Back in the days before the Wall Street Journal used photographs, the publisher was once asked for the reason. "If we don't use photographs," he said, "we don't have to deal with photographers."

I sometimes think the reason there isn't more innovation — and not just in the insurance industry — is that it's a pain to deal with true innovators. True innovators are disruptive. They can be abrupt, even rude, because they're often mad about something they want to fix and they're in a hurry. They aren't always right — but good luck telling them that. And did I mention that they're disruptive? Once they nail the big idea, they force an awful lot of people to change an awful lot of things that they've done comfortably for a long time.

People often tell me they'd like to write a book. I tell them they're wrong. Writing a book is really hard. People don't actually want to write a book. They want to have written a book. 

I'd say that's true of most companies. They don't want to innovate. They want to have innovated.

That's a long way of saying that Gordon Bell, a computing pioneer I had the privilege of knowing and occasionally working with over the past 35-plus years, died recently. Though known primarily as the father of the minicomputer, Gordon was a profound innovator who had a sweeping effect on the progress of computing over the past 60 years, and I'd like to tell you a bit about him.

I'll get to some of the basic biographical bits at the end of this — and there are some interesting ones, such as that he was a professional electrician by age 12 — but I'll start with what struck me most about Gordon: his let's-cut-to-the-chase mentality. 

Some of Gordon's cut-to-the-chase comments became famous. In the early days of computing, when much of what's now done in the processor was accomplished via a host of devices inside the box surrounding the processor, Gordon decreed: "The most reliable part of a computer is the one you leave out." When he became more senior as his career progressed, he announced that "a demo is worth 1,000 pages of a business plan" (and you had to be awfully well prepared to defend that demo). When he served on boards, and management made a projection he didn't accept, he'd lean across the table and say, "Wanna bet? $1,000, your money against mine, I say you don't hit that number." He found that making an executive bet their own money, as opposed to corporate funds, had a way of getting their attention.

My longtime colleague John Sviokla says Gordon once showed him a Decmail he sent to the founder and CEO of Digital Equipment Corp. (DEC) in 1977 that went something like this: "I just came from the XX product meeting, and there are too many people on the team. But this is Digital, and we can't fire anybody, so I suggest we create the NOD, the No Output Division, and we transfer half the team to the NOD. The product will come out faster. — regards, Gordon."

Gordon could go beyond caustic, too. The New York Times obituary says he was known for throwing erasers at people in meetings. My frequent co-author and friend Chunka Mui wrote a lovely encomium to Gordon's "boyish and tempestuous enthusiasm" but... describes a meeting where Gordon pulled a knife. 

It was just a pocketknife, and he used it to cut the cord of his own microphone while on a panel Chunka was moderating, but he still caused quite the scene. A questioner wouldn't concede on a point where Gordon had deep technical expertise, and Gordon wouldn't stop hammering him. Finally, the questioner's thesis adviser told Gordon to "just shut up" — and Gordon did, in his own way. 

But Gordon was fundamentally a generous, warm-hearted man, and, as much as he zeroed in on weak arguments and unhelpful bureaucracy, he lit up and could positively cackle when something struck him as right. He sometimes burst with so many ideas at once that he was hard to follow; his brain would jump to a new sentence before his mouth had finished the previous one. 

I'll never forget the presentation that Chunka and I made at a conference Gordon attended as we were getting ready to release "Billion Dollar Lessons," based on research we and 20 consultants had done over two years into 2,500 corporate disasters to identify patterns of failure. Gordon dashed up to us as we left the stage and, with a big grin, said, "Screw the book. We're going to start a hedge fund and make millions."

Gordon certainly had great technical skills — he was known as the Frank Lloyd Wright of computer architects — but a lot of people have great technical skills. Where Gordon stood out, at least for me, was that he had a vision (and that, of course, it turned out to be right).

After earning his bachelor's and master's degrees in engineering at MIT, Gordon joined Digital in 1960, a time when computers were mainframes, multimillion-dollar behemoths occupying huge, air-conditioned data centers and served by technicians in white lab coats. Gordon quickly became the chief architect for the PDP line of minicomputers that put DEC on the map. That work set up his vision: finding ways to get computing out of the data center and to people who could interact with them.

He left in 1966 after butting heads with the founder and CEO one time too many. (That combative, take-no-prisoners streak again.) He taught computer science for six years at Carnegie Mellon, where he became a pioneer in time-sharing — if he couldn't get the mainframe or minicomputer to you, he could at least connect you to it.

Gordon returned to DEC in 1972 and developed the VAX line of minicomputers. They were such a success in the market that they made DEC the second-largest computer company, behind only IBM, for many years. They were also a technical tour de force, known for communicating seamlessly with other computers. When I covered IBM for the Wall Street Journal in the late 1980s, IBM minicomputers were still so bad at talking to each other that the suggested solution was to put one of Gordon's VAXes in between them. 

