where agents/brokers can leverage their current customer base to increase profits and margins. It must turn client purchasing histories and behavioral patterns into revelations and opportunities for the broker to deliver value to the customer. Data monetization in action What does the data monetization process look like in everyday agency practice? Here are some examples:

• Agents know in real time, on every account, where the immediate upsell and cross-sell opportunities. The system recommends these opportunities based on customer industry, size and other factors.
• The system identifies which customers are bleeding agency money and which are profitable, so agents can see precisely how a given renewal would affect the bottom line.
• The system can instantly slice and dice an existing book of business to identify the best leads for a new line of business. It could then assign leads to the right sales person to manage the funnel and provide metrics on conversion rates and other KPIs.
• It would offer real-time analysis of:
  • How different business lines are performing
  • Which customers are profitable, break-even or unprofitable
  • What is the total income a customer brings vs. the number of staff hours and resources the customer requires
  • What is a customer’s claims history relative to policy income
  • Time, resources and effort invested in the insurance portfolio relative to actual revenue

Ready access to these kinds of answers can be used to guide renewal strategy, pricing decisions and management of staff’s time and resources toward the most profitable outcomes. Organization change While adopting the right technology is vital to data monetization, it must also be accompanied by cultural changes:

• Staff must have incentives to follow up and make sure revenue opportunities are closed successfully
• Operating procedures must be updated to clarify new rules and how they are to be followed
• Management must follow up weekly for the first few months of implementation

See also: Is Big Data a Sort of Voodoo Economics?   Turning data into revenue and a reshaped customer experience Insurance is a customer-centric business at its core. However, many agents are not living up to their customers’ expectations when it comes to the experiences they deliver. By adopting a business and technology approach based on data monetization, agents can use real-time customer intelligence to deliver more tailored advice and generate bottom- and top-line value. It’s all there in the data – and it’s time to unlock the box.

