In a world of straight-through-processing and “touchless” claims, customers are demanding faster pay-outs on their insurance claims through smarter, more intuitive digital interactions and customer-centric support models.
Until fairly recently, standard industry processes have allowed time for loss adjustors, claims handlers and expert SIU investigators to appropriately assess customer claims. This approach has been a largely effective, but resource-intensive control on fraud. However, with the introduction of increasing automation, there is far less time available now for human review.
Insurers want to keep customers happy with smooth and rapid processes, but they also want to be confident that they are paying the right people, in the right circumstances, and limiting the opportunity for fraud. To achieve both of these objectives, real-time risk detection technology has a crucial role to play.
The far-reaching impacts of fraud
Insurance fraud has too often been regarded as a victimless crime. The reality is very different. Fraud has an immense impact on society, seriously damaging trust as well as creating material financial implications. According to the Coalition Against Insurance Fraud, criminals steal at least $80 billion every year from American consumers. Premiums rise to manage this additional risk, affecting all customers. Fraud also hurts loss ratios, disrupts daily operations, distorts pricing and affects reserves calculations.
And it’s not just insurance companies that pay when criminals carry out fraud—innocent people, often customers, get caught up in these crimes more often than most would like to think. Arson, murder-for-hire, crash-for-cash, staged accidents and medical malpractice are all examples where organized crime groups have targeted innocent citizens and exposed them to physical harm.
With insurance processes digitizing at an increased rate, the opportunity for fraud has expanded significantly, and it is vital that appropriate responses to those threats are available.
Anti-fraud technology has already evolved at an exceptional rate in the last five years, which has included the creation of better investigation tools and experimentation with data science or machine learning techniques But insurers should not accept yesterday’s technology when they can be pushing for tomorrow's:
Scoring and alerting should be available in real time to keep pace with the demands from automated claims management workflows.
Analytics should be transparent and explainable so that the work and decisions of investigators are defensible.
Technology should be built on open architecture, should be capable of integration with core claims management or underwriting systems in real time and should offer flexibility for deployment in the cloud or on-premise.
Expert investigators and skilled data scientists should be able to focus on the highest-value cases rather than being frustrated by mundane data tasks.
Software and systems should support processes where appropriate, but insurers should be able to independently own and manage their own analytics without relying on external services.
Many companies find themselves working with siloed data, attempting to catch irregularities across unconnected data sets. Instead, insurers should demand a single view of all parties—policyholders, claimants, suppliers, brokers—to work within a single data set.
Insurers should also be able to use fraud management technology to easily detect and manage instances of identity manipulation—the slightest change between a name, date of birth, ID or address should be easily spotted and flagged, even if it’s across multiple data sets, to root out fraud without delay. Detection should also consider the relationships between parties, which is often as crucial to understand as the circumstances of each individual claim.
Data privacy regulation has changed significantly in the last decade with the introduction of new laws such as the California Consumer Privacy Act or GDPR in the EU. To ensure compliance. security models must be sufficiently granular and be able to support different user types in accessing different levels of data according to their specific permissions.
Finally, rather than opting for point detection solutions, analytics capabilities should be applied to deliver value across the enterprise. For example, intelligence that can be gained from a claims fraud detection solution can be highly valuable for detecting and preventing underwriting fraud. The same intelligence can equally be helpful in identifying churn risk or upselling opportunities. The technologies being deployed for fraud should also be sufficiently scalable and robust to service multiple use cases to maximize value and achieve a far lower overall cost of ownership.
Customers want to associate their insurers with stability, trust, competence and airtight operations. With so much innovation happening globally, now is the moment for insurers to think big and evolve their enterprise fraud capabilities. Fraud is not a victimless crime, it is not the cost of doing business and we do not have to accept the status quo.
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With cloud computing, insurers can most effectively use big data and predictive analytics to personalize insurance offerings, accelerate the underwriting and claims processes, catch fraudsters more easily and reduce their IT spending.
In August 2008, a service outage changed how a streaming service would do business in the future. Netflix had a database corruption incident in one of its private data centers. The issue meant Netflix could not ship DVDs for three days, which translated to millions of dollars in lost revenue. That wasn’t the first time the company had struggled.
As Netflix would reveal years later, its on-premise data center systems were struggling to scale quickly enough to meet demand. Instead of taking the short-term route and fixing only the local data center, Netflix went all out and migrated to an instantly scalable cloud infrastructure. Along with streaming "House of Cards," moving to the cloud was probably one of the best business decisions Netflix has ever made.
Do Insurance Companies Need to Migrate to the Cloud?
Growth-minded insurers should consider why motivated companies like Netflix chose cloud migration over a decade ago.
Dave Hahn, a senior engineer in cloud operations at Netflix, said the company would have had to spend billions of dollars to create world-class data centers in multiple, global locations if it wanted to continue using on-premises systems. Netflix also knew it would suffer future outages in separate data centers if it didn’t move its operations to the cloud.
Future proofing infrastructure and existing business offerings was only half of the issue. The cloud brings with it the potential for new offerings and the ability to optimize the customer’s experience. One of the most profitable benefits of cloud migration is how it supports Netflix’s use of big data, artificial intelligence and machine learning at speed and scale to make personalized program recommendations based on what a person has watched.
How It Works
For insurance companies, a custom cloud setup can help them harvest insightful data on policy holders in real time. This data can help organizations determine an individual’s likely risk and to personalize and price insurance products based on each customer’s behavior. The cloud also supports the collection and analysis of real time data provided by IoT devices, such as black boxes in cars or wearable tech that monitors health and physical activity, to moderate customer behavior and to reduce the risk of a claim and offer reduced premiums.
What Cloud Computing Applications Exist for Insurers?
Cloud computing for the insurance industry comes in several powerful forms.
1. Personalized Insurance Products and Improved Customer Experience
Cloud computing can help businesses harness the power of artificial intelligence (AI) and machine learning (ML). Here are some examples.