Gordon left DEC again in 1983 after a massive heart attack that he blamed on the stress of his relationship with Ken Olsen, the CEO and founder. When Gordon recovered, he retired, declaring that DEC had lost its way. (It had.)

He briefly went into public service, joining the National Science Foundation in 1986 and, pursuing that vision of making computer more available, led an initiative to link the world's supercomputers via high-speed network. That proved to be a powerful accelerant to the development of the internet. 

Gordon is also known among techies for Bell's law, which he posited in 1972 and which says that a new form of computing will appear roughly every 10 years. Mainframes were the 1960s, minicomputers the 1970s, personal computers the 1980s, the web browser in the 1990s, smartphones in the 2000s, the cloud in the 2010s, generative AI in the 2020s... and we'll see what's next.

I think Gordon was searching for a potential new form of computing when he began his last major project, in the 2000s, which produced a thought-provoking book, "Total Recall: How the E-Memory Revolution Will Change Everything." Gordon decided to digitize his life, so he captured everything he could find: writings, photographs, speeches, you name it. He began wearing a small camera around his neck that took the occasional photograph (once a minute, if I recall), wore an arm strap that captured his biometrics and began recording his phone calls. 

He never quite figured out what to do with all those digital bits, but I'll always remember him with a little camera around his neck and a big grin on his face as, in his 80s, he was still happily playing around with ideas. 

When his family sent out an email announcing his death, they began with a recent quote from him: "Old computer pioneers don't die; they just lose their physical bits."

*****

I'm all for innovation. I just want to be sure we're prepared for all the good, the bad and the ugly — or, in Gordon's case, the great, the uncomfortable and the sometimes caustic — that comes with it, and I hope understanding a bit about Gordon's trajectory will help set expectations.

I also obviously was looking for a way to express my admiration publicly. Thanks for hearing me out.

Cheers,

Paul

Alex is the chief people officer at Sidecar Health, responsible for growing the team and crafting a culture that will fuel its team to achieve its ambitious mission. She has spent her career building companies across a variety of industries and in various roles, from strategy and business operations to people and places. She has led the development of the people function from the ground up at several fast-growing startups, shaping them into award-winning workplaces. She was most recently head of people at Ike (now Nuro), a company developing automation technology to transform the trucking industry. Prior to that, she was the VP of people and culture at Glint (now part of LinkedIn), an industry-leading HR SaaS platform. Alex has a master’s in research and evaluation and a bachelor’s in anthropology from the University of California, Los Angeles. She’s an avid traveler and backpacker, and if she could travel anywhere, it would be back in time to watch Jerry perform with the Dead.

Sherry Chan is the chief strategy officer for Atidot, a Series B funded insurtech startup that uses AI to create opportunities for life insurance companies across the value chain.   Sherry has over 20 years of actuarial experience, having served as chief actuary for the city of New York and the state of Ohio. As New York City’s chief actuary, she provided technical expertise to the city’s five retirement systems and pension funds, with approximately 800,000 participants and nearly $275 billion of assets, certified the $10 billion annual required pension contributions and oversaw a city agency with a professional staff that has decades of experience in and out of city service. She is a board member of the Society of Actuaries.  Sherry obtained both her bachelor of science in actuarial science and mathematics and her executive MBA from Ohio State University. She established the university’s first actuarial endowment, the Sherry S. Chan Actuarial Endowment, and is a member of their College of Arts & Science Dean’s Advisory Committee.

Insurance Thought Leadership

Let’s begin with health insurance. 

For decades, we've all been reading about soaring healthcare costs and, thus, much higher insurance premiums, but an article this month in the Washington Post says that the increases in premiums have been declining and that premiums have actually risen more slowly than general inflation since 2020. Alex, as the chief people officer at Sidecar Health, are you seeing that sort of trend?

Alex Coonce

The sad truth is that even if the rate of increases is slowing, premiums continue to rise and the overall cost of care for most American families is already, or is very quickly becoming, unaffordable. The median family income in America is about $70,000, while the average family premium cost is north of $20,000. Spending nearly 30% of a family’s income on health insurance premiums is simply unsustainable. The math doesn’t work. Meanwhile, the three biggest health insurers in America took home nearly $900 billion in revenue in 2023, so the incentive structure is clearly unbalanced.  

We’re proud that our annual premium increase averages 4% for all our employer groups, which our data shows is nearly three percentage points lower than traditional carriers in our markets. Not only do our premiums start on average 20% lower than traditional carriers, we’re also able to keep renewals low because our model is the first to truly align incentives and put patients in the driver’s seat of their care. When armed with choice, transparency and the power of cash to pay for care on the spot, our members make smart decisions, which result in lower total out-of-pocket costs. 

Insurance Thought Leadership  

We've also all read about employers increasing deductibles and generally trying to limit their exposure on the health insurance of their employees. Is that fair? What are other trends you're seeing in employer-based healthcare?  

