Grace Vandecruze, managing director and founder of Grace Global Capital, talks about insurance industry M&A trends, and how technology of tomorrow will impact the ability of companies to compete and thrive in the future.

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Jamie Yoder, president of Snapsheet, talks about how his career helping advise insurers on how technology and information impacts their strategies has positioned him for a new role in putting that theory into practice to help Snapsheet serve its customers.

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Matt Mosher, Executive Vp and Chief Operating Officer of A.M. Best Co., talks about progress in the company's goal to include an analysis of innovation in its ratings of insurers.

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Mark Chester, CEO and Founder of Ley Line Advisory, discusses the company's goal to help insurance companies be more agile in adoption of new technologies and digital opportunities.

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An unmanned car driven by a search engine company? We’ve seen that movie. It ends with robots harvesting our bodies for energy.

That is a line from a 2011 Chrysler car commercial mocking Google’s self-driving car project. Another Chrysler commercial was even blunter: “Robots can take our food, our clothes and our homes. But, they will never take our cars.”

Chrysler’s early mocking of Google’s efforts exemplifies the fact that few cling to the status quo tighter than the companies that best understand it and have the most stake in preserving it. It is human nature to value what one does well and look askance at innovations that challenge the assumptions underlying current success.

Sprinkle in some predictably irrational wishful thinking and you have the mindset that too quickly dismisses potentially dangerous disruptions. Ironically, seven years later, those Google “robots” are now mostly driving Chrysler Pacifica minivans. Those robots have taken Chrysler's cars and driven more than 10 million miles.

Chrysler benefits by selling cars to Waymo, the spinoff from that Google project, but not nearly as much as it might have from building the robots themselves. Waymo is valued at $175 billion, about five times Chrysler’s market value.

History brims with other examples. When Alexander Graham Bell offered to sell his telephone patents to Western Union, the committee evaluating the deal concluded:

Messrs. Hubbard and Bell want to install one of their 'telephone devices' in every city. The idea is idiotic on the face of it… This device is inherently of no use to us. We do not recommend its purchase.

Ken Olsen, who disrupted IBM’s mainframe dominance with his DEC minicomputers, mocked the usefulness of personal computers in their early days. He declared, “The personal computer will fall flat on its face in business.” Olsen was very wrong, and DEC would eventually be sold to Compaq Computer, a personal computer maker, for a fraction of its peak value.

See also: Why AI IS All It’s Cracked Up to Be 

Steve Ballmer’s initial ridicule of Apple’s iPhone is also legendary, though the words of the then-CEO of Microsoft were mild compared with the disdain on his face when asked to comment on the iPhone launch. Years later, after he retired, Ballmer insisted that he was right about the iPhone in the context of mobile phones at the time. What he missed, he admitted, was that the strict separation of hardware, operating system and applications that drove Microsoft’s success in PCs wasn’t going to reproduce itself on mobile phones. Ballmer also didn’t recognize the power of the business model innovation that allowed the iPhone’s high cost to be built into monthly cell phone bills and to be subsidized by mobile operators. (Jump to the 4:00 mark.) The biggest challenge for successful business executives—like Ballmer, Olsen and those at Western Union—when confronted with potentially disruptive innovations is to think deeply about potential strategic shifts, rather than simply mock innovations for violating current assumptions.

Another perhaps soon-to-be classic example is unfolding at State Farm Insurance. State Farm released a TV ad that is a thinly veiled attack on Lemonade, a well-funded insurtech startup. Lemonade makes wide use of AI-based chatbots for customer service. State Farm, instead, prides itself on its host of human agents. In the ad, a State Farm agent says:

The budget insurance companies are building these cheap, knockoff robots to compete with us… These bots don’t have the compassion of a real State Farm agent.

As I’ve previously written, AI is one of six information technology trends that is reshaping every information-intensive industry, including insurance. In fact, as I recently told a group of insurance executives, I believe insurance will probably change more in the next 10 to 15 years than it has in the last 300.

See also: Lemonade Really Does Have a Big Heart 

That doesn’t mean that Lemonade’s use of chatbots for customer service will destroy State Farm. But, as State Farm should know, customer-service chatbots are only one of numerous innovations that Lemonade is bringing to the game.

As several McKinsey consultants point out, AI-related technologies are driving “seismic tech-driven shifts” in a number of different aspects of insurance. Lemonade has also adopted a mobile-first strategy and is applying behavioral economics to drive other business model innovations. State Farm executives need to get beyond the mocking and think deeply about how emerging innovations might disrupt their strategic assumptions.

