The journey began with a possible purchase on eBay.

Robin Roberson thought to herself, "Wouldn't it be great if I could have someone go look at the item to make sure the seller is being straight with me?" Robin realized that others might want someone to go look, too, so she founded a company called WeGoLook in 2009 and recruited free-lance "lookers" around the country. She found her way into the insurance market soon enough—why would an insurer have an adjuster drive an hour to take photos of a car accident in a rural area if a "looker" was nearby?—and built her free-lance force up to more than 30,000. Crawford & Co. came calling and bought an 85% stake at the end of 2016 at a price that valued the whole firm at $42.5 million, making Robin one of the early stars of the insurtech movement.

For her next act, Robin has set her sights on, among other things, cybersecurity, and is championing a novel approach that she and a colleague will describe in detail at the Future of Risk, April 1-3, in Chicago. (You can register here. I'm going....) I've known Robin for years because some of my former partners at ITL helped steer her toward insurance and even initiated the connection with Crawford, so I caught up with her ahead of her talk to get a sense of where she thinks cybersecurity and cyber insurance need to head.

The issue boils down to "tokenization," which she and her colleague Alex Pezold, co-founder of TokenEx, have written about a bit for us here. Basically, tokenization replaces the data in a company's systems with tokens that, given the proper authorization, can be used to summon the actual data.

That may sound rather like encryption but goes beyond it in two ways. First, the tokens bear no mathematical connection to the data they summon, so a hacker can't simply figure out an encryption key and have access to all your data. Second, with tokenization, the data is taken off-site to a "vault" in the cloud. Hackers would have to break into it, too, and such a vault can be secured in ways that companies find nearly impossible to manage, given all the online connections they have—remember that the huge breach at Target happened because hackers snuck in via its HVAC systems. If hackers do make their way into your systems and grab your data in a tokenized system, all they get are a bunch of tokens that mean nothing to them or anyone else.

"A lot of cyber premium is being left on the table," says Robin, who has co-founded a boutique consulting firm, Goose & Gander, that works with startups such as TokenEx. "Carriers are concerned that the risks are too great. But if insurers price policies in tiers that encourage tokenization, they can be confident that they aren't taking on too much risk."

She adds that tokenization just requires an API (application programming interface) layer. "People don't understand how easy it is to implement this layer that sits between their systems and their data," she says.

Robin thinks small to medium-sized businesses could be big beneficiaries because they don't otherwise have the resources that big companies do when it comes to protecting their data.

Tokenization is already in widespread use with payments. "That's the cool thing," Robin says. "This is a solution that comes out of the finance industry." If you insert your credit card to buy gas, she says, the pump doesn't collect your card information. The card connects with the payment system, which simply sends a token to the pump saying you're authorized to pump gas.

The issue has been getting insurers, and their clients, to stretch the use of tokenization beyond payments and into protection of data.

"We're already seeing some traction," she says.

Robin says additional data protection will position insurers and their clients to deal more easily with the growing number of privacy laws, including the California Consumer Privacy Act (CCPA), which she's also covered for us here.

"It would behoove the industry to get ahead of the game and to start planning for all of the changes now," she said. "When you do, you can be compliant whether you're in California, or Oklahoma or any state."

She and Alex will tell us more at the Future of Risk on April 2. I hope to see you there.

Cheers,

Paul Carroll
Editor-in-Chief

The year is 1959. Neuroscientist and psychologist Bela Julesz tests the ability of the brain to perceive images in 3D. With circular dots and a double image, subjects could begin to see a circle floating above a printed background. Fast forward 20 years, and two of Julesz’s students use a computer to accomplish the same feat in just a single image. By 1991, Magic Eye pictures used repeat patterns to control the depth of perception. A complete 3D image could be hidden inside a 2D pattern. The only way someone could see the image was to relax the eye, blur the pattern and let the brain do the rest. What looked out of focus, blurry and flat, was transformed into an image of stark clarity that leapt off the paper.

Is this a magic formula for considering today’s insurance? A jumble of patterns exist. Focus is difficult to maintain. Thousands of details and past assumptions threaten to distort what insurance executives need to decipher. But…if we relax just a bit and allow the blurriness to exist for a few moments, a certain clarity arises. Not only does the picture become clear, it jumps off the page in 3D. As market boundaries blur and evaporate, new answers to insurance technology, processes and business models are coming to life.

Which boundaries are reshaping the industry?

Four years ago, Majesco published its first Future Trends report that examined the converging “tectonic plates” of people, technology and market boundary changes that are redefining the world, industries and businesses — including insurance. Recently, we released the latest report, Future Trends: Looking Back and Leaping Forward, where we once again discussed shifting market boundaries under six trending categories:

• Insurtech
• Channels
• Blurring Boundaries (between industries)
• New Competition
• New Products
• Competition for Talent

From the start, we recognized that insurers were going to begin competing in a new paradigm beyond their brand, product, price and distribution. This new paradigm required insurers to compete also on the customer experience and to move from vertical market boundaries to porous market boundaries, or ecosystems.

Ecosystems are fluid, porous and operate across and within verticals and multiple channels. The first platform companies like Amazon, Google, Apple, Netflix and Uber disrupted multiple industry verticals and demonstrated why market boundaries limit revenue generation, customer value and market valuations. By bursting the boundaries, they lost predictability, but they gained market reach.