Alex Coonce

Unfortunately, “fair” is not a word often associated with today’s healthcare system. As costs continue to rise, employers are in the tricky position of having to balance business needs and their bottom line with increasingly unaffordable health plans for their employees. Ultimately, increased costs typically trickle down to employees in the form of higher premiums and deductibles.   

Employers are getting creative to limit their exposure and reduce costs, from moving toward high-deductible plans, launching wellness programs, investing in telehealth and even building on-site clinics. Lately, we’ve seen more employers implement prescription drug management programs, using pharmacy benefit managers (PBMs), promoting the use of generic drugs and providing access to specialty medications through specific channels. Some employers are even adopting tiered network plans, where employees pay different levels of out-of-pocket costs depending on the healthcare provider they choose.

The reality is that all the tactics I mentioned are necessary on traditional health insurance plans. With the introduction of new models like Sidecar Health, employers realize the financial advantage immediately, while their employees benefit from both lower costs and unprecedented access to high-quality affordable care where they’re in full control of their decisions around who to see.

Insurance Thought Leadership

What are you seeing in terms of individual care?

Alex Coonce

What you see is people choosing to go uninsured. Nearly 28 million people in America don’t have health insurance, and that’s because it’s simply too expensive. What we learned in the individual market was that even if you pay for insurance, it doesn’t mean your insurance guarantees you access to affordable healthcare. Often, your insurance-negotiated rates, your copays and coinsurance are on average 30% more expensive than paying for care directly. 

The Sidecar Health model has demonstrated some key learnings that can help shape the future of healthcare for all. For example, direct, cash pay models often result in lower prices. Also, putting incentives in place for consumers to make their healthcare decisions instead of financial institutions results in more informed care decisions and lower expenses.  

Insurance Thought Leadership

Turning to life insurance: 

Sherry, as chief strategy officer at Atidot, could you please explain a bit about how you use AI and what the benefits are, both for Atidot and for your customers on both sides-- the carriers and the policyholders?  

Sherry Chan

Atidot employs both “traditional” AI and generative AI. The former is used to help predict policyholder behavior, such as what insurance product they may want, how much of it they want, when they may want it and how long they will want it for. GenAI is then used to process these insights into a usable format for the carriers. 

For example, if our predictive models are showing there is a lack of demand or satisfaction by policyholders on a certain insurance product or feature, carriers can leverage our genAI offerings to acquire, engage or retain their policyholders. Our AI models have proven success in assisting policyholders in better understanding insurance and assisting carriers to provide better customer service, all while crafting a personalized journey that is more beneficial and efficient for all parties involved.

Insurance Thought Leadership

COVID sparked a surge in purchases of life insurance. Is that continuing, or are we regressing to the mean?

Sherry Chan

Life insurance is still being purchased; it’s just in a different format. During COVID, when death was a heightened concern and people were social distancing, life insurance purchases surged in the direct-to-consumer market. Due to folks’ urgency of wanting to secure a policy, term insurance’s cost relative to other insurance products, and its availability online, made it the popular go-to purchase. Now, we see a shift back toward fully underwritten products. People are more comfortable being back in person and no longer feel they need a policy immediately, which affords them the opportunity to be better educated about the various products and features, and prices are lower because people are willing to engage in the traditional, in-person underwriting process.

Insurance Thought Leadership

How can we continue to encourage people to narrow the protection gap? 

Sherry Chan

Narrowing the protection gap can be approached from several angles. One, there needs to be better insurance education so individuals understand the benefits, the options and the process of securing a policy. Another approach is to provide incentives to agents to better service policyholders, balancing their engagement between new business and in-force business. Lastly, it’s also about helping carriers better understand their customers so they can nurture the relationship and provide a personalized experience throughout the value chain.

Insurance Thought Leadership

There has been a move away from the traditional approach to life insurance, requiring a medical exam and collection of fluids. As an actuary, how far do you think we can truncate that process while still underwriting accurately?

Sherry Chan

This heavily depends on data – i.e. how much data we can get and how accurate the data is. The more data we can get and the more accurate it is, the better we can train the models being built, making the results more and more reliable and cutting down the need for other processes. Additionally, data can also be available across time, as opposed to a specific point in time, which would allow us to deduce trends, paving the way for the underwriting process to be even more accurate and less dependent on traditional approaches. The possibility of instantaneous underwriting can be limitless with the growth and improvement of data!

Insurance Thought Leadership

Are there any other major trends that our readers should know about? 

Sherry Chan

There are several trends taking shape that are causing products and markets to merge. First, there will be a great wealth transfer of $90 trillion in the next 20 years from the Silent Generation and Baby Boomers to the Millennials. With this transfer will come a demand for shifting insurance and retirement planning needs, merging these two industries closer together. Another trend we already are seeing is private equity firms’ purchase and entrance into the insurance market, which brings about a lot of changes. A third trend is the changing landscape in fiduciary regulations. Together, these trends will converge asset management with wealth management, so people will need to think more holistically in financial planning, with insurance being in the mix of it all.