One way to do so is being offered at InsuranceThoughtLeadership.com, where ITL editor-in-chief and industry thought leader Paul Carroll has offered a “State Farm Lemonade Throw Down.” Carroll offers to host an online debate between the two firms’ CEOs about how quickly AI technology should be integrated into interactions with customers. Lemonade’s CEO, Daniel Schreiber, has accepted. I hope Michael Tipsord, State Farm’s CEO, will accept, as well.

Better for Mr. Tipsord to face the question now, while there is ample time to still out-innovate Lemonade and other startups, than to be left to reflect on what went wrong years later, as Steve Ballmer had to do with the iPhone.

How do you increase quality in claims assessment, management and administration? We share insights into an end-to-end, AI-powered, claims-automation approach to increase quality, improve processing efficiency and reduce cost.

In this blog series, I’ve spoken about how AI increases process efficiency, reduces costs and helps business solve problems. I also showed how it enables smart business transformation by creating intelligent processes at every step along the value chain and intelligent products and services in the market. In my previous post, I illustrated how insurers can use AI-related technologies in underwriting and service management. Now, I’ll explain how AI helps insurers to manage claims more effectively and efficiently. How can insurers use AI in claims management? AI technologies make information systems more adaptive to humans and improve the interaction between humans and computer systems. By doing this, AI gives insurers an edge on how they manage claims—faster, better and with fewer errors. Insurers can achieve better claims management by using the intelligent technologies in some of the following ways:

• To enable a real-time question-and-answer service for first notice of loss;
• To pre-assess claims and to automate damage evaluation;
• To enable automated claims fraud detection using enriched data analytics;
• To predict claim volume patterns;
• To augment loss analysis

What are the benefits of using AI for claims management? In our  2017 Technology Vision for Insurance , we highlighted how Fukoku Mutual Life Insurance in Japan is using the IBM Watson Explorer AI platform to classify diseases, injuries and surgical procedures as well as to calculate claims payouts. See also: Insurers: Start Boosting Your ‘AIQ’   Our research has shown automated machine classification can be 30% more accurate than manual classification by humans and has the potential to increase productivity by 80%. AI-related technologies can enable higher quality in claims assessment, management and administration. It also supports improving the predictability of reserves and fraud. Smart machines can pre-assess claims and automate damage evaluation. Machine learning enables insurers to classify claims via email in the case of an accident or if medical care is required. It’s fast, accurate, efficient and simple to use. Case Study 1: Cognitive health insurance claims process management We have conducted a pilot with one of our insurance clients on the application of AI to its health insurance claims processes. This insurer’s health claims management process took about 11.5 minutes from receipt of the claim to updating it and closing the record. Scanning the paper documents and uploading them into the portal where they were categorized were the first manual steps. It took roughly five minutes to analyze the data, another five to verify rejection rules and one and a half minutes to accept or reject the claim. With our machine learning solution in place, a fully automated process was enabled and took only three minutes to do the same amount of work. This represents a 74% reduction in the claims settlement time. Furthermore, the machine learning technology applied was able to process health claims with 80% accuracy. The other 20% are incorrectly processed owing to spelling errors or database limitations. However, machine learning technologies are able to store and recall those errors for more accurate claims processing in the future. Case study 2: AI-powered automation of automobile claims processing Accenture was recently part of a major client initiative to identify technologies and partner for an AI-driven automation journey. We proposed and built a solution to automate processes to extract and classify data from commercial automobile claims PDF documents. The client faced many challenges, including having fewer than 400 records to classify 55 unique cases, and these records were mismatched and labeled inconsistently. The client also received scanned images containing text, owing to the redaction process followed to ensure data privacy. We developed an on-premise solution using a combination of IBM offerings and open-source technologies that enabled a detailed analysis of training data. The solution also helped the client to identify quality and sparse/skew data and to test various approaches to maximize performance. In the end, a blind data set of 207 claims documents was processed within a four-hour assessment window, and we were able to process claims PDF documents with scanned images as well as text, including several formats and layouts not part of training data. See also: How to Use AI, Starting With Distribution   We identified several pain points in the current claims management process:

• Error-prone manual data extraction;
• Inconsistent claim classification;
• The need for additional downstream validation;
• Increased time and cost for processing and resolution.

Solution proposed: In the next post, I’ll look at how AI-related technology can be used to improve customer services and policy administration. Get in touch to find out how you can use AI in the entire insurance value chain, or download the How to boost your AIQ report.