Insurers can collect more data about customers in one place and over a long period. Querying such data would help them understand their customers better for claims and fraud detection.
A company can run big data analytics against all of its claims’ databases, as well as databases now being shared across multiple organizations, to discover individual patterns or group customers’ behaviors. This big data sharing can accelerate the claims process, enhance the customer experience and greatly increase fraud detection. As early as 2016, Lemonade Insurance stated that its AI chatbot “Jim,” supported by real-time big data analytics, settled a claim within three seconds. Perhaps this is exceptional, but insurance wait times and process duration and costs can be significantly reduced.
IoT devices can be linked to cloud databases and machine learning applications to collect and analyze customer information in real time to encourage positive behavior and reduce risk/claims.
Insurers can also employ data mining techniques to better predict customer profitability and policy risk. This would inform the company about whether it needed to raise its policy pricing or offer new products for specific individuals or groups.
Cloud computing is the foundation for boosting customer attraction/retention, improving fraud mitigation and increasing ROI on insurance IT spending.
2. Room to Grow at Your Own Pace
One significant benefit cloud computing has over on-premises systems is that insurers can scale operations and infrastructure on-demand to adjust to market changes, including accommodating spikes in demand for products and services.
Conversely, a business can scale down to save costs when capacity is not required. For example, an insurer can limit the amount of bandwidth used on off-peak days, months or seasons; they can even stand up and tear down test environments automatically.
3. Remote Agents
The insurance industry had distributed field teams way before the pandemic forced other sectors to consider working remotely. However, cybersecurity attacks have increased 800% since the start of the COVID-19 pandemic. Most cyber threats target employees who are working outside their company’s premises via the internet.
Some 36% of participants in a PWC study said they had not conducted risk assessments on their connected devices. About half of the ones who did said they did not know how to address the issues they uncovered. Insurers using legacy applications may be risking their valuable data and reputations.
Using a cloud platform maximizes security for remote insurance workers, allowing them to focus on signing up more clients. Insurers can worry less about data breaches, adverse publicity and potential lawsuits that may damage their brand.
Moving to the cloud greatly reduces the need to buy and maintain physical IT components such as networking equipment and servers. Migrating the company infrastructure from on premise will also remove significant maintenance and upgrade effort and costs.
Like Netflix, an insurer no longer has to spend a fortune on building and maintaining world-class data centers. It only needs to migrate its data and upgrade some of its core insurance software solutions to be able to capitalize on the competitive advantages of working in a cloud environment.
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Artificial intelligence (AI) holds a lot of promise for the insurance industry, particularly for reducing premium leakage, accelerating claims and making underwriting more accurate. AI can identify patterns and indicators of risk that would otherwise go unnoticed by human eyes.
Unfortunately, AI has often been a black box: Data goes in, results come out and no one — not even the creators of the AI — has any idea how the AI came to its conclusions. That’s because pure machine learning (ML) analyzes the data in an iterative fashion to develop a model, and that process is simply not available or understandable.
For example, when DeepMind, an AI developed by a Google subsidiary, became the first artificial intelligence to beat a high-level professional Go player, it made moves that were bewildering to other professional players who observed the game. Move 37 in game two of the match was particularly strange, though, after the fact, it certainly appeared to be strong — after all, DeepMind went on the win. But there was no way to ask DeepMind why it had chosen the move that it did. Professional Go players had to puzzle it out for themselves.
That's a problem. Without transparency into the processes AI uses to arrive at its conclusions, insurers leave themselves open to accusations of bias. These concerns of bias are not unfounded. If the data itself is biased, then the model created will reflect it. There are many examples; one of the most infamous is an AI recruiting system that Amazon had been developing. The goal was to have the AI screen resumes to identify the best-qualified candidates, but it became clear that the algorithm had taught itself that men were preferable to women, and rejected candidates on the basis of their gender. Instead of eliminating biases in existing recruiting systems, Amazon’s AI had automated them. The project was canceled.
Insurance is a highly regulated industry, and those regulations are clearly moving toward a world in which carriers will not be allowed to make decisions that affect their customers based on black-box AI. The EU has proposed AI regulations that, among other requirements, would mandate that AI used for high-risk applications be “sufficiently transparent to enable users to understand and control how the high-risk AI system produces its output.” What qualifies as high-risk? Anything that could damage fundamental rights guaranteed in the Charter of Fundamental Rights of the European Union, which includes discrimination on the basis of sex, race, ethnicity and other traits.
Simply put, insurers will need to demonstrate that the AI they use does not include racial, gender or other biases.
But beyond the legal requirements for AI transparency, there are also strong market forces pushing insurers in that direction. Insurers need explainable AI to build trust with their customers, who are very wary of its use. For instance, after fast-growing, AI-powered insurer Lemonade tweeted that it had collected 1,600 data points on customers and used nonverbal clues in video to determine how to decide on claims, the public backlash was swift. The company issued an apology and explained that it does not use AI to deny claims, but the brand certainly suffered as a result.
Insurers don’t need to abandon the use of AI or even “black-box” AI. There are forms of AI that are transparent and explainable, such as symbolic AI. Unlike pure ML, symbolic AI is rule-based, with codes describing what the technology has to do. Variables are used to reach conclusions. When the two are used together, it’s called hybrid AI, and it has the advantage of leveraging the strengths of each while remaining explainable. ML can target pieces of a given problem where explainability isn’t necessary.
For instance, let’s say an insurer has a large number of medical claims, and it wants AI to understand the body parts involved in the accident. The first step is to make sure that the system is using up-to-date terminology, because there may be terms used in the claims that are not part of the lexicon the AI needs to understand. ML can automate the detection of concepts to create a map of the sequences used. It doesn’t need to be explainable because there’s a reference point, a dictionary, that can determine whether the output is correct.
The system could then capture the data in claims and normalize it. If the right shoulder is injured in an accident, symbolic AI can detect all synonyms, understand the context and come back with a code of the body part involved. It’s transparent because we can see where it’s coded with a snippet from the original report. There’s a massive efficiency gain, but, ultimately, humans are still making the final decision on the claim.