Insurance Thought Leadership

What didn't I ask you about that I should have asked you about? 

Sherry Chan

Through time, our economy’s engine has shifted from its dependency on our hands to a dependency on our heads and our hearts. Our country used to be largely manufacturing, leveraging our hands to work. Then our country shifted toward more white-collar jobs where we use our heads to work. Looking ahead, we will need to depend on our hearts more to work. We are already seeing this movement where empathy is seen as a leadership trait, where brands are canceled if they don’t align with certain passions and where marketing for companies like cell phone providers, airlines and insurance carriers are focused on selling the feeling and security of connecting you with loved ones or protecting the people and things that matter most to you. Other examples of our economy operating off our hearts are present in social media “likes” and even in the newest versions of genAI that many of us find mindblowing because they’re so emotive. 

With this changing world, we’re all implored to think about how we will change, too.

The difficult economic and climatic conditions of the past few years have created a challenging environment for commercial property owners. Despite an improvement in reinsurance capacity since the financially devastating year of 2022, underwriters continue to face headwinds, and conditions remain less favorable than in past years.  

Inflation and other macroeconomic pressures are not helping. Significant increases in structural steel and concrete products have been particularly challenging for builders and played a major role in ballooning construction costs. Meanwhile, construction wages have risen by 22% over the past four years, roughly matching the general level of inflation. These difficulties are exacerbated by labor shortages within the industry, with 77% of contractors reporting difficulties in sourcing skilled workers for building projects. All this has inevitably led to delayed construction timelines and higher business interruption costs. 

In addition to these economic pain points, geographic and climatic conditions have become major factors in elevated property insurance prices. Regions prone to hurricanes, floods, wildfires, tornadoes and winter storms typically see higher insurance rates due to the increased frequency and severity of these events, which collectively caused losses exceeding $100 billion in 2023 alone.

See also: Parametric Insurance Can Tackle Climate Risks

From 2020 to 2022, the U.S. experienced 60 weather and climate disasters with losses exceeding $1 billion each. The total damage from weather and climate disasters since 1980 amounts to approximately $2.7 trillion. On average, from 2018 to 2022, the U.S. endured 18 such disasters annually. The year 2023 set several weather and climate records. Notably, Earth experienced its warmest July on record, and Tropical Storm Hilary became the first tropical storm to hit Southern California in 84 years, shattering daily rainfall records. Overall, 2023 witnessed 28 weather and climate disasters with losses exceeding $1 billion each. Flooding events alone caused almost $7 billion in damages across the U.S. 

The combination of a lackluster economy, workforce shortages,and escalating material costs has put commercial property owners in an unenviable position. In the past, property insurance rates primarily depended on the building's quality. Today's pricing is increasingly determined by factors such as construction year, materials used and whether a property’s location renders it vulnerable to surging natural disasters.

What should commercial property owners do? 

Insurance strategies that would have been conservative in 2018 have been rendered prudent by the challenging property market of 2024. In this type of environment, it is crucial for property owners to ensure that their coverage is both adequate and cost-effective. Those who are concerned about their current coverage or dreading their next renewal should consider taking the following steps to mitigate their risk profile and make themselves as appealing as possible to insurers: 

See also: Glimmers of Good News on Climate (Finally)

1. Conduct a Professional Property Inspection:

Engage a licensed professional or organization to thoroughly inspect your property. This step can help identify potential risks or existing damages that may affect your insurance premiums. 

2. Obtain an Up-to-Date Building Valuation:

Have your insurance agency perform a detailed valuation of your building. This ensures your coverage reflects the current value and condition of your property, helping you avoid being underinsured. This is especially important in the context of recent inflation – outdated valuations may lead to underinsurance.

3. Benchmark Your Costs:

Compare the insurance cost per square foot of your property with similar structures in your area. This will help you understand if you are paying a competitive rate and where you might negotiate better terms.

 4. Prioritize Repairs and Upgrades:

Address any delayed maintenance issues such as sprinkler system upgrades, roof repairs and updates to security and electrical systems. These improvements can reduce the risk of damage and potentially lower your insurance premiums.

5. Prepay Premiums and Bundle Policies:

Consider paying your premiums in advance, if possible, as some insurers offer discounts for prepayment. Additionally, bundling multiple policies with the same provider can also lead to savings.

6. Advocate for Your Coverage:

Ensure that your insurance agency is seeking the best possible coverages for your property. Regularly review your policy details with your agent and make adjustments as market conditions and your property needs evolve.

Balancing the priorities of premium costs and coverage quality is a perennial challenge for commercial property owners and one that has become more difficult than ever in the past few years. In this fluid economic and climactic environment, it is more important than ever that you look critically at your policy and take common-sense steps such as those listed above to lower your risk profile and get the best coverage you can. You have the power to avoid becoming a statistic. When significant damage occurs, there is no advantage to being underinsured.