Last time, we discussed some of the potential benefits of AI in commercial insurance. Now, let's talk making the business case. Many insurers are hesitant to invest in AI without proof that these theoretically smart systems will yield real-world returns. A mature AI vendor will have the foresight to develop a team within its organization that’s dedicated to value analytics. This team — made up of data scientists and actuarial experts — will use the company’s own AI solution to run a simulation that can quantify potential savings that the solution could provide. This capability is crucial, as insurers don’t want to wait three or four years to realize a return. The value analytics team will take an insurer’s historical data and run the simulation. It might conclude that if the insurer had implemented this AI solution two years ago, it could have saved a certain amount — such as 5% to 10% — on claims costs. This percentage of savings might be based on a specific action, such as moving injured workers from low-ranked providers to high-ranked providers — or doing the same for attorneys. Or, the savings might encompass claims that could have avoided certain scenarios, such as surgery or litigation. See also: 4 AI Payoffs in Commercial Insurance   Once the AI solution is deployed against live data, the models continue to run every month (or quarter) based on a pre-defined set of performance metrics. Every month (or quarter), the calculations become more accurate, moving from a rough estimate to a tighter range and eventually to a precise calculation of savings achieved. Traditional models were challenged by the fact that claims are long-term transactions that can take as much as 18 to 24 months to close, but AI — with its machine learning — is able to handle this complexity with a high degree of accuracy. A Holistic Approach, Not a Silver Bullet In folklore, it’s the silver bullet that kills the wolf. This bullet has come to signify a simple solution that magically resolves an insurmountable problem. However, an important part of making AI real is understanding that, while it is powerful, it’s no silver bullet. At the end of the day, AI is most effective when it’s part of a holistic approach. All the pieces of the puzzle must be put in place. At a high level, these pieces include the AI technology itself, operational tweaks and metrics to gauge results. Impact follows when all these components work in harmony. When these conditions are there, we’ll begin to see the needle move on costs and outcomes. For example, insurers can use AI insights to create more efficient workflows; they can facilitate more effective hiring and training practices that enable human resources to apply their expertise at precisely the right moment in the claims process. It’s iterative, with machine learning driving change in a continuous cycle. See also: New Era of Commercial Insurance  Although immediate savings can be achieved, an enduring competitive advantage can only be realized when the application of AI is seen as a journey. It requires continuing effort and investment. Strategic players understand it can take a few years of making improvements to truly redefine their cost structure, customer experience and position in the market. The organizations that start early on the AI path with an iterative mindset will be well-equipped. We’re looking forward to an exciting decade ahead. As first published in Digital Insurance.

In the complex, diverse insurance industry, it can be hard to reconcile theory and practice. Adapting to new processes, systems, and strategies is always challenging. However, with the arrival of new opportunities, cultural transformation will go more smoothly. Insurance companies that are considering how to plug into the insurtech landscape should understand the various models within the innovation ecosystem. Carriers have to weigh their options carefully before choosing between incubators and accelerators, or venture capital and partnerships, when creating their best internal and external teams. The key elements disrupting the insurance industry include the Internet of Things (IoT), wearables, big data, artificial intelligence and on-demand insurance. Although well-established business models, processes and organizations are being forced to adapt, insurtech can be more collaborative than disruptive. It is no secret that the insurance industry is responding to changing market dynamics such as new regulations, legislation and technology. With digital transformation, there are numerous ways technology can improve and streamline current insurance processes. See also: Rise of the Machines in Insurance   Cognitive Computing Cognitive computing, a subset of AI, mimics human intelligence. It can be deployed to radically streamline industry processes. According to the 2016 IBM Institute for Business Value survey, 90% of insurance executives believe that cognitive technologies will have an impact on their revenue models. The ability of cognitive technologies to handle both structured and unstructured data in new ways will foster advanced models of business operations and processes. Insurance carriers can use this technology for improved customer self-service, call-center assistance, underwriting, claims management and regulatory compliance. Big Data Unstructured data is rapidly growing every day. For instance, wearables can provide insurance companies with massive amounts of data that can yield insights about their markets. Social media also produces a flood of data. To harvest this data intelligently, insurers need to adopt the right analytical solutions to analyze, clean and verify data to customize their offerings according to their clients’ individual needs. Predictive analytics evaluates the trends found in big data to determine risk, set premiums, quote individual and group insurance policies and target key markets more accurately. Linking the Two Insurance organizations may have more data than they realize or know what to do with. Existing data is coming in from different core systems, and new data is being captured with IoT devices like wearables and sensors. Cognitive computing is the link to organizing and optimizing this data for use. See also: Strategies to Master Massively Big Data   Whether it is used to predict risk and determine premiums, flag fraudulent claims or identify what products a customer is likely to buy, cognitive computing is the way to ensure these goals are achieved. Sorting these trends among reams of data makes them more manageable and ensures that a business’s IT objectives link back to business strategies. Over the years, systems will evolve through learning processes to a level of intelligence that can adequately support more complex business functions. Schedule a meeting with your executive team to examine risks, opportunities and insurtech synergies that can take your organization beyond the competition.