The boundary lesson for insurers is that the industry isn’t simply being reshaped, it is being “unshaped.” 

It’s no wonder, then, that many insurers are finding themselves and their strategies adrift — no longer safely anchored to traditional assumptions. Insurers now have to wrap their heads around a new image that will allow them to escape 2D frameworks and find answers in new dimensions.

See also: Insurtech 2020: Trends That Offer Growth  

Can we find clarity among the blurriness of market boundaries? 

With traditional market and product assumptions (and constraints) evaporating before our eyes, clarity has to be found in a whole new definition of insurance products and services. From ecosystems to technologies, some picture has to emerge that will allow our brains to think “outside the page."

In words, this image might be, “Escape linear thinking. Embrace the idea of plug and play, partners, networks and ecosystems.”

What is affecting our boundaries and how can we use an ecosystem approach to take advantage of these boundary shifts? We can find out by considering four of the boundary-breaking areas — Insurtech, Channels, Blurring Boundaries and New Products.

Insurtech

If you have been keeping an eye on insurtech, then you’ll know how volatile and substantial investment has been. Based on Venture Scanner data, insurtech investment in 2015 was $1.78 billion as compared with $3.37 billion in 2018 (89% growth) and just over $5 billion through Q3 2019.

Even more interesting are the top funding areas. From the recent Venture Scanner report, Q3 2019 showed the largest influx of funding was in the Insurance Infrastructure/Backend category, with $1.12 billion.

This is a major flip given that channels/front-end were originally the top priority. This flip in focus recognizes the criticality of next-gen technology platforms for insurers that provide flexibility, agility, speed and scale. What does this mean for insurers that are looking for clarity?

First, insurers can take advantage of insurtech investments without making direct investments in insurtech. This is the one of the major takeaways. Insurtech capabilities are now ready as plug-and-play, ecosystem-based, cloud-available services such as Majesco’s Digital1st Insurance,

Channels

Today’s customers have introduced new time requirements and pressures into the insurance equation because they are looking for solutions that meet their needs on their terms (when and how they need it), and with speed. There is the time to quote, time to underwrite and time to purchase, which are all opportunities to lose or to gain the sale.

In this new era of insurance, nearly every insurance process is rapidly becoming frictionless, including buying. If distribution channels are easy to use with products that are easy to understand, then insurance has the opportunity to grow through a friction-free, multi-channel distribution system.

The industry is now exploding with new concepts in distribution, including new distribution channel options from marketplaces like Bold Penguin and digital MGAs like Slice Labs. We have also seen the shift from portals to digital experience platforms like Majesco Digital1st Insurance, which has allowed companies like Burns & Wilcox, a major wholesaler, to bring innovative specialty insurance solutions to brokers and agents. Ecosystems can rewrite channel strategy and open the windows to allow for unprecedented levels of channel partnership.

Blurring Boundaries (between industries)

Embedded insurance is an example of boundaries becoming invisible. There is a “hidden channel,” connecting insurance with another ecosystem, such as rental properties, auto manufacturers or even baby gift registries – and embedding the opportunity to purchase within the existing process.

To capture the opportunity, insurers must create an ecosystem of partnerships with a range of digital capabilities and channels to reach new and existing customers. How do insurers recognize the opportunities that exist within the flow of the current of buyer needs, events and lifestyles, to fit the product to the flow of life instead of trying to sell “upstream”?

Majesco Consumer and SMB research has found that customers are very interested in innovative channels like embedding insurance. The answer boils down to alignment. Clear strategies will align the right channels, technologies and partnerships, considering the synergies of partner organizations and the expectations of today’s and tomorrow’s customers. In many cases, insurers will need to quickly build relationships and cross industry verticals. In most cases, strategic clarity will be found through rapid test-and-learn cycles.

New Products

Over the last four years, we have seen a growing proliferation of new products and value-added services. These products use new data sources, offer new customer experiences, leverage new technologies and, most importantly, are focused on meeting a new set of risk needs and expectations, particularly for millennials and Gen Z.

The most important change, driven by startups and greenfields, is the unbundling of “one-size-fits-all” insurance into products based on specific needs at specific times. Unbundling, coupled with the growth in the sharing and gig economy has powered the development of micro-insurance or on-demand products across all insurance segments and lines of business.

See also: Future of Insurance Is Clear (but Hard)  

Initially, unbundling was best accomplished by a range of small and agile insurance or MGA startups. As traditional insurers and reinsurers have begun to re-envision their responses to blurring industry and market boundaries, they have begun forming clear approaches to on-demand product development. Fast forward to today, and we are now seeing the emergence of on-demand voluntary benefits, life insurance, rideshare, cyber and so much more.

These four boundary-breaking trends are proving that insurers of all sizes can now find an alternate picture within a blurring universe — clear answers rising above the background of tradition and disruption.

Insurance fraud scams seem to make the news at least every month, as organized criminals seek to exploit the way insurers reimburse clinics, pharmacies and other providers for their services. What’s often shocking is how much money fraudsters can steal from insurers before they’re caught. Recently, in a single month, two separate alleged fraud rings based in California were busted for scams that investigators say netted $20 million or more. 