AI holds a lot of promise for insurers, but no insurer wants to introduce additional risk into the business with a system that produces unexplainable results. Through the appropriate use of hybrid AI, carriers can build trust with their customers and ensure they are compliant with regulations while still enjoying the massive benefits that AI can provide.
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Some topics are sure-fire conversation-killers at cocktail parties—your juice cleanse, recent dental procedures and your bottle cap collection, for example. Document management systems may fall into that category. While industry professionals may find shop talk engrossing, the eyes of the average person almost certainly will glaze over after only a few minutes of imaging and versioning chatter.
Efficiently managing documents may not be sexy, but it is vitally important to organizations. Knowledge workers often feel overwhelmed by the amount of information they must process daily: CIOInsight reported that 83% of professionals believe that today's "accelerated pace and connectivity of business" require them to produce, share, manage and distribute more documents than before. Inadequate systems and overwhelmed employees result in process inefficiencies, suboptimal decision-making and heightened business risks.
Certificates of insurance (COIs) present a particularly vexing document management challenge for risk management professionals. Tracking COIs—documents that confirm that adequate amounts of the right kinds of insurance from satisfactory insurers are in place—is essential to ensure that organizations are protected against losses resulting from contractors, vendors, tenants and others. But the sheer volume of COIs to be cataloged and reviewed, and the time and resources required to analyze and respond to them properly, can be overwhelming. Document management tools and processes are essential to effective COI administration.
Document management is mundane – but don’t fall asleep at the wheel
Document management enables organizations to effectively capture, distribute, track, store and retrieve electronic documents, ensuring that everyone in an organization has access to reliable, up-to-date information when and where it is needed.
Risk and insurance management has always been a document-intensive process, and diligently handling the information has long been an essential skill for every risk management organization. Over the lifecycle of a typical commercial insurance relationship, hundreds, or even thousands, of documents are generated by internal stakeholders, the broker, the insurer and service providers such as claims administrators. For companies that rely significantly on contractors, vendors or tenants, managing certificates of insurance can be a full-time role. It certainly won’t be the “chest-beating” part of the business, but not giving it the appropriate attention can lead to disastrous consequences, including failed risk transfer, leaving undeserving companies (and their insurers) with a claim.
Companies now have an array of options for improving their document management practices. Off-the-shelf and customized document management software solutions can help tame the blooming, buzzing document jungle in which many risk managers find themselves. They make creating, sharing, storing, retrieving, securing and reviewing documents easier. They also can enhance productivity, reduce the risk of document misuse, augment data security and improve compliance with regulatory requirements.
Managing certificates of insurance
Organizations routinely transfer certain types of risk through contracts with vendors, contractors, tenants and others. COIs—which capture all the essential details of an insurance policy in an easy-to-read, standardized format—assure an organization that its vendors, contractors or tenants can meet their liability obligations under these various contracts.
For many organizations, COIs are the largest category of documents managed by a risk management department. Big companies—especially large contractors—may track tens of thousands of COIs, insurance forms and often complete policies. Making sure that insurance coverage is adequate, appropriate, current and from acceptable insurance carriers is complex and time-intensive. Industry experts estimate that one full-time person is required to track every 1,500 COIs properly. In many cases, risk management departments cannot afford the staffing to do the job adequately.
Properly managing COIs requires more than simply verifying the existence of insurance policies. Ensuring that the policies provide adequate coverage that complies with contractual terms requires specialists in insurance policy wording who can determine whether insurance coverage is appropriate for the risks assumed by a vendor, contractor or tenant. Maintaining this level of expertise in-house may be beyond the means and budget of many risk management departments. An outsourced solution is often the most cost-effective way to ensure that COIs are properly managed.
Achieving superior document management
The typical risk management department has enormous responsibilities and limited resources. Efficiency is essential, but so is accuracy—mistakes can have damaging and far-reaching consequences. Effective document management can help to simplify routine activities, accelerate processes and ensure that all stakeholders have access to up-to-date, accurate information as it is needed. Risk managers often struggle to justify new expenditures in the competition for budget allocations, but an effective document management system should be seen as a long-term cost-reduction exercise with the potential to lower the overall cost of risk.
Effectively administering COIs and related insurance documentation is one of the most substantial benefits of a disciplined approach to document management in a risk management department—but also one of the biggest challenges. Some organizations manage thousands of COIs, and a single mistake can cost millions of dollars. COIs demand constant attention from contracts and insurance coverage experts. Risk management departments should consider outsourcing this function to specialists who can cost-effectively provide both process efficiency and domain expertise.
If history is a guide, the needs of risk management departments will only increase as risk managers are called on to do more without a corresponding increase in budget or resources. They cannot squander precious time by chasing after documents or questioning whether they are working with the most up-to-date information. They also cannot afford to make avoidable mistakes caused by inadequate, incomplete or out-of-date information. Document management may not make for sparking conversation at a cocktail party, but it can make all the difference in the world in improving the efficiency, effectiveness and accuracy of risk management processes.
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Martin Mick is the co-founder and CEO of Docutrax, a knowledge-based business service that identifies and reduces insurance-related third-party risk to a wide variety of industry verticals.
Digital transformation initiatives are accelerating because of the pandemic and the mandate to “go digital.” Even more important are the changing expectations of insureds, particularly millennials, who have grown accustomed to receiving products when, where and how they want them. Even boomers have these very same expectations.
Given that digital technology is driving nearly every major industry, it is a wonder that it has taken so long to garner a foothold in insurance. The simple reason is that the insurance industry didn’t have to. Everyone was on the same page. There was no risk of falling behind.
But that was then, and this is now.
Today, insurers must continuously align with where consumer interest and appetite are tracking, modifying organizations and resources to the quest without losing sight of ease and simplicity. As the insurance sector frantically tries to make up for lost time, those insurers that will win the future will be those that deliver an Amazon-like experience for the customer.