Summary:
A recent discussion with one of our customers highlighted a sophisticated global car insurance fraud where criminals exploit insurers' lax verification processes. The fraudsters insure cars online without ID verification, report lost keys, and either tow the vehicle or recode the keys to steal it. They also damage the car to necessitate towing, gaining possession through these means. This scam has been identified in multiple countries, including the US, UK, and South Africa, prompting insurers to implement stricter verification measures using data from credit bureaus. FRISS suggests enhanced defenses like multi-factor authentication, biometric verification, cross-checking details, and stricter key replication policies. Additionally, insurers should verify towing requests, educate policyholders on proper claims procedures, and use network analytics to detect fraud. These measures aim to balance robust fraud prevention with maintaining a positive customer experience.

A recent discussion by our very own VP of Sales EMEA/APAC, Ariane Braam-Verkoren, with an insurer highlighted a concerning global fraud scenario that organized networks are leveraging against insurance companies worldwide. 

Here's how the scam unfolds: 

The criminal selects a car from a parking lot, then insures it online through a provider that doesn't require ID or ownership verification. Shortly afterward, they report lost keys, prompting the insurer to either tow the vehicle to a chosen location or send a locksmith to recode the keys, enabling the criminal to drive away. When they discovered that some insurers don't offer key replacement, they adapted by puncturing the car's radiator to mechanically damage it. Their goal in this case is likely to have the vehicle towed to another location, thus gaining possession of the car. 

Claims with a similar modus operandi have been identified in countries such as the US, UK and South Africa, where these criminals exploited the lack of stringent verification processes by using fictitious information to facilitate car thefts, staged accidents or using towing operators to uplift accident damaged vehicles to their towing yards where they hold these vehicles ransom until the insurer pays for the release.   

Throughout this process, nobody checks if the person reporting the loss or damage is the rightful owner of that car.  

As a result, insurers in these regions have implemented stricter policies and verification processes to confirm insurable interest. They leverage data from credit bureaus during the application process to verify customer information. This functionality is also available in other countries, especially in Europe, where similar data sources are utilized to enhance the accuracy and security of the insurance application and claims processes. 

Here’s how insurers can bolster their defenses, with assistance from FRISS: 

Identity Verification 

Multi-Factor Authentication (MFA): Require the person reporting the loss or damage to provide both a driver's license and a photo ID. 

Biometric Verification: Implement biometric verification methods, such as fingerprint or facial recognition. 

Secondary Contact Method: Verify the claim by calling a registered phone number or sending a confirmation message to the policyholder's contact number. This step ensures that even if fraudsters capture the contact details, the rightful policyholder is notified. 

Policyholder Verification 

Cross-Checking Details: Use FRISS technology to cross-check the person’s details against insurance records, ensuring they are the registered policyholder or an authorized individual on the policy. 

Alert System: Create an alert when the person reporting the claim is not listed in the policy information. FRISS scoring or identifiers can highlight discrepancies in contact details. 

Ownership verification: Requires the policyholder to provide proof of vehicle ownership when the policy is initiated. Alternatively, this verification can be facilitated through technology and data sources that automatically confirm ownership details. 

Strict Key Replication Policies 

Authorization Checks: Implement protocols requiring key replication requests to be authorized by higher-level officials within the insurance company. 

Call-Back Procedure: Establish a call-back procedure to the registered owner using a verified contact method. 

Manufacturer Key Replacement: Ensure that keys are replaced only through car manufacturing dealers, who are required to verify the owner's identity. 

Physical Presence Requirement: Mandate the physical presence of the car owner for key replication. If the owner cannot be present, require a notarized authorization. 

Towing and Repair Protocols 

Pre-Authorization for Towing: Verify towing requests through additional checks, including direct contact with the registered owner and confirmation of incident details. 

Secure Towing Contracts: Partner with towing companies that have strict identity verification protocols. 

Damage Verification 

Independent Assessor: Have an independent assessor verify reported damages before authorizing repairs or towing. If damage appears self-inflicted or malicious, initiate an investigation. 

Customer Education through Awareness Campaigns 

Claims Procedure Education: Educate policyholders on the importance of following proper claims procedures to prevent unauthorized claims. 

Verification Steps Awareness: Ensure policyholders are aware of the verification steps the insurance company will take to prevent fraud. 

Online Claim Registration: Advocate for the use of online claim registration processes that require login credentials, enhancing security. 

Network Analytics 

Watchlists and Network Analytics: Implement watchlists and network analytics to identify and monitor suspicious activity patterns and uncover organized networks. 

Conclusion 

These fraud scenarios highlight significant vulnerabilities in the current claims processes. Other trends such as claims of lower value, which often go undetected due to the thresholds set by insurers in straight-through processing, can also highlight a significant vulnerability.  Organized crime syndicates make use of these vulnerabilities and find their ways to fraud the system. By implementing stricter verification protocols, leveraging advanced technology, and educating policyholders, insurers can significantly reduce the risk of such frauds. This always needs to be in balance with the disturbance it might give honest customers who are in need of support. Collaboration with FRISS will provide the technological backbone to support these enhanced measures, ensuring that identity verification, network analytics and real-time checks on fraud scenarios are robust and secure without impacting the pleasant customer experience. 