Clearly, there’s a need for fraud detection tools that can spot these frauds in their early stages. Based on my experience working for a company that uses machine learning and artificial intelligence to detect e-commerce fraud, I think these tools can also help stop organized insurance fraud. One technique called group analysis seems like an especially promising approach for catching fraud rings sooner rather than later. 

In this article, we’ll focus on organized health insurance fraud because it’s common, costly and hard to detect quickly using traditional screening methods. But the group analysis approach could apply to other kinds of organized insurance fraud, as well. 

The health insurance fraud landscape

It’s hard to find solid, consistent numbers on the cost of health insurance fraud, in part because it’s hard to detect at scale. The National Health Care Anti-Fraud Association (NHCAA) estimates that somewhere between 3% and 10% of U.S. healthcare dollars are spent on fraud every year, which translates into as much as $300 billion annually. 

While law enforcement does go after insurance fraud scams, the amount recovered doesn’t come close to the projected scale of losses. For example, in 2018, the U.S. Department of Justice recovered $2.5 billion in costs related to fraud and improper claims. That’s a lot of money, but it’s not $300 billion.

See also: Future of Insurance Is… Not Insurance  

How do fraudsters get away with stealing so much money from insurers and government programs? It’s mostly because they’re professionals, and they operate on a large scale. The NHCAA says most insurance fraud is committed by organized groups, which operate a variety of scams, including:

• Filing claims for procedures and services that never happened, using stolen patient data.
• Padding legitimate claims with procedures that never happened.
• Accepting kickbacks for patient referrals for unnecessary treatments.
• Setting up fake clinics to bilk patients’ insurers out of reimbursements for marked-up procedures and prescriptions. 

How AI and group analysis could help spot organized healthcare fraud

When insurers review claims individually for signs of fraud, they’re taking an approach like the one that e-commerce merchants have used for years: looking for fraud on a case-by-case basis. This is necessary, of course, because individuals do sometimes try to exploit the system. But individual claim review will miss the bigger picture.

That’s because sometimes patterns that indicate possible fraud are only visible when you look at the larger data set. That’s true no matter what type of fraud you’re trying to stop. For example, in e-commerce, a series of orders that look legitimate and raise no fraud flags can be part of a broader fraud scheme. 

How is that possible? 

Here’s an e-commerce example: Let’s say a merchant receives a dozen orders from different customers within an hour, all with valid payment and customer identity information. Each order passes fraud screening and gets approved. 

But the merchant’s fraud protection program also conducts group analysis—looking at all the traits of each order and analyzing the entire group to spot unusual patterns. After the 12^th order, the group analysis flags the entire batch of orders for further review, because every credit card used had the same bank identification number. When analysts look at the group analysis data and individual orders, it’s apparent that criminals compromised a batch of different cards issued by a single bank and used them to go shopping online. The orders are canceled, and the merchant avoids losses.

Insurance fraud investigators already look for big-picture patterns, of course. Federal, state and local law enforcement agencies deploy hundreds of people who spend thousands of hours checking out possible fraud rings based on intelligence and patterns of behavior, then collecting evidence to make arrests. But group analysis has the potential to help investigators identify suspicious patterns faster, to limit fraud losses. 

For example, a fraud ring in California is currently facing charges for an elaborate, two-year scheme that investigators say stole $19 million from TRICARE and $3 million from another insurer. According to the indictment, the ruse included two fake pain clinics set up by the fraudsters, kickbacks to a doctor for referring TRICARE and ILWU policyholders to the fake clinics and fraudulent prescriptions and refill requests for pain creams billed to those insurers at up to $15,000 per tube. 

The part of the story that stands out is that the ring’s operations were at their peak five years ago, but the alleged fraudsters are only now facing charges. It seems unlikely the insurers would be able to recover the stolen funds after so much time. 

See also: Empowering Health Through Blockchain  

How could group analysis make a difference in a complex case like this? It’s clear that each claim on its own passed the insurers’ fraud review. And it’s also clear that someone eventually spotted a pattern or received information about possible organized fraud. 

However, a machine learning system continuously analyzing claims for large-scale patterns might flag many claims based on referrals of patients with the same insurance by one doctor to two specific (and recently opened) clinics. Or the system might detect an unusually large number of prescriptions for very expensive creams coming from the pharmacy. As more data comes in, AI-driven systems get smarter about which patterns might be fraud and which might not. And, depending on the pace and timing of the claims, group analysis could spot fraudulent patterns in days, weeks or months, rather than years. 

Group analysis and AI could change the health fraud landscape

Giving health insurers and fraud investigators AI tools can do more than save money. These analytics tools could also reduce the number of patients who are subject to bogus treatments because fraudsters want to exploit their insurance coverage. And faster intervention could also discourage some fraudsters from making the effort. After all, why build fake clinics and find corrupt practitioners if the whole operation could be shut down before it’s profitable? 

Fighting fraud is a task that may never end. But by making it harder for criminals to succeed, AI-based group analysis could give investigators a powerful way to fight back faster against organized insurance fraud.

Data is the foundation of insurance, and two emerging technologies, the Internet of Things (IoT, and artificial intelligence (AI), are making that foundation more useful than ever.

IoT allows internet-connected devices to send and receive real-time data. Insurers are increasingly using IoT data to streamline operations, improve customer engagement, offer discounts for and encourage healthy behavior such as safe driving and regular exercise, calculate risks more accurately, boost competitive advantage and streamline compliance.