This goal may prove difficult, however, as many incumbent carriers are NOT focused on the customer. Ironically, many multi-line carriers operate as multiple single-line carriers because they do not look at the customer as a channel. A number of industry upstarts, however, have stepped in to fill this void. Lemonade, for example, has been able to expand its portfolio quickly and bundle different policies using modern technology.
By packaging up a suite of insurance products in a simple, comprehensible way, insurers will find themselves in sync with what customers really want: simpler, one-stop shopping, with easy, omnichannel buying journeys. Customers are difficult and expensive to acquire, so retention is all too important. Our research shows that the greater the number of policies a policyholder has with a single insurer, the greater the loyalty and the lower the churn. The more an insurer can meet a consumer’s diverse needs in a simpler way, the more recurring revenue the insurer will derive from each customer – even to the point of becoming their sole insurance provider.
There is a huge opportunity for insurers to design products and solutions that not only protect health, wealth and risks but work with people’s lifestyles to prevent injury or loss and the subsequent claim. For insurance providers to be able to make the most of these opportunities, they must adopt more customer-centric business models – and that means addressing issues with their legacy infrastructures, which were designed for a product-centric approach. The insurance industry of tomorrow will be more than just a product; it will be an experience.
With the technology that has been used by insurers for decades, and even with many modern legacy core systems deployed just a few years ago, it is impossible to add a usage-based or episodic insurance product. It is equally difficult to sell a bundle of different types of insurance products in one go or bundle insurance and non-insurance products to add unique value. Those modern legacy systems were designed for a more traditional era of insurance. They served their purpose for yesterday, but tomorrow will be quite different.
To be competitive in the modern market, insurers must adopt cloud-native, microservices and API-rich insurance platforms. These new technology platforms for the future of insurance, called coretech, bring together the core operational and digital insurance capabilities needed to support emerging business models and leverage insurtech innovation and data for growth in emerging B2B and B2C ecosystems.
At EIS, we have embraced the ecosystem-enabling fundamentals of coretech to help some of the top carriers in the industry, including a 100 year-old bastion looking to transform their antiquated technologies and modernize their processes.
Key decision-makers contemplating a coretech solution must first take a look at their existing business architecture and ask themselves some hard questions, such as: Is it product- or customer-centered? Are we limited by closed-in architecture, lack of application programming interfaces (APIs), or an inability to participate in ecosystems? Can we only sell products that our modern legacy system will allow us to sell?
Upstarts to the industry are the manifestation that change is needed and validation that many carriers are currently failing. A mindset change is what’s needed, and insurtechs, focused entirely on the customer experience, are quickly stepping in to fill the void. All of this disruption is causing insurance companies to quickly reevaluate their infrastructures. Carriers can be fast followers when change can quickly take their business away.
It’s no accident that so many of the businesses we interact with on a daily basis already embody this customer-centric notion, adapting what they do and how they do it to customers' needs and preferences on a real-time basis. It’s all driven by data, and the massive expansion of our ability to collect, interpret and apply it. Bringing this potential into the heart of the business will align insurers to consumers’ true north – as the obvious choice in a crowded market.
The insurers of the future will be those that enable digital ecosystems that place the customer at the center, and view the customer as the channel so that insurers can offer the products and services that the customer wants, not what a legacy system allows them to sell. Incumbent players have a powerful opportunity to drive the industry forward and bring customers with them.
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Anthony Grosso is the industry lead, insurance markets, at EIS.
He has more than 25 years of hands-on experience leading innovation, business development, product, and marketing across all sectors of the insurance industry.
Not long after I got involved with ITL, going on eight years ago, I spoke at a conference where I heard an extraordinary question about life insurance. Following a presentation that highlighted the industry's desultory sales, an audience member stood up and said, "States require drivers to buy auto insurance. Banks require people to carry homeowners insurance if they have a mortgage. Do you think there's any way to have people be required to purchase life insurance?"
"Wow," I thought. "How bad off must the industry be if someone's best hope for increasing sales is to force people to buy the product?"
A lot has changed since then, as you can see from the six articles we're highlighting as part of this month's ITL Focus. The purchasing process has in many cases been sped up considerably, partly because of policies that no longer require medical exams or blood and urine tests. A better understanding of behavioral economics has helped carriers and agents get past some of the mental hurdles that have limited purchases. Some carriers are moving beyond the emphasis on the death benefit and providing what might be thought of as life benefits -- e.g., finding ways to encourage healthy behavior.
I suspect we're not even close to done with the progress. It seems to me that the lines will increasingly blur between life insurance and financial management, given that life insurance is an important financial asset; people often think about their finances, and life insurance can become a natural part of that focus. I could also see the trend toward embedded insurance expanding the life insurance market -- why couldn't a term life policy be, for instance, embedded in a mortgage when someone buys a building, to make sure the purchase is secure even if something happens to the buyer?
Over the years, I've had people tell me life insurance is boring. I don't see it that way at all.
- Paul Carroll, ITL's Editor-in-Chief
WHAT TO WATCH
The Future of Blockchain: Usage in Life and Annuities
Blockchain is providing a solution for the insurance industry to share information easily and slash operating costs. Having explored the possibilities for blockchain in personal lines and commercial lines in P&C, we conclude our webinar series on the technology (for now) by taking a look at two use cases in life and annuities that are close to moving into production.
WHAT TO READ
What Is Happening to Life Insurance?
IIS expert Ronnie Klein explores why so many are exiting individual life insurance, then explores a new model.
How Life Insurers Can Reach Millennials
Millennials already understand the need for car and home insurance. The pandemic has given life insurers an opportunity.
Behavioral Science and Life Insurance
Carriers must fully grasp human biases and behaviors and harness technologies to improve health.
Where Does Life Insurance Go Now?
Between the shift to a remote workforce, and the pandemic itself, life insurance had no choice but to evolve -- and there's no going back.
Simplicity, Magic in Life Insurance Sales
Everything we’ve learned about e-commerce design can be applied to the life insurance consumer--no matter where or how a policy is purchased.