Written by Dennis Potgieter

Sponsored by ITL Partner: FRISS

Even though insurance fraud costs companies billions of  dollars each year, detection has historically been a manual process. It relied on human analysts to identify patterns and anomalies in claims data. However, with the advent of big data and advanced analytics techniques, it is now possible to use technology to automate and enhance fraud detection. 

Understanding Insurance Fraud 

Insurance fraud is the act of intentionally deceiving an insurance company to receive an illegitimate benefit. There are many forms, including: 

• False claims: This involves submitting a claim for a loss that did not occur or exaggerating the severity of a loss to receive a larger payout. 

• Staged accidents: This involves deliberately causing an accident to make a false insurance claim. 

• Premium fraud: This involves providing false information to an insurance company to obtain a lower premium rate. 

• Identity theft: This involves using someone else's identity to make a false insurance claim. 

Underwriting Insurance Fraud 

Underwriting insurance fraud occurs when an individual or organization provides false or misleading information to an insurance company to obtain coverage or receive a payout on a claim. This type of fraud can take many forms, including providing false information about the value of insured property, misrepresenting the nature or severity of an injury or loss or failing to disclose relevant information that would affect the insurance company's decision to provide coverage. 

Insurance fraud can be costly for insurance companies, as they may end up paying out claims that they would not have approved if they had accurate information. This, in turn, can lead to higher premiums for policyholders as insurance companies seek to recoup their losses. 

To prevent underwriting insurance fraud, insurance companies typically conduct thorough investigations of applicants and claims, using a variety of tools and techniques to verify information and detect fraud. These may include background checks, inspections of insured property and analysis of medical records and other documentation.

See also: Disaster Fraud: The Dark Side of Claims

Fraud Detection Process at Underwriting Stage 

Claims Insurance Fraud 

Claims insurance fraud involves deceiving an insurance company to receive an illegitimate benefit. In contrast to underwriting insurance fraud, which involves providing false information during the insurance application process, claims insurance fraud occurs after a policy has been issued and a claim is submitted. 

There are different types of claims insurance fraud, including: 

• Created accidents: This involves deliberately causing an accident to make a false insurance claim. 

• Exaggerated claims: This involves inflating the amount of damages or injuries suffered to receive a larger payout. 

• False claims: This involves submitting a claim for a loss that did not occur or that was not  covered under the policy. 

• Multiple claims: This involves submitting multiple claims for the same loss to receive multiple payouts. 

• Fake billing and submission: This involves submitting a claim for a loss that never occurred, such as claiming a car was stolen when it was not. 

These are just a few examples of the many ways in which insurance fraud can occur. Detecting and preventing these fraudulent activities is crucial for insurance companies to maintain profitability and avoid losses.

See also: Coping With Insider and Outsider Fraud

Fraud Detection Process at Claims Stage, Investigation Stage, and Post-Claims Stage 

Using Big Data for Fraud Detection 

Big data refers to the vast amounts of data that are generated every day from a wide variety of sources. This data includes everything from social media posts and online transactions to medical records and government data. For insurance companies, big data provides a wealth of information that can be used to detect and prevent fraud. 

One of the main advantages of big data is that it allows for the creation of detailed profiles of individuals and entities. By collecting and analyzing data from a wide range of sources, insurance companies can gain a comprehensive understanding of a person's behavior and history, making it easier to identify fraudulent activity. 

For example, insurance companies can use big data to analyze patterns of behavior, such as how often a person files claims or the types of claims they file. If a person suddenly starts filing a large number of claims or claims for unusual types of losses, this could be a sign of fraudulent activity.

In addition, insurance companies can use big data to detect anomalies in claims data. For example, if a person files a claim for a loss that is far outside the norm for their geographic region or demographic group, this could be a sign of fraudulent activity. 

Advanced Analytics Techniques for Fraud Detection 

In addition to big data, insurance companies can use advanced analytics techniques. These include: 

• Machine learning: Machine learning algorithms can be trained to identify patterns in data that are associated with fraudulent activity. By analyzing historical claims data, machine learning models can learn to identify the characteristics of fraudulent claims and flag suspicious claims for further investigation. 

• Predictive analytics: Predictive analytics models can be used to forecast the likelihood of a claim being fraudulent based on historical data. By analyzing factors such as a person's past behavior and demographic characteristics, these models can assign a fraud risk score to each claim, allowing investigators to focus on the highest-risk claims. 

• Social network analysis: Social network analysis involves analyzing the connections between individuals and entities to identify patterns of fraudulent activity. By examining the relationships between claimants, insurance companies can identify networks of fraudsters who are working together to commit fraud. 

See also: Are You Fraud-Friendly?