And that’s just the beginning. Connected devices will be increasingly valuable for other activities, including loss control, pricing, underwriting and marketing.

IoT produces a flood of big data that would be unmanageable without AI to organize it and extract what’s valuable. Using IoT and AI together can benefit not only insurers but brokers, employers, employees and consumers, too. Some IoT software vendors now offer built-in AI capabilities, such as machine-learning-based analytics. AI and analytics can find the needles of insight in the haystack of data and learn from them to identify patterns and trends that might otherwise be undetectable.

Technologies that monitor vehicle speed, brake function and driving habits are starting to transform auto insurance. Several insurers are offering savings to drivers whose data show that they’re safe.

About one in five Americans own a wearable fitness device. Wearables can provide extensive data, including an individual’s daily exercise level, heartbeat rate and even length and quality of sleep. 

Life and health insurers selling both individual and group policies would love to get their hands on this data and use it to motivate insureds to adopt healthy lifestyles, to offer appropriate discounts and to improve underwriting. John Hancock already plans to require new insureds to use activity trackers and share their fitness data in exchange for discounted premiums and other benefits.

In underwriting, wearables provide data that can either lessen or eliminate the need for medical tests. Some insurance software vendors have integrated wearable data analytics with cardio fitness scores for simplified underwriting.  The data also can also help guide product development.

Wearable devices that can detect heartbeat irregularities and high blood pressure can also alert insureds to the need for early treatment, potentially reducing costs for insurers. But there are downsides. The insurer has access to the most private type of information whenever it is connected to a customer wearing a device. (What could be more personal than one’s health?) So the insurer must take pains to ensure security and be able to credibly assure customers and employers (if it’s a group policy) that personal health information will be guarded like Fort Knox.

See also: Insurance and the Internet of Things  

Insurers, of course, have always dealt with sensitive information, but the sheer volume of IoT data presents more opportunities for hackers and other criminals. AI may also have a role here, in providing early-warning detection of possible hacking or fraud. 

IoT, combined with AI, is already beginning to transform the industry. Insurers looking to get the best return on investment for their data dollars would be wise to investigate making the combination a part of their technology strategy.

Have you ever been walking down Bourbon Street late one evening, only to see some street preacher carrying a sign warning you to repent because the end is near? My guess is you have, whether in New Orleans or some other city – you’ve seen him, you’ve smiled, laughed or ignored him and you went on about your business. Did you ever take time to ponder: WHAT IF HE IS RIGHT? If you had any inclination that he might be right, you probably would have left Bourbon Street by way of St. Louis Cathedral and then prayed for some way to explain your presence in the French Quarter. Don’t panic, I’m not going to use this column to call you out for your prior sins. See also: How to Extend Reach of Auto Insurance   I am, however, going to repeat the warning: “THE END IS NEAR." The END I am discussing is for insurance as it has been. To us (as agents), it is a profession, a good job offering exceptional compensation for those willing to work and the opportunity to build a book of business that offers recurring revenue. We can easily explain the importance of what we do. We can no longer easily explain the cost. My older, retired sister called me last week to ask about her auto insurance renewal on her Chevy, with her one accident. Her renewal quote was over $4,000. A column ("State’s sky-high car insurance rates going up!" by Dan Fagain) in Sunday’s Advocate said:

• Louisiana already has the second-highest rates in the country.
• Some recent auto insurance rates are increasing 22%.
• The average rate for a Louisiana resident was close to $2,000 a year.
• In 2012 and 2013, Louisiana had the highest rates in the nation.

By comparison: A check of Quick Facts for the U.S. Census Bureau indicates the 2016 median household income in Louisiana was $45,652, and the 2016 per capita income was $25,515. In April 1993, I wrote a report for a consumer advocacy group promoting “verbal threshold” no-fault auto insurance. This compared the auto insurance costs and issues driving these costs in the states of Texas, Louisiana, Arkansas, Alabama and Mississippi. There was no significant difference in the number of claims per capita, nor the intensity of the claim. The only difference of consequence was the frequency and severity of the bodily injury losses in Louisiana. The one element of the study that explained this difference best was attorney involvement. Louisiana had one attorney for every 280 people and one law student for every 1,145 citizens. The next closest to us was Texas, with one attorney for each 320 people and one law student for each 2,332 citizens. Our system has more people to feed with each premium dollar. What if we, as professionals, ignore the pain of our clients and don’t reinvent ourselves and our industry to work first for the consumers – those who use the system and those who pay for it? Can you afford to take that risk? Have we reached or are we reaching the price point where what we sell is no longer affordable to the people who buy our products? Are you willing and able to engage seriously with other professionals to make our system work for the consumers – the premium payers – first? This is not just an issue only of auto insurance and lawyers. This is about the cost and availability of liability insurance of various types that can protect individuals and business owners from their own negligence or alleged negligence. If we don’t fix this – the government will try. The marketplace will not be denied. The insurance industry was unwilling and unable to address the flood exposure – that brought us the National Flood Insurance Program (NFIP). Our health insurance model was too expensive and too cumbersome – now we have something worse, but only until it collapses under its own weight and it becomes a single payer system. Before you laugh at us poor folks in Louisiana – understand that the unsustainability of our traditional insurance offerings will eventually move into most states. It is not the geography of our state – it is the demographics, power of the trial bar, the culture and human greed. Technology exists today to streamline what we do and to reduce greatly the cost of what we sell -- to bring affordability back into the process and purchase. If we leverage it, it may save us. See also: The Sharing Economy and Auto Insurance   Peter Drucker, one of the great thinkers of the last 100 years, explained, “Customers do not see it as their job to ensure manufacturers a profit. The only sound way to price is to start out with what the market will pay – and thus, it must be assumed, what the competition will charge – and design to that price specification.” I may be an old rambling street preacher walking around with a sign warning “the end is near.” Laugh if you will, but ask yourself, “WHAT IF I’M RIGHT?!”