Solving Life Insurance Coverage Gap
We are now seeing the fruits of our labors materialized into a genuine straight-through process for term life.
Insurance Thought Leadership (ITL) delivers engaging, informative articles from our global network of thought leaders and decision makers. Their insights are transforming the insurance and risk management marketplace through knowledge sharing, big ideas on a wide variety of topics, and lessons learned through real-life applications of innovative technology.
We also connect our network of authors and readers in ways that help them uncover opportunities and that lead to innovation and strategic advantage.
Six Things Newsletter | August 31, 2021
In this week's Six Things, Paul Carroll looks at a behavioral science scandal. Plus, tomorrow's insurance is connected; boosting cyber hygiene with insurtech; mental health in a post-COVID era; and more.
In this week's Six Things, Paul Carroll looks at a behavioral science scandal. Plus, tomorrow's insurance is connected; boosting cyber hygiene with insurtech; mental health in a post-COVID era; and more.
A much-cited claim about how behavioral science can guide insurance has been exposed as fraudulent. The claim was made most prominently by Dan Ariely, a best-selling author and pioneer in the field of behavioral economics, who was Lemonade’s chief behavioral officer from 2015 through 2020. But the claim turns out to be based on fabricated data.
Tune in to this month’s webinar as industry experts reveal insights to next-gen distribution management that will help insurers grow and retain their distribution channels.
Peter Drucker once famously said that “what gets measured gets managed,” and the Insurance Information Institute is unveiling measures for U.S. communities’ resilience against natural disasters. In this webinar, ITL Editor-in-Chief Paul Carroll and the Triple-I’s senior economist, Michel Leonard, discuss what the measures cover, how individuals and communities can use them and where the Triple-I will take them from here.
Cognitive computing is a funny beast. Every time you hit your target, you find that another pops up off in the distance.
When I first saw a demonstration of speech recognition, some 30 years ago, I was mightily impressed that the computer understood a few words. If I had seen what would be possible today, I’d have been stunned. But now? Oh, that’s just Siri or Alexa. And why didn’t auto-correct guess exactly what I wanted to say?
Streamlining operations, increasing efficiency, and driving customer loyalty are some of the benefits of predictive analytics in automated underwriting. Ohio’s talent pipeline has the wide range of skills industry leaders need to drive innovation in insurtech and fintech.
Insurance Thought Leadership (ITL) delivers engaging, informative articles from our global network of thought leaders and decision makers. Their insights are transforming the insurance and risk management marketplace through knowledge sharing, big ideas on a wide variety of topics, and lessons learned through real-life applications of innovative technology.
We also connect our network of authors and readers in ways that help them uncover opportunities and that lead to innovation and strategic advantage.
A much-cited claim about how behavioral science can guide insurance has been exposed as fraudulent. The claim was made most prominently by Dan Ariely, a best-selling author and pioneer in the field of behavioral economics, who was Lemonade's chief behavioral officer from 2015 through 2020. But the claim turns out to be based on fabricated data.
The claim was based on a study that Ariely and four co-authors published in 2012 in the Proceedings of the National Academy of Sciences. Ariely then cited the study at length in his 2013 book, The Honest Truth About Dishonesty, continuing his string of best-sellers that began with Predictably Irrational in 2008.
The study reported that people would be more honest if you asked them to promise to be truthful before providing information rather than having them provide the information and then certify that what they reported was accurate. In other words, you disrupt the usual process, in which people supply information and then just have to rationalize a bit of cheating afterward.
The study said it drew on nearly 13,500 customers of an auto insurer, half of whom signed a claim of truthfulness at the top of an application and half of whom signed at the bottom. The study reported that those who signed at the bottom said they drove about 10% fewer miles than those who signed at the top -- and, of course, paid lower premiums as a result.
The conclusion was so appealing that the paper was cited more than 400 times in academic publications. Many organizations, including the IRS, began having at least some people attest to their honesty at the start of the process. I certainly fell for the idea. I couldn't even tell you how many times I've cited the study.
More importantly, from the standpoint of insurance, Lemonade incorporated behavioral economics ideas into its initial business model that at least rhymed with the study's conclusion, even if they didn't specifically build on it. Lemonade took a set share of premium, to demonstrate to customers that it had no incentive to deny claims. Lemonade also said it would donate to specified causes if claims were below a set level -- encouraging clients to minimize claims.
Other insurers surely built on the study, especially given Lemonade's success (even though its use of behavioral economics seems to have mattered far less than its sleek customer experience and slick marketing).
As part of the retractions, the authors published the original data -- which is how it became apparent that the study was based on more than an honest mistake; the data had been manufactured.
Sleuths at Data Colada spotted what, in retrospect, were obvious problems. The data didn't follow a Bell curve, as you'd expect. There weren't some people who drove a little, some who drove a lot and a whole bunch who fell in the middle. Every division based on mileage had almost exactly the same number of people in it, from low mileage through high mileage, and not a single person out of nearly 13,500 drove more than 50,000 miles in a year. In addition, the mileage that people supposedly reported was accurate down to the mile, even though actual people would round off the numbers. The precision was a clear indication that a random number generator was being used.
There was more, too. In any case, when confronted with the Data Colada analysis, all the authors quickly agreed that the data had to have been faked.
At the moment, the focus seems to be on figuring out who to blame for the fraud. I confess to some personal confusion. I spent time with Ariely at a small, three-day conference where we both spoke in 2008 and found him to be extremely smart and thoroughly engaging, so I'd like to think that he wasn't involved. (He has vigorously denied faking any data.) But he has said he was the only one of the five authors who dealt directly with the insurer that provided the data, and it's not at all clear to me what the insurer would gain by faking the results. (While the company wasn't initially named, it's since been identified as The Hartford.) I'm also confused because he cited the study to me, personally, at that gathering in 2008 but didn't publish the results for four years. Why wait so long with such an interesting result? (He's on the record as having cited the study in a talk at Google in 2008, so he wasn't just talking to me, either.)