The Future of Insurance Fraud Detection 

As big data and advanced analytics techniques continue to evolve, the future of insurance fraud detection looks promising. In the years to come, we can expect to see even more sophisticated fraud detection systems that use data and artificial intelligence to identify fraudulent activity in real time.

Adoption Phases of Big Data Analytics 

However, fraud detection is not a one-size-fits-all solution. While big data and advanced analytics can provide powerful tools for insurance fraud detection, the industry must be aware of potential challenges and limitations. Here are a few things the industry should look out for: 

• Data quality: The accuracy and completeness of data are critical for effective fraud detection. If data is incomplete, outdated or inaccurate, it can lead to false positives or false negatives. Therefore, insurance companies should ensure that their data is of high quality and regularly updated. 

• Privacy concerns: Insurance companies must also be mindful of privacy concerns when collecting and analyzing data. They must comply with data protection regulations and ensure that sensitive personal information is kept secure.

• Bias: Machine learning algorithms can be susceptible to bias, particularly if the data used to train them is biased. For example, if historical claims data is biased against certain demographic groups, the machine learning model may perpetuate that bias in its fraud detection. Therefore, it is important to regularly audit and evaluate algorithms for  potential bias. 

• Human intervention: While big data and advanced analytics can automate many aspects of fraud detection, it is still important to have human analysts review and verify suspicious claims. Human expertise is essential for making complex judgments and interpreting the nuances of certain claims. 

While big data and advanced analytics can provide powerful tools for insurance fraud detection, it is important for the industry to be aware of potential challenges and limitations. By addressing these challenges and ensuring that data is of high quality, accurate and unbiased, the industry can continue to improve its fraud detection capabilities and prevent losses.

A ransomware breach can be devastating for insurance providers, both in financial terms and in terms of the companies' reputation. 

With ransomware attacks on the rise and growing in sophistication, it is no longer enough to have a contingency plan in place if the worst happens; forward-thinking providers are looking at ways to prevent the next data breach before it can result in harmful media coverage and a class action lawsuit. 

That conversation should not be based in the IT department. Move it up to the C-suite level, where the focus is inherently directed toward the core objectives of asset protection and risk management. 

A systems review for vulnerabilities from unpatched software or password attacks should be on the agenda, but do not overlook the way in which most ransomware is now delivered—through phishing emails distributed to all of your personnel, from the CEO to the newly hired junior underwriter. 

Phishing emails? Like those old Nigerian prince scams? Hardly. By combining the capabilities of artificial intelligence (AI) with the voluminous amount of personal identifying information now easily accessible about all of us online, hackers can create personalized emails capable of fooling even the most vigilant employees. 

This is how phishing used to look:

Surprisingly, even these types of emails still claim thousands of victims every year. But the current state of phishing can create emails like this:

This email greets the recipient with a nickname commonly used by his friends and family. It was apparently sent by someone he knows and includes a photo and other personal details. The sender’s email address might be different, but given the preponderance of evidence that this is genuine, that difference could be attributed to the sender's changing email providers—if it is even noticed at all. 

What would happen if enough information were found about 100 of your employees to create an email like this? One financial organization ran a penetration test and found that phishing emails like this one routinely averaged a 4% click-through rate, with half of those who clicked also downloading a malicious payload. That means for every 100 employees at your company, four are potential phishing victims. And all it takes is one click from one work account to compromise your systems. 

How Do Hackers Obtain Private Information?

It’s easier than you might think. There are more than 250 data brokers that specialize in collecting personal identifying information on everyone, and sharing or selling access to that content to any interested party. 

The potential pools of content sources that can be accessed are seemingly endless: news articles, public records, property ownership documents, Google Street View photos, high school/college records, community events, social media. During COVID, data brokers paid restaurants, then desperate to survive with empty dining rooms, to share whatever customer information they collected from apps, loyalty programs and food delivery orders.  

In addition to personal and demographic data, organizations are also now gathering information on our opinions and behavior that can be leveraged to sell more products and services – and if data brokers want that content, as well, they are welcome to it. 

See also: A Resurgence in Credit Card Fraud

Protect Your Company – By Protecting Your Personnel

Ransomware gangs achieved an alarming 56% increase in victims worldwide in 2023, despite greater awareness of the risk and despite servers having been hardened to resist infiltration. And early indications suggest that 2024 may be even worse. Imagine having to send the dreaded email to policyholders acknowledging that their personal information may have been acquired by hackers, access made possible in part because of one employee’s Instagram post about his trip to the Grand Canyon.

Trying to control the flow and exchange of information online to prevent such an attack may seem like an impossible task – like putting toothpaste back in the tube. But it can be done, and focusing on that objective now is preferable to dealing with the cost of restoring IT systems after a breach, providing credit monitoring and identity theft protection to victims and coping with the negative publicity and the class action lawsuit.

The plan starts with education. While every insurance organization likely provides guidance on recognizing the common signatures of phishing emails and texts, intensifying these efforts may be necessary to make personnel aware of the enhanced capabilities of AI-generated emails, and how vigilance is now more important than ever. Anything that looks even slightly suspicious should be questioned and reported. 