If insurers want to lower their legal costs, or at least make themselves less vulnerable to costly litigation, they need to increase their emphasis on safety. 

They need to revise their policies to align with public policy. They need to make it their policy to ensure safety before they insure clients—before they issue insurance to businesses—whose places of business are dangerous or potentially deadly. 

Absent a change, policies for all clients will become more expensive. The expense may be too much for some companies to bear, the expense may be too burdensome for most small businesses to endure, unless the seemingly inevitable becomes the easily avoidable.

That is to say, insurance can be more affordable, and insurers can afford to make more money, if safety is a national priority.

Achieving this goal is a matter not only of listening to what a lawyer says, but doing what he recommends.

According to Howard P. Lesnik, an injury law expert and member of the New Jersey Association of Justice, insurers should listen to what juries have said; insurers should listen to what juries continue to say, that accident victims deserve the damages they seek.

All juries may not say the same thing, but many say what all insurers should hear—the truth.

The truth is: When a place of business is injurious to the public, when the injuries are similar and the place where they happen is the same, when a business does nothing to prevent accidents that have a high likelihood of resulting in physical injuries, then it is no accident that that business is indifferent to the interests of the public.

Insurers must not be accomplices to such indifference. Not when a policy of do-nothingism is a prescription to lose everything. Not when the price of inaction is a possible class action lawsuit. Not when the ultimate price is bankruptcy, morally and monetarily.

See also: Visions of Safety and Pictures of Success  

A policy of conscience, on the other hand, is anything but indifferent.

It is a statement of principle, saying to the nation that insurers do acknowledge, that insurers do accept their role as leaders.

Such a statement would do a lot to define the insurance industry as a symbol of leadership.

To be true to that statement, insurers must listen to what an injury law expert has to say. 

In so doing, a dialogue may ensue. and new standards of excellence may emerge.

This dialogue is too important to ignore or dismiss, given the dangers that exist and the risks that threaten the lives of individuals and the livelihoods of individual workers throughout the insurance industry. 

Silence, in other words, is deadly.

Through an exchange of ideas and an attempt to achieve certain ideals, insurers can promote better business practices, superior workplace conditions and fewer accidents. They can also champion greater oversight and safety.

Let insurers strive to do these things, despite whatever challenges, criticisms or costs may arise.

Let insurers do what is right, despite whatever may happen, period.

Insurance, being one of the most conservative, centralized and walled industries, is awakening from its slumber and probing new technologies. Its shy yet solid interest in innovations, particularly in blockchain, is powered by customers’ increased distrust in centralized financial services, which has led to high rates of underinsurance. 

Driven by both curiosity and fear, insurance companies seek to hire blockchain developers to help them out. Curiosity comes from blockchain promising to save time and lower transactional costs. At the same time, insurers fear this innovation as it can open up new approaches for cyber-attacks. 

Let’s explore how insurance companies can adopt blockchain technologies safely and cease to lag behind other financial service sectors.  

What is blockchain in insurance?

First things first, let’s define what blockchain is in the context of insurance.

The blockchain technology is based on the distributed ledger principle that eliminates the need for intermediaries. Copies of the shared ledger are stored across multiple users’ locations, providing any endorsed insurance company, agent, broker or underwriter with access to the same source of data updated in real time. All the transactions registered on a blockchain are verified and encrypted, while all the changes to the records are published as additions to the original data. 

The practical application can look like this: With the help of blockchain, medical records can be encrypted and shared between hospitals and insurers (even across borders), thus cutting duplicated and erroneous records, lengthy claim processing, claim denials and excessive checkups.    

How blockchain is implemented in insurance

According to the Accenture Technology Vision 2019 survey, more than 80% of insurance companies claimed they adopted or were planning to adopt the blockchain technology. It’s true: Many blockchain insurance projects are lingering at the proof of concept stage. However, to accelerate adoption, some companies choose to collaborate and form alliances, such as the Blockchain Insurance Industry Initiative (B3i) or the Institutes' RiskStream Collaborative. 

See also: Blockchain: Seizing the Opportunities 

These trailblazing alliances develop blockchain-based platforms to make the following blockchain use cases possible. 

Fraud and abuse prevention

Fraud costs the insurance industry monstrous amounts of money, mostly because it’s impossible to detect fraudulent activities with regular methods based on the use of publicly available data and private data sources. As a result, the accumulated data is usually fragmented due to legal constraints accompanying personally identifiable information. 

Unfortunately, these gaps in visibility are being compromised by fraudsters. For example, multiple claims can be filed for a single case of care.