But I'm more concerned with the broader point, which I think is this:
Behavioral economics is still a powerful tool for insurers despite this embarrassing fraud. We may like to think of customers as completely rational, but they aren't, and we need to understand them as they are, not as we'd like them to be. That doesn't mean accepting broad pronouncements about behavior, even from charismatic experts like Ariely. Understanding behavior means engaging with our own customers deeply, testing how they react to various actions on our part and then tailoring our interactions with them, foibles and all, to maximize benefits both for them and for us.
I realize that this is two weeks in a row where I've take a contrary view about technologies and techniques that are huge benefits to the insurance industry -- last week's was When AI Doesn't Work. I'm sure these two Six Things commentaries aren't the start of a trend. But I don't believe that trees grow to the sky, so I don't see the point in pretending they might. When there's a problem, I'll always try to point it out.
Cheers,
Paul
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Carroll spent 17 years at the Wall Street Journal as an editor and reporter; he was nominated twice for the Pulitzer Prize. He later was a finalist for a National Magazine Award.
This article was written by Chunka Mui for the International Insurance Society, a sister organization of Insurance Thought Leadership, under the umbrella of The Institutes. To see more IIS articles by Chunka and other IIS experts, visit www.internationalinsurance.org.
“There are decades where nothing happens, and there are weeks where decades happen,” Vladimir Lenin observed. The arduous weeks spent grappling with the COVID-19 pandemic certainly fall into the weeks-where-decades-happen category.
Take telehealth; its adoption has seemingly been on the horizon for decades and suddenly, within weeks after COVID-19 became a pandemic, telehealth achieved near universal embrace. McKinsey estimated that healthcare providers saw 50 to 175 times more patients via telehealth in the months after the pandemic than ever before. Additionally, 57% of providers viewed telehealth more favorably than before the pandemic, and 64% of providers reported that they felt more comfortable using telehealth. Now, even as the pandemic recedes, another McKinsey survey found that 40% of consumers believe they will continue to use telehealth at similar or greater levels even after the pandemic ends. These punctuated changes in preference, perception and practice will force the rewiring of the entire healthcare delivery system.
Similarly, insurance has steadily, but unevenly, digitized for decades. Suddenly (and admirably), within weeks after COVID-19, the digital nature of most insurers’ work, collaboration, transactions and customer service greatly accelerated. A recent PwC survey found that customers are not suffering laggards lightly. Of customers who expressed difficulties in dealing with their carriers, 41% said they are likely to switch providers due to inadequate digital capabilities.
A key aspect of successful innovation in the context of such rapid change is to first deeply understand the technological drivers behind that change. I briefly introduced these drivers as the Laws of Zero in my first article of this series, titled "How Insurers Can Change the World." In this article, I explore these laws to highlight the changing future context in which insurers must operate. (I go into even more detail in a book I've written with ITL Editor-in-Chief Paul Carroll and a longtime colleague of ours, Tim Andrews, a vice president at Booz Allen Hamilton, that will be released Sept. 21.)
The basic ideas behind the Laws of Zero are that seven key drivers of change—computing, communications, information, genomics, energy, water and transportation—are improving exponentially in capability while headed toward a nearly zero relative cost. This yields two critical implications. First, as shown in the figure below, there exists a rapidly expanding gap between state-of-the-art technology potential and incremental change. Secondly, the rapidly decreasing costs of those state-of-the-art capabilities will drive marketplace adoption; the notion of zero(ish) cost grabs the attention of loads of people and means we use as much of these capabilities as we need to address any problem.
Figure 1: The Rapidly Expanding Technology Gap
Successful innovation requires anticipating future scenarios, both upside and downside, enabled by the Laws of Zero, and then smartly pulling backwards to the present to chart possible paths for working toward the opportunities while managing downside risks. The best way to predict the future is to invent it, as personal computer pioneer Alan Kay says.
Now, let’s explore the drivers and lay the foundation for understanding the upside and downside scenarios that should drive your innovation agenda.
1.Computing
The smartphone in your pocket has over 120 million times more processing power than the computer systems that guided Apollo 11 to the moon and back—at a percentage of their cost that effectively rounds to zero. While computing power obviously isn’t free (as anyone buying a smartphone knows), that power looks almost free from any historical distance.
Now, consider how computing capabilities will change over the next several decades. If Moore’s Law remains an accurate guide, computing power will double 20 times in the next 30 years while cost would be cut in half 20 times. In other words, we can look forward to analytical power more than one million times faster than the present with a per-unit cost of today’s divided by one million. What’s more, trillions of devices will be connected in a network, making the so-called Internet of Things millions of times more important than it already is.
Building on ever-smaller connected devices, over the next several years AI-driven voice input assistants such as Alexa, Google Home and Siri will not only take commands but will act as sensors that can detect illness, provide home security, etc. Robots will extend our presence: Just slap on some virtual reality goggles and (with permission) “inhabit” a robot in your kid’s, parent’s or friend’s room. Computing could be implanted in our bodies. A chip right below the jaw and near the ear could capture our voices while vibrating in ways that our ears would easily pick up as sound. There is even talk of chip implants that would plug directly into our brains and give us instant access to essentially all the world’s information. People may turn into a form of centaur, except that, instead of being half-human and half-horse, we would be part people, part electronics.
People, homes, cars and all other things being insured and served will never be the same, and the insurers that serve these assets must adapt.
2. Communications
Communications will reach into every corner of the globe, as tens-of-billions of devices and trillions of sensors are incorporated into a tapestry of communication. In other words, we aren’t just talking about humans connecting with each other. We’re also talking about humans talking to devices as well as devices talking to each other. This communication could happen anywhere because, with a little solar power and a tiny antenna, every device could be connected.
Communication will become richer too, as having bandwidth to burn means that video can be part of every connection. Think of how easily the world moved from voice calls to Zoom calls during the pandemic. Now imagine having thousands of times as much bandwidth available. If you draw the graph of cost vs. performance from today’s perspective, that cost will be so low that universal-ultra-high bandwidth connectivity will be the normal expectation rather than an exception.