A lot of people are talking about the promise of artificial intelligence (AI), and some say it’s too early to evaluate its long-term impact. I disagree. I believe we need to evaluate AI’s value now, because it’s already beginning to fundamentally change the way auto insurers do business. A sweeping statement, perhaps, but there’s a lead-up to this discussion that is creating the perfect storm for P&C insurers. First, insurer performance is challenging, and most every insurer I speak with is racing to identify ways to reduce expenses while continuing to offer desirable products to savvy consumers -- consumers who expect insurance to be delivered and serviced just as seamlessly as their interactions with their favorite online retailer. Next, vehicle complexity is making it extremely difficult to price risk, predict frequency (largely due to advanced driver assistance systems, or ADAS) and understand increasing repair costs, thanks to enhanced electronic content, such as the sensors in newer vehicles. In this environment, AI can play a critical role, helping insurers bring expenses back in line while creating opportunities to deliver a better insurance experience for consumers. And, as vehicles become more connected, streaming more data, the role of AI will only grow. AI Now If you’re still not clear on what exactly AI is, it refers to programs that are capable of learning to make decisions more like humans. AI is at work all around us – when robots control other robots on the manufacturing line, intelligently automating the management and optimization of financial portfolios, detecting cancer using MRIs and machine vision and powering self-driving cars. In fact, AI is becoming so prevalent it’s expected to create $1.2 trillion in business value by the end of this year and $3.9 trillion by 2022. AI in Insurance It's now our industry’s turn to put AI to work. What we’re seeing in other industries is now happening in claims. AI is being injected into key points in the claim process, helping to create value that can be seen (and felt) inside and outside the organization. Meaning, AI done right can yield improvements designed to enhance the experience of all stakeholders. From an internal efficiencies perspective, consider AI’s impact on workflow challenges. As just one example, let’s look at the value of mobility and IoT, telematics in particular, because this is foundational to AI-driven improvements in processes. As you read on, think about all the existing processes and labor currently linked to your own auto claims area, because even the workflow that initiates a claim--in place for a hundred years--is now being changed, thanks to AI. See also: Strategist’s Guide to Artificial Intelligence   The New Claims Workflow There is a new claims workflow taking hold right now, not some point in the future. First, policyholders won't call the insurer when they experience an accident—the insurer will contact him/her. This is because the insurer will apply AI to telematics data, setting an alert tagged to view the rate of change of the vehicle and determine in real time that there has been an accident. Now apply AI-driven conversations via chatbots with customers at scale, in real time, to guide them through the claims process after that accident occurs. In our example, the chatbot asks the claimant for a photograph—an automated, back-end review determines suitability of the photograph, enabling the insurer to determine with high accuracy and in real time whether the vehicle is likely to be a total loss or repairable and advises the policyholder accordingly. Fast, transparent communication. If the damage is repairable, the chatbot asks for additional facts and photos. The insurer detects location and severity of the damage by automatically comparing it against millions of collision variables and applying predictive, model-driven AI. Heat maps are used as visible illustrations of the damage, building credibility with your policyholder. The internal workflow changes further when virtual inspections are powered by AI. Remote appraisers can be given photos, heat maps and even a guided estimating tool, reducing time and effort in the field and yielding higher accuracy and productivity, processing 15 or more estimates per day versus four to five estimates in a pre-AI, field inspection world. Once the estimate is written, information gleaned from the photographs is fused with insights gleaned from CCC’s wealth of estimating experience to determine if the estimate is in line with insurer guidelines. The appraiser views the pictures and, applying AI, builds out the estimate with interactive prompts to improve it. Thanks to AI, the policyholder is given an estimate in significantly less time than is possible today. AI also fuels communication that is more transparent and consistent with consumer expectations. When a vehicle is repairable, the policyholder doesn’t need to wait impatiently for days while the claims and repair process slowly unfolds in ways they don’t know about or understand. Instead, a consumer has access to a host of chatbot and SMS technology, where messages communicate the necessary steps to resolve the claim. Similar to how we book a restaurant reservation, the policyholder can schedule a repair shop appointment; and like an airline that can notify us of flight status, repair status updates have become standard practice for shops. Through the use of AI, services can be dispatched and intelligently routed to the repair shop of choice—or the salvage yard in the case of a total loss, saving time and money on additional tows and storage fees. From the policyholders' perspective, the insurer continues to prove that it has their best interests at heart, building trust and loyalty at a pivotal time in the relationship. In other words, an experience is built around AI, putting it to work to benefit the consumer. And, the same thing is happening for the estimator. On the casualty side, insurers handling first- and third-party claims can leverage AI to help inform investigations and increase loss cost management accuracy. For example, AI can detect the principal direction of force and the delta V to predict the likely physical injuries and outcomes of the vehicle’s occupants. There are early indications that integrating this data for analytics and intelligence purposes can improve claims outcomes, both by qualifying injury causation and revealing whether certain injuries are consistent with the facts of the accident. See also: Why AI-Assisted Selling Is the Future   AI Next What I’ve just described is the tip of the iceberg. We are at the tipping point. Connected cars will drive another wave of claims innovation. According to IHS Markit, worldwide sales of connected cars will reach 72.5 million units in 2023, up from 24 million units in 2015. That means, in just over eight years, almost 69% of passenger vehicles sold will be exchanging data with external sources. What does that mean for us? If I’m looking into my crystal ball, here’s what I see: When there's an accident, the amount of instantaneous information available to us will probably be 10 times what it is today. We won’t need policyholders to take the photographs I mentioned earlier. With telematics data, we will have all of the information that is knowable about an accident event, which makes the AI even faster and more accurate and claims management and related outcomes even that much better. If the car isn't that safe, it will be picked up by a self-driving tow truck and taken to the shop while another self-driving car will come pick up the policyholder. By the way, at the shop, no one's going to have to order any parts; the parts will be ordered within minutes, maybe even seconds after the accident. From an internal and external perspective, there is no downside to embracing AI’s promise: reduced claims costs, increased customer satisfaction and improved business outcomes – today and into the future. The value is there; the time is now.

"Insurance innovation" is often treated as an oxymoron, but it can't be. Innovation in the world writ large doesn't happen unless someone takes on the risk from a new technology or business model, and we all see new technologies and related business models flooding the market. Someone in the world of insurance and risk management has been doing something right.