When data is stored on a blockchain-based ledger, it’s secured with cryptographic signatures and granular permission settings. It means that all the parties can share data and verify its authenticity without revealing sensitive information. A shared decentralized ledger facilitates historic data consolidation and helps companies spot suspicious patterns, such as:

• Multiple processing of the same claim    
• An insurance policy’s ownership manipulation
• Insurance sold by unlicensed brokers

To attain even higher security, insurance companies can provide customers with encrypted digital ID cards that can’t be faked. 

Boosted transparency and trust

Insurance companies are called walled gardens for a reason. Customers have little chance to see how their data is managed. For example, they will never know that their data is shared with third parties. It’s no wonder that customers grow distrustful of insurance companies, particularly when facing long claim processing times or receiving claim denials—while the cost of premiums is ever-increasing. 

However, when multiple insurance companies choose to contribute data to the same decentralized and shared ledger, it can lead to three big advantages:

1. Insurance companies can build more complete customer profiles and eliminate duplicate records. As the data in the blockchain ledger is immutable, the insurance companies won’t doubt its authenticity.  
2. Customers will get visibility into what data their insurers have on them, and how this data is processed. Plus, when blockchain is combined with machine learning and AI, claim processing can be automated, thus accelerating payouts. 
3. Blockchain helps automatically verify third-party claims or payments made through personal devices. Further on, the insurance company will be able to see all those transactions reflected on the blockchain.

Streamlined claim management

Selling and managing insurance policies is a labor-intensive process. In the context of high competition, insurance companies that stick to slow and paperwork-heavy traditional approaches lose to more digitally savvy competitors. The latter are able to offer lower premiums by automating claim management. 

Some of the processes can be automated by means of smart contracts which are getting popular for property and casualty insurance. When used in combination with connected devices, a smart contract can trigger automatic claim processing when, for example, anti-theft sensors go off under certain pre-programmed conditions. 

However, the truly streamlined insurance management requires increased trust from both insurers and consumers. The best way to reach this balance is to create a blockchain-based ecosystem with a considerable number of high-profile participants. A model illustration is the Bank of China, which has recently partnered with leading insurance companies and launched its own blockchain. Once new records are added to the blockchain, the distributed ledger technology helps update and validate the data against other records in the network, which significantly reduces operating costs, at the same time providing high security for transactions.

The distributed ledger technology also deals with one more factor that slows down claim management—the need for bank transfers. As a rule, customers don’t see payouts in their accounts for weeks. However, when banks and insurers have a single system they trust, the payouts can be processed without considerable delays.

See also: Blockchain, Privacy and Regulation 

Final thoughts

Blockchain is a decisive factor in transforming the insurance industry and helping it break free from outdated traditions. The need for innovation in insurance is critical—customers are craving transparency, speed and cost flexibility. Blockchain is designed to deliver on these desires and meet all the participants’ particular expectations. 

When there’s little to no chance of fraud, people will trust their insurance agents more. When complex policy claims are processed 10x faster, there’s no room for friction. At the same time, when claim processing is automated, insurers have more possibilities to be flexible with pricing. 

What’s more, the covered use cases are just the beginning. With more blockchain-based applications going live and more companies entering into collaborations, the insurance industry can grow its tech ecosystem to create better products for case management, audit and risk modeling.

Analytics can be a great equalizer in every industry. It's why 90% of respondents to a McKinsey survey call their analytics investment "medium to high" and another 30% referred to the investment as "very significant" proof that the surveyed understand the value that analytics possesses.

Those investors—especially the commercial insurers—understand the value of analytics and get their money's worth. In addition to improving sales targets and reducing churn, analytics can increase profitability when it comes to underwriting and selecting risk.

Still, the full potential of analytics goes beyond the insights it provides insurers. When merged with modern technology, data and analytics can fuel efficiency, accuracy and productivity. When used within the decision engine to drive automation, for example, data and analytics can help insurers expedite processes and improve customer experiences, even without human intervention.

Automated reports and actions provide insurers new ways to optimize their day-to-day operations. However, the marriage of automation and analytics is especially vital for the small commercial market as they contend with higher volumes of policy quoting and writing. Using predictive models, automation can reduce the amount of human effort it takes to sell and service policies for small businesses.

Analytics and automation present opportunities to optimize every facet of growing market share for small commercial insurers if properly applied. The sooner that insurers embrace the two, the better off they—and their customers—will be.

Analytics and Automation Can Deliver

When it comes to risk assessment for small businesses, insurers are usually hampered with limited or even misleading information. Unfortunately, this can result in a gap between a risk-appropriate rate and the quoted premium. Thanks to automation and analytics, however, that sort of disparity can be a thing of the past.

See also: What Predictive Analytics Is Reshaping  

While there are many ways analytics and automation can be used to improve the small commercial insurance industry, there are three particular areas where major improvements have been demonstrated. For insurers that are on the fence about committing to analytics and automation, here's where their influences will likely be most visible:

1. Simplified Applications

By automating customer quoting and underwriting, insurers can phase out the process of collecting troves of information on an application. With reliable third-party data sources, automation can fill in many of the blanks present on typical applications. Insurers will then only need to ask for what’s relevant for the predictive model to assess the risk and provide direction on pricing.

In the same vein, the automation of processes and decisions empowers insurers to use straight-through processing for new applications—quoting and binding policies entirely through an e-commerce experience, without involving staff or consuming staff time. Typically, this is a far more streamlined process for both the insured and insurer, and delivers improved customer experiences.