It seems that with every advancement in technology a new threat vector is born. This theory holds true as we begin to embrace the world of cryptocurrency. Cryptocurrencies have emerged as an alternative means for financial transactions, while the value of a single Bitcoin cryptocurrency rose to $20,000 in late 2017. Hackers took notice and succeeded in stealing over $1 billion in cryptocurrency in 2018 alone. Unfortunately, the cyber threat goes beyond the theft of the currency itself. This new platform has given birth to a cyber crime known as cryptojacking. Cryptojacking Defined Cryptocurrency can be earned by a process called cryptomining. Cryptominers must first solve complex mathematical problems to validate transactions. To do this, they use software to create a very complex cryptographic puzzle that requires massive amounts of computing power. Rather than use their own resources, cyber criminals infiltrate the networks of unsuspecting victims to leverage the victim’s computers for their own mining activities. Hackers then send the results back to servers they control. This often results in slowing or crashing of computer systems, equipment replacement costs, increased energy costs and lost productivity. See also: Cyber: Black Hole or Huge Opportunity?   There are several attack methods, including:

• Phishing emails: The victim clicks on a malicious link or attachment. This runs a code that injects a cryptomining script on the target computer. The script will continuously run, often undetected.
• Drive-by mining: The hacker injects a cryptojacking script on targeted websites or pop-up ads. When a victim visits that website or receives a pop-up from the infected ad, the script will run and infiltrate the network.
• Rogue employees: Insiders with access to IT infrastructure can set up cryptojacking systems, including physical servers, within the workplace premises.

Preventing a Cryptojacking Attack There are several strategies that may help prevent a cryptojacking attack:

• Web filtering tools should be used to block websites that are known to spread cryptojacking scripts.
• A cryptojacking ad blocker can be installed to prevent infected ads from popping up.
• Endpoint detection technology can recognize known crypto miners as soon as they penetrate the network.
• Mobile device programs can manage vulnerable apps and malicious extensions that may be found on employee-owned devices.
• Employees must be educated to recognize phishing emails in security awareness training programs.

Transferring Cryptojacking Risk Many cyber security experts will agree that there is no silver bullet that will prevent all cyberattacks. As a result, the commercial cyber insurance market has evolved along with cyber threats to facilitate options for cyber risk transfer. These insurance policies can provide indemnification for both first-party direct costs and subsequent third-party liability costs in the aftermath of a cyberattack. See also: The New Cyber Insurance Paradigm   While policy wording can differ among insurance companies, there are common coverages that are found in many policies. These may be especially helpful in transferring financial losses specific to a cryptojacking attack, including:

• Business Interruption – The cumulative effect of the slowing of hundreds or thousands of computers in one organization can lead to significant cost over time. Components may fail prematurely due to overuse, and critical controls may be affected. The resulting downtime and restoration process may cause financial loss, which may be recovered under a cyber insurance policy.
• Network Security Liability – Companies may unknowingly transmit cryptomining code to other organizations, creating legal liability. Litigation costs and settlements may be covered under these policies.
• Crisis Management – Hackers may change tactics after the initial cryptojacking attack. Once they have access to networks, they may move laterally and access sensitive information that they can monetize, such as Social Security numbers and financial records. Costs to retain external vendors to investigate and respond to the attack, including IT forensics firms, privacy attorneys, credit monitoring fees, notification and call center costs, may be covered.
• Increased costs due to fraudulent use of a victim’s vendor services, such as a cloud provider or internet-based services, may also be a covered cost.

In light of the emerging threats posed by cryptojacking criminals, it is imperative that steps are taken to prevent, mitigate and transfer the risk. Technology-based controls, employee training and insurance risk transfer mechanisms should all be considered.