Yet we still see a lot of puzzlement about how to sort through all the technologies that are suddenly becoming available to insurers as they try to innovate. The insurtech movement has moved through the first phase: We all know it's real. But what to do about the next phase, the get-an-actual-new-product-or-service-or-business-model-into-the-market phase? 

Companies are trying all kinds of things: innovation scouts, hackathons, sprints, "innovation tourism," including memberships at Plug and Play, etc. But there isn't a lot to show yet for all the effort by insurers. 

To see what companies are doing with innovation efforts and to help highlight what is actually working, we undertook a major research effort with our friends at The Institutes and supplemented that with nearly 1,100 hours of interviews with insurance executives working in innovation. Guy Fraker, our chief innovation officer, lays out some initial results in the first part of a three-part series, available here.

Two points stand out to me (though please read the whole piece, because there's a lot more there).

First, companies are tackling innovation in too piecemeal a fashion, mapped to the current structure, and need to coordinate across silos to be effective. Company structure is optimized to address questions that have already been answered, but innovation is about posing and answering new questions. The current structure can actually work against the innovation efforts, which are usually best done by a small, goal-oriented team that pays little attention to silos.

Second, a high percentage of executives said that their IT infrastructure limits their ability to innovate, but that's rarely true. There are, in fact, ways to innovate alongside a modernizing of the IT operation. Limitations can even make an innovation effort more focused and fruitful. 

Guy, having laid out an overview of the research in this first article, will get into more of the how-tos in the coming weeks. The good news is that innovation efforts, organized properly, can actually start smaller than you think -- and, no, you don't have to shell out big bucks for a membership at Plug and Play. And when you've succeeded once, you create momentum so that innovation efforts can build on themselves.

Have a great week. 

Paul Carroll
Editor-in-Chief

If lawyers are to represent insurers, if they are to be counselors in the fullest sense of the word, if they are to anticipate and answer questions of the highest importance, they must understand how technology continues to transform the insurance industry as a whole. They must not simply be aware of a few codicils and a minority of codes. They must be conversant with, so they can call and examine witnesses who are fluent in, the technology that influences everything from actuarial science to sales. I write these words as someone who has a law degree. Thus, I know how rigid legal curricula are versus how dynamic technology is. One predates computers, smartphones and tablets, save the ceremonial kind outside a courthouse, while the other has an increasingly short lifespan—its debut is also its death, because the one law not on the books is the law every lawyer should learn. I refer to Moore’s law. From careful observation of an emerging trend, Gordon Moore extrapolated that computing would dramatically increase in power, and decrease in relative cost, at an exponential pace. See also: 2 Steps to Transform Claims, Legal Group   According to Wayne R. Cohen, a professor at George Washington University School of Law and a partner at Cohen & Cohen, Moore’s law is crucial to how lawyers and insurers work together. He says: "More laws are not the solution to Moore’s law. What we need instead are competent lawyers who can advise insurers and be advocates for the rights of the insured, but within the changing technological landscape." I agree with Cohen’s point for several reasons. First is the health of the insurance industry. Insurers cannot succeed without lawyers to advise them, unless they want to issue policies that will compound their liabilities and weaken their ability to survive. Second, we cannot forfeit 2.7% of gross domestic product (GDP), or $507.7 billion, because a majority of lawyers cannot write the language necessary for insurers to underwrite the policies that consumers want to buy and that employers need to purchase. To repeat: We cannot have the innumerate or the technologically illiterate endorse what they do not know and cannot read, as if they were to register their approval by drawing an uppercase X on the signature line of a document, in lieu of confessing their own shortcomings. Third, unless insurers raise the technoloy issue with law schools or until the American Bar Association (ABA) raises the bar of competency, so to speak, new lawyers will find it difficult to get work and pay down their student loans. See also: 3 Major Areas of Opportunity   Let insurers be agents of change. Let them be agents that not only sell policies but help set public policy. Let them reach a verdict—let them issue a ruling as binding as any legal precedent—that is too decisive to reverse and too clear to reject. Lawyers who join this movement will inspire their colleagues to follow suit. They will be at the vanguard of law, technology and insurance. Their actions will ensure the safety of all we seek to insure.