2. Expedited Claims Processing

Small businesses are acutely sensitive to how long it takes insurers to pay claims and how good (or bad) their experiences are. Analytics helps insurers triage claims while suggesting different processing options.

According to a LexisNexis study, the availability of this data helps shorten processing cycle times by up to 15%. For example, through IoT (internet of things) devices, an insurer can detect water heater leaks and other high-risk problems in real time, enabling the insurer to anticipate potential claims and possibly even prevent them.

Of course, being fast is only part of the equation—the process must also be accurate. Thankfully, automation and analytics improve processes by catching overlooked data points. When sophisticated analytics are applied against a large sample of detailed claims data, the resulting insights can, for example, highlight the best way to get an injured employee back on his or her feet and offer a customized plan to do so.

See also: What’s Beyond Robotic Process Automation  

3. Improved Risk Identification

By using reliable third-party data, such as information available through a data consortium, insurers can more quickly and accurately identify risk—even if it’s in a sector where they have little or no experience—and ensure that risk-appropriate pricing is quoted. Analytics thus becomes a valuable growth engine for insurers to confidently expand into different business lines and regions.  In an environment where 40% of the smallest organizations have no business insurance whatsoever, insurers that embrace modern technology could reap significant rewards. By combining analytics with automation, the small business insurance market could be transformed—which would be welcome news for both insurers and their customers.

Did a Chinese general from 500 B.C. know more about the current state of data and analytics than many modern insurers? 

Sun Tzu, the over-quoted author of The Art of War, wrote about battle – not binary code – yet his most famous saying perfectly captures the dilemma facing today’s insurers attempting to embrace data analytics: “Tactics without strategy is the noise before defeat.”

The buzz around big data is as loud as ever, but life and health insurers report mounting pressure to define a strategy and deliver a return on investment, according to RGA’s 2019 Global Life and Health Data Analytics Survey. Many are struggling. While eight out of the 10 major multinational organizations participating in RGA’s online survey reported having a data analytics strategy in place, half were in early stages of putting this plan into practice and one had not yet begun.

What accounts for the delay? Part of the problem may rest on a simple misunderstanding. It can be tempting to make the mistake of classifying data strategy solely as an information technology (IT) function, focusing on the back-end processing and management of ever more complex and voluminous data sets. But transforming a collection of initiatives into a successful data and analytics program requires more than efficiently managing ones and zeros. A true strategy should enable a carrier to maximize business value from data.

Technology is an enabler along the journey, but, to succeed, a carrier must first agree on the destination. Is the enterprise seeking to enhance in-force management, generate more leads, accelerate underwriting, engage more customers, manage claims more efficiently or something else? In RGA’s Data Analytics Survey, carriers identified the business areas most likely to be transformed by data analytics over the next three to five years. Eight of 10 participating insurers agreed that data analytics would have a “high” or “very high” influence over practices within distribution, underwriting, claims management and marketing/branding functions, with 60% of respondents sharing the intent to invest significantly in data-driven accelerated underwriting.

See also: Understanding New Generations of Data  

Next, the insurer must understand the many data sources available, whether traditional (fully underwritten) applications and financial disclosures, digital sources such as electronic medical and prescription records and insurance-linked wellness programs or more leading-edge information gathering via social disclosures and “Internet of Things” devices. Interestingly, only one carrier in RGA’s Data Analytics Survey acknowledged using wearable information such as steps, sleep and heart rate monitoring from wearable devices, but 60% of respondents plan to use wearable sources in the future. 50% indicated plans to employ “digital fingerprint” data that draw on social media disclosures, although none of the respondents use such data sources today.

To respond to these questions, successful data strategists adhere to four basic principles:

• Prospect — Effective data valuation – the evaluation of internal and external data sources – and processes to identify, prioritize and acquire new data sources are essential.
• Communicate — Carriers with successful data strategies have focused on understanding and communicating the data assets available within the enterprise. 
• Optimize — Extracting maximum value from the data available generally involves identifying new or underused data assets, enriching existing sources and monetizing data or data-driven algorithms.
• Protect — Data protection is an essential consideration. Carriers must constantly weigh how to best eliminate or mitigate risks related to data privacy and protection. 

Know the Landscape

Defining a data strategy begins with these four principles, but it doesn’t end there. As Sun Tzu noted, “He will win who knows when to fight and when not to fight.” Before pursuing a plan of attack, Tzu argued that the successful general first surveys the field of battle and evaluates the strengths and weaknesses of both armies. An effective data strategist must study the industry landscape and determine what information is available, relevant and compliant.

The data and analytics field is advancing more rapidly than regulatory rulemaking in certain markets, and carriers are challenged to plan for the future while regulatory constraints and expectations are still shifting. A “guidance map” can help, so long as it is revisited regularly. In most regions, a single piece (or two…) of legislation tends to govern overall approaches to data use. Building off this legislation, carriers can establish overall frameworks to guide risk mitigation and anticipate which data applications are likely to be acceptable. This is a start – not an end – and insurers must continue to track and respond to overall regulatory change.