Imagine what that will mean for every aspect of the insurance value chain, including underwriting, distribution, claims and service.
3. Information
The ability to embed computing and communications into every aspect of life will exponentially expand the amount of information available. Paired with rapidly improving data analytics, machine learning and other artificial intelligence capabilities, information will enable more powerful knowledge-driven enterprises.
Think about a situation we’re all familiar with, the daily commute. Every car and street will soon be so thoroughly wired that traffic will be managed in ways that aren’t conceivable today. For example, just because you can’t see what might be coming at you from the sides at an intersection, doesn’t mean another car can’t see for you and relay that information to your car; a camera mounted on a car, for instance, could spot a vehicle zooming through a red light and automatically alert all cars in the vicinity to halt and wait for the danger to clear the intersection. The presence of ice or any other danger will be immediately communicated to all cars in the area. Traffic will be managed as a single, highly efficient digital system, rather than through a few rules that require hundreds of millions of drivers to sort things out on their own.
Ubiquitous sensors will supply information from everywhere else, too - - including our bodies. Already, sensors built into contact lenses can measure blood sugar levels. A cuff about the size of a smartwatch can report on blood pressure in real time. Tiny cameras can now be sealed into a capsule the size of a cod liver oil tablet that someone can swallow; these cameras screen for cancer as they pass through the person’s bowel, meaning the person can avoid the dreaded colonoscopy. In addition, chips the size of a grain of salt are being developed that could be swallowed and provide real-time data on our vital signs from inside our bloodstreams - - sort of an Internet of Me to go along with the Internet of Things.
Yes, this sort of transparency could be a scary prospect, and the concept of Big Brother is a real possibility. Breaches in cyber security will be an ever-present threat. How do insurers shape their futures in a world where every bit of information is available? How do these insurers offer trustworthy products and service while navigating potential problems?
4.Genomics
If DNA is “the language in which God created life,” as President Bill Clinton once put it, then genomics’ acceleration has brought us to the point where we can read and write in the language of life. It cost billions of research dollars to sequence the first human genome in 2003. Today, sequencing a genome costs roughly $600. That’s a cost improvement of more than one million times. That’s almost seven orders of magnitude in just 18 years, and the gains are hardly finished. There are already attachments that let you sequence a genome from an app on your own smartphone. Likewise, rapid improvements are being made in the field of gene editing, building on revolutionary techniques such as CRISPR/Cas9 (called CRISPR for short) and mRNA.
In medicine, as genomics pioneer Craig Venter has observed, almost every new drug and vaccine is already based on genomics, and, even at our early stage of knowledge, genomics provides hope for addressing several diseases caused by variation in a single gene. These diseases, known as monogenic disorders, include sickle cell anemia, cystic fibrosis, Huntington’s disease and Duchenne muscular dystrophy – debilitating diseases that afflict some 400,000 people in the U.S. CRISPR is helping researchers better understand these diseases, and a number of therapies are in clinical trials for treating and even curing them.
The combination of massive power and plunging costs guarantees that we will soon be able to sequence any genome, anytime, anywhere, with profound implications not just for medicine but far beyond. Genomics is a foundational tool in almost every field of science related to biology, including agriculture, environmental studies, health and zoology. Genomics will exponentially amplify science and engineering’s impact over the next half century to a degree that will likely surpass the impact of the computing platform it is built upon.
We still have much to learn to become truly fluent in the language of life. But it is not hard to envision harnessing the power of genomics to create healthier foods; to eliminate microbes that cause disease; to eradicate the most dangerous pests; to identify and possibly correct the genetic markers that cause disease; and to do all of the former in an ethical and equitable manner with a deep understanding of the implications of our choices.
The opportunities and challenges for life and health insurance will be profound.
5. Energy
When Bell Labs developed the first solar photovoltaic panel in 1954, the cost was $1,000 per watt produced. That meant it cost $75,000 to power a single reading lamp, which is a little pricey. By 2017, solar was down to $0.25 a watt. A solar project that will supply 7% of the electricity to Los Angeles promises power at less than $0.02 per kilowatt hour (kwh), while the national average for electricity charges to consumers in the U.S. is nearly seven times that. The International Energy Agency’s annual report for 2020 says solar power is already “the cheapest electricity in history.” A drop in price by a factor of 3,000 over six decades isn’t Moore’s law, but it’s certainly headed toward that magic number: zero.
Wind power is also on an aggressive move toward zero as prices are down nearly 50% in the past year. Contracts were recently signed for wind power in Brazil at a cost of 1.75 cents per kilowatt hour, about one-fourth the average of 6.8 cents per kwh worldwide for coal, considered to be the cheapest of the conventional energy sources.
The key holdup for renewable energy has been batteries. There must be some way to store the solar and wind energy for when you need it, which means the need for lots of battery capacity. Fortunately, batteries are progressing on three key fronts: battery life, power and cost. CATL, the world’s top battery producer, recently announced a car battery that can operate for 1.2 million miles, eight times longer than most car batteries on the market today. Additionally, battery prices have plunged 87% in the past 10 years.
So, we have at least three cost curves that look like they’re headed toward zero: solar, wind, and batteries. That’s plenty, but others are worth mentioning as well, including nuclear fission, nuclear fusion, geothermal and radical energy efficiency. Together, these curves create a Law of Zero for clean energy that will create unfathomable benefits.
Energy drives every living thing, and unlimited clean energy will drive unlimited opportunities.
6. Water
A quarter of humanity faces looming water crises, and demand is growing along with population, urbanization and wealth and the taxing of traditional fresh water supplies while also polluting them. But there’s hope – limitless energy could allow for the almost magical availability of water.
By 2050, anyone near a body of saltwater could benefit from water technology breakthroughs. Desalination has always been possible, but prohibitively expensive because of energy costs, whether done by filtering out the salt through osmosis or by evaporating the water and leaving the salt behind. Cheap energy makes desalination more plausible, as many cities around the world are getting desperate for water.