A recent social media dust-up between renters and homeowners insurance technology upstart Lemonade Insurance and old-line insurance industry stalwart State Farm motivated us to look at what their respective customers are saying about their experiences with the companies. A little context: State Farm recently aired a television commercial poking fun at technology-focused entrants to the marketplace. Specifically, the commercial made fun of the use of bots (artificial intelligence) used to process claims. Lemonade was quick to respond to the perceived slight, with early Lemonade investor Ashton Kutcher even weighing in on Twitter. Kutcher has since deleted his tweet, but Coverager captured it in a screenshot. To support its claim that Lemonade leverages technology to provide a customer experience superior to State Farm, Lemonade’s CEO Daniel Schreiber published, compared and contrasted its renters insurance customer rating and ranking to State Farm from Clearsurance's independent platform. You can see Clearsurance’s full renters insurance rankings here. Full disclosure: Lemonade is an engaged subscriber and affiliate marketing partner of Clearsurance. State Farm is not currently a subscriber. Being a subscriber does not enable any company to manipulate their customer ratings, which derive 100% from customer feedback. See also: New Entrants Flood Into Insurance   With that context, let’s see what renters insurance policyholders are saying about each company. Below is a table that includes renters insurance ratings of Lemonade and State Farm for six different categories. It’s important to note that, given that Lemonade was founded in 2015 and has a vastly smaller market share than State Farm, the startup insurer has far fewer renters insurance reviews (57) on Clearsurance than State Farm (1,349). Given that, the data should be taken with a grain of salt as Clearsurance user testing has revealed that the more reviews on a company, the more weight a consumer assigns to that company’s rating. *Lemonade's claim service rating based on just nine reviews Time will ultimately tell whether Lemonade can maintain these high customer ratings as it scales and receives more reviews from its policyholders. Still, we can at the very least get a sense for how consumers feel about Lemonade’s technology-based insurance. And the early returns portend a customer base that is highly satisfied with the experience. Despite not having agents like State Farm, which has more than 18,000, Lemonade has a 4.75 customer service rating out of 5. The part of the story that’s harder to tell with the data is how consumers’ experience has been at the time of a claim. Lemonade’s 4.33 claim service score is based on just nine reviews, which isn’t enough to draw any conclusions. By comparison, State Farm’s 4.26 claim service rating (based on 267 reviews that include a claim) and 4.41 customer service rating are both among the best for renters insurance companies. The largest discrepancy between the two companies is price. Lemonade has received a 4.80 rating from consumers for price, while State Farm’s 4.21 price rating is its lowest of any of the six categories we collect ratings on. Beyond just the ratings, though, consumer feedback within reviews has helped provide us with a look at what their policyholders value. Lemonade’s policyholders frequently discuss the ease of working with the company, things like getting a quote, buying a policy and setting up the coverage. In fact. 53% of Lemonade reviews discuss ease of the user experience while just 15% of State Farm reviews do so. The online services of Lemonade are also a main focus of reviews. More than a third of Lemonade reviews (35%) discuss the companies’ online and application-services while just 3% of State Farm reviews address the insurer’s online services. Instead, State Farm reviews are more apt to talk about agents (18%, compared with 0% for Lemonade, which has no agents). All this isn’t to say consumers have indicated one method — agent or bot — is better than the other. Quite the contrary, in fact. The consumer ratings data shows that both methods are pleasing the companies’ respective policyholders. State Farm and Lemonade appear to be geared toward different demographics and different service preferences. Some may prefer the personalized service an agent can provide. Others may prefer the ease and speed of a bot — like Lemonade’s Maya. That’s what this data indicates. And both companies appear to be enjoying success of their different business strategies. Lemonade has raised $180 million in funding and just last week was one of the companies Forbes named in a list of the next billion-dollar startups. State Farm, meanwhile, holds the largest P&C market share in the U.S. See also: Making Lemons From Lemonade   The misconception in all this — and why Lemonade may have taken offense to State Farm’s commercial — is that it insinuated agents are far superior to bots. The State Farm agent in the commercial says, “These bots don’t have the compassion of a real State Farm agent.” While more State Farm reviews use words describing the helpfulness of the company (15% to 7% for Lemonade), the customer service ratings in the table above indicate that isn’t the only part that matters. In today’s technological age, customer service in the eyes of the consumer may not just be about being compassionate. It factors in things like ease and speed, too. We would submit that saving a customer time from having to think about insurance is an act of compassion. What this means for Lemonade and State Farm in years to come remains to be seen. For now, a majority of the policyholders from these companies have indicated they’ve had a positive experience. If you’ve held a policy with Lemonade or State Farm, share your experience on Clearsurance to help better inform other insurance shoppers. This article originally appeared on the Clearsurance blog.