Conducting a data inventory, either through manual fact-finding and in-person interviews or by purchasing an automated system to crawl available databases to catalogue them, is another important step. Aside from revealing gaps, an inventory can democratize awareness of available data beyond a small coterie of experts and help carriers draw on the collective insight of the broader organization. RGA’s Data Analytics Survey asked insurers which data sources they currently use within their organizations. In the underwriting function, the top data sources used today were claims history (60%), prescription data (50%), lab/exam and motor vehicle (40%).

Top Down or Bottom Up? 

Armed with greater insight, insurers can draw up a “target list” of data sets to pursue. This is easily the most resource-intensive task facing any data strategist, but it can also be the most rewarding. When determining the best approach to developing such a list, size doesn’t matter, but organizational maturity does. Our favorite general could have been advising any insurer’s board room when he wrote: “He will win who knows how to handle both superior and inferior forces.”

A bottom-up method is best-suited for a larger, better-resourced data and analytics team. With this approach, companies dedicate a team of seasoned professionals to systematically explore available data sets throughout an organization for untapped opportunities. This requires a deep understanding of market conditions, the capacity to methodically break down big data sets into more manageable segments and the freedom to delay immediate return on investment. The team should regularly meet with business leaders to evaluate progress.

See also: Data Prefill: Now You See It, Now You Don’t  

A top-down approach has more in common with the fail-fast ethos of a startup and works best in leaner, more limited and less structured organizations. Participants brainstorm business problems that can be solved as new and interesting data sources emerge. Rather than examining all available data, set by set, resources are focused on gathering input from business leaders, synthesizing project ideas, evaluating what business needs benefit most from a data-based solution and then coming to a consensus around concepts with the greatest chance of success. This approach generates results faster and with less investment, but, because it relies heavily on the knowledge and guidance of a few executives, it can miss opportunities. 

Tzu realized more than a millennia ago that, to win, any enterprise must out-think, rather than out-fight, an opponent. When it comes to today’s modern insurance landscape, military metaphors only extend so far. Still, it’s undeniable that a new competitive contest has emerged over data, and an effective strategy will distinguish the victors from the vanquished.

Curious? Contact us to discuss techniques to develop an effective data strategy in your organization.

The automotive claims process has long been strenuous, time-consuming and costly both for insurers and consumers. The moment an incident occurs, a driver is placed in a world of stress. In addition to managing the emotional strain that is a car crash, the driver now has to deal with several different parties to repair the damage. Traditionally, it takes one to three days after filing a claim to initiate contact with an insurance adjuster (it takes even more time if the adjuster needs to inspect the damage).

There is suddenly an unexpected burden consuming time and money and requiring paperwork. But advancements in artificial intelligence and telematics (such as our new Claims Studio) can revolutionize the claims system by validating claims, processing them much faster and placing safety at the forefront for drivers. 

Here are three ways the insurance industry can adapt to improve the claims process: 

Validating Claims

Automotive claims have historically been a manual process, where drivers retell their side of the story following a collision. These details are then shared with insurance companies, adjusters and, at times, even courts, to resolve claims and disputes. This process leaves room for ambiguity and human error, because, as we all know, there are two sides to each story. We also have to take into consideration the shock that results from a car crash – a driver might not remember or realize immediately the need to take photos of the damages or call the insurance company to begin the claims process.

Insurers can help drivers mitigate this complicated and stressful process by implementing advanced technologies, now available, that provide accurate, unbiased crash storylines. These narratives detail key findings such as the severity of a crash, where the vehicle was hit, the driver’s speed (before, during and after a collision), the weather and more. A claims adjuster needs this information to do his or her job. When this information is incomplete or inaccurate, the process takes longer, and costs increase for the driver.

Accelerating the Claims Process

In addition to enabling insurers to settle claims more seamlessly and accurately (preventing potential fraud), these technologies aid in settling claims earlier, paving the way for better customer experiences. For example, our solution automatically populates crash insights and reporting into a web portal or directly into an insurer’s claims management system, providing insurers with many details needed to quickly process a claim. By offering claims adjusters this information within 10 minutes of an accident, insurers are empowering them to help drivers quickly resolve their issues.

Placing Safety at the Forefront

The use of artificial intelligence and telematics has brought significant benefits to insurers and consumers. Several auto insurers are already using mobile telematics to assess risk and promote safer driving behavior, but the benefits don’t start and end there. In fact, one of the most important – and life-saving – aspects of the technology is the ability to detect crashes within moments of their occurring. Technology provides real-time notifications of a vehicle crash to quickly send roadside assistance to drivers when they need it most. By providing critical details like GPS location, time and driver identification, new crash detection solutions enable insurers to save valuable time in emergency situations, offering an added level of peace of mind. 

See also: Untapped Potential of Artificial Intelligence  

In some instances, the new technologies could also save a life. One instance is Discovery Insure, a South Africa-based insurer that uses our Crash Detector to send immediate roadside assistance and paramedics to customers following collisions and life-threatening crashes. One customer, Evelyn Sadler, received immediate attention after a taxi swerved into her vehicle, causing it to go airborne. As the distracted driving epidemic increases, causing 1.25 million people to die in road crashes each year, insurers can offer drivers technologies and solutions that can keep safety at the forefront and prevent many deaths. 

The future of the automotive claims system is already here, with several insurers realizing the impact this technology has on their bottom line. I’m excited to continue to watch this space grow – and hope that additional insurance organizations will quickly follow suit.