Water won’t be pulled out of thin air in great quantities anytime soon, but that technology is also under development. One group won a $1.5 million X Prize by developing a generator that can be used in any climate to extract at least 2,000 liters of water a day from the air at a cost of less than $0.02 per liter, using entirely renewable energy. One can imagine a day when decentralized production of water will lead to benefits akin to those that come from having abundant electricity while off the grid.
Where there is abundant water, along with the energy that comes from the Law of Zero, there can be food. The basics of life will be available everywhere, even at the far corners of the Earth.
7. Transportation
Although the enthusiasm for autonomous vehicles (AVs) took a hit for a couple of years – they are a really hard problem – momentum is building again, and the multitude of startups and brilliant scientists tackling the issues portends a future that will include an unlimited number of AVs.
The implications are mind-boggling. AVs are aimed at dramatically improving two key drawbacks of human-driven cars. First, humans are bad drivers. More than 90% of vehicular accidents are due to human error, which result in tens of thousands of deaths, millions of injuries and hundreds of billions in cost each year—just in the U.S. Worldwide, the figures are even more staggering. Bad driving also leads to traffic congestion, costing hundreds of billions of dollars due to added hours in traffic, wasted gasoline and lost productivity. Secondly, human-driven cars are very underused. Most of these cars are personally owned and sit parked more than 95% of the time. Some estimate that AVs, once successfully deployed as fleets of shared Uber-like, on-demand vehicles, could reduce accidents, lower congestion and reduce the number of cars by 90%.
Now, a lot of metal will need to be shaped and maintained even in an autonomous future, so transportation won’t be free. But that transportation will be so much less expensive than it is today that we can be profligate in throwing transportation resources at anything we want to. Think in terms of a world where fuel is free and, thus, infinite, where many considerations of time and distance no longer matter. Think about how health, wealth, education, economic mobility and more could all improve because access to transportation currently constrains so many people.
Yes, lots of people and businesses will have to adapt. Among the notable are the 4.5 million professional drivers in the U.S. AVs will also change emergency rooms, which currently treat some 2.5 million people each year after auto accidents and, based on current estimates, might treat only 10% as many individuals once AVs become ubiquitous. Car dealers, gas stations, oil companies, auto repair shops and most others in the multitrillion-dollar transportation value chain might well be disrupted.
There’s also the existential question for auto insurers: Why do you need personal auto insurance when there are almost no accidents, and you aren’t driving anyway? Will personal car insurance essentially go away?
* * *
Not all the Laws of Zero will kick in right away. The ubiquity of water, in particular, will take time to play out, partly because getting to zero cost for energy will also take time. Other laws, such as for information and genomics, are driving disruption faster than most imagine.
Here’s the core question all insurers should explore: How will these Laws of Zero shape the future? As customers, supply chain partners, competitors and others in the world at large accelerate their own digitization, driven by the Laws of Zero, how will insurers innovatively adapt their own business and operating models to stay responsive and competitive? Insurers should assume that decades will continue to happen in the weeks and months ahead.
These are times that demand both giant leaps and baby steps. In coming articles and webinars, we will continue to explore how insurers can systematically do both. In the meantime, we welcome your comments and questions.Read more at internationalinsurance.org.
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IIS serves as the inclusive voice of the industry, providing a platform for both private and public stakeholders to promote resilience, drive innovation, and stimulate the development of markets. The IIS membership is diverse and inclusive, with members hailing from mature and emerging markets representing all sectors of the re/insurance industry, academics, regulators and policymakers. As a non-advocative organization, the IIS serves as a neutral platform for active collaboration and examination of issues that shape the future of the global insurance industry. Its signature annual event, the Global Insurance Forum, is considered the premier industry conference and is attended by 500+ insurance leaders from around the globe.
Finding peace of mind and mental clarity isn’t always easy, but it can often be the first step toward personal and professional success. On the flip side, when stress seems consuming, it can affect a person’s ability to focus, thereby taking a toll on workplace performance.
The American Heart Association CEO Roundtable Report surveyed thousands of employees (pre-COVID) and found 76% reported they struggled with at least one issue affecting their mental health.
The past year of COVID-related social distancing, isolation and worry have resulted in increased rates of stress, anxiety and depression. Even post-pandemic, addressing these challenges head-on and with a research-focused strategy is critical.
As companies across all sectors balance the return of their workforce in person or in a hybrid format and address the mental wellbeing of their employees, several critical trends emerge as necessary steps for employers to ensure the maximum wellbeing of their team. These include:
Understanding the connection between mental and physical health:
According to data from Springbuk Analytics, 69% of patients with a mental health condition also have a chronic condition.
When patients have a mental health condition and at least one chronic condition, insurance costs to employers rise by 126%.
Understanding how mental health affects workplace productivity:
The World Health Organization (WHO) indicates that, by 2030, depression will be the leading cause of lost productivity in all economically advanced countries.
Of course, with a diverse range of possible methods, solidifying best practices can seem overwhelming even for the most experienced management professionals. The “Building a Caring Culture: Addressing Mental Health in the Workplace” white paper, prepared in conjunction with CSDZ, Holmes Murphy and MindWise Innovations, provides key insights and best practices on addressing mental health in the workplace.
Building a workplace where mental health can easily be addressed is no small task. Mental health needs to be addressed across all sectors, such as health, wellness, safety and employee benefits.
Training leaders and supervisors to provide care and support to their employees, accepting employees for who they are, fostering a safe and empathetic workplace and understanding that each worker has other stresses, pressures and distractions from their personal lives all contribute to making mental health a priority in the workplace.
By talking about mental health and wellbeing in the workplace, we can work together to break down the stigma and help others with existing conditions.
Get Involved
Our authors are what set Insurance Thought Leadership apart.
Cal Beyer is the vice president of Workforce Risk and Worker Wellbeing. He has over 30 years of safety, insurance and risk management experience, including 24 of those years serving the construction industry in various capacities.