Consider providing employees with a corporate account that monitors and removes personal information online. Some focus only on data brokers and people finder websites, where this content is most commonly found. Others will extend their search across the breadth of the internet to locate the kind of information that hackers exploit, and to make sure it comes down. Such services can cost as little as a few dollars per employee per year. 

Once that content is removed, there are ways to prevent new content from showing up; tools such as a VPN and VoIP numbers can replace authentic information (i.e. phone numbers, online search and browsing history) with content that cannot be traced back to an individual user. 

Not every organization will take these steps, which gives those that do an advantage because hackers, regardless of whatever IT skills they have acquired for their trade, are also lazy. They seek targets where the most content on the most individuals can be accessed and weaponized. If enough details about your personnel cannot be easily collected for a phishing attack that is likely to succeed, they will turn their attention elsewhere. 

See also: Are You Fraud-Friendly?

An Ounce of Prevention…

Cyberattacks are on the rise across all industries, but the financial sector, including insurance organizations, is particularly vulnerable to a wide range of threats. The reason is obvious: hackers know these targets have access to millions of dollars in funds and provide critical services that many people rely on. They also see a high likelihood that victims will pay the ransom quickly to restore access. A 2023 survey from Sophos found that nearly half of those organizations that were hit chose to pay quickly.

In 2023, financial organizations had to invest an average of $2.2 million to fully recover from an attack, plus what could be millions more in legal fees.

By increasing awareness of the challenge of phishing – with both your personnel and your vendors – and reducing access to personal identifying information, it is possible to keep these AI-enhanced attacks from claiming your organization as their next victim. 

As the global life insurance industry continues to undergo significant change, chief risk officers (CROs) have an increasingly pivotal role to play in ensuring their organizations prepare for a multitude of complex and wide-ranging challenges.

Geopolitical conflict and a changing climate

The impact of the war in Ukraine, together with the lasting effects of the pandemic, have led to a turbulent few years with higher inflation driving up interest rates and significant economic uncertainty. This geopolitical volatility has continued into 2024, exacerbated by the conflict in the Middle East and the prospect of elections in over 50 countries around the world. Against this backdrop, CROs will need to continually consider the wider potential implications of geopolitical risks on an insurer's risk profile, both economic and operational. 

Climate change, meanwhile, is complex, nuanced and characterized by uncertainty. The Institute and Faculty of Actuaries (IFoA) has warned that current climate-change scenario modeling techniques are significantly underestimating climate risk, with too much of a focus on regulatory scenarios, which, while they introduce consistency, also introduce the risk of groupthink. In addition, these techniques still exclude many catastrophic impacts that we can expect from climate change – they simply do not exist or are not well represented in models and methods that we use today. 

Also, the focus of most life insurers' investigations into climate change has been on the direct impact of physical and transitional risks on asset portfolios without considering the potential wider indirect impacts on both assets and liabilities--for example, considering how variations in climate might affect policyholder behavior, which could in turn affect mortality or persistency. To be more effective, CROs will need to address the material limitations and uncertainties of scenario modeling. 

Climate change requires a new lens through which to view materiality and proportionality, alongside current methods. The global risk landscape is more complex and connected, and the potential for disasters to cascade through systems is increasing with the impacts having greater geographical, social and temporal reach.

Regulation rising on the CRO radar

In the U.K., Solvency U.K. reforms have been well communicated, with changes to the risk margin having come into effect at the end of 2023 and matching adjustment reforms due in the middle of 2024. The PRA have also recently focused on funded reinsurance as one of their top priorities for 2024. The CRO will need to consider the impact of recapture on capital requirements, considering how collateral links to their risk appetite and have a plan for taking ownership of assets and liabilities in the event of recapture.

Meanwhile, IFRS 17 has been a long time coming, and our recent global survey of over 300 firms suggests more work is needed to complete the job. So far, much of the burden has fallen on the finance function to interpret the standard, implement new methodology and assumptions, adopt new systems and cope with increased complexity in the reporting. This is set to change, with CROs expected to become more involved. This is because the new IFRS standard contains more judgment than its predecessors. And where there is judgment, you typically see a greater level of oversight. IFRS 17 results are also externally reported, so a risk function is likely to have a closer view over model reliability.

See also: Building an Effective Risk Culture

Consumer outcomes and operational resilience

Regulatory focus in the U.K. during 2024 seems concentrated on consumer outcomes, evidenced by the rollout of the consumer duty introducing a new consumer principle that requires firms to deliver good outcomes for retail customers. It goes further by requiring firms to enable their customers to make effective decisions that are in their own interests. This is intended by the regulator to be a paradigm shift in delivering a higher standard of customer care and protection in the market.

This links to operational resilience, which is focused on the ability of insurers to adapt and respond to operational disruption. For example, the Financial Conduct Authority in the U.K. has been focusing on the potential impact on consumers, such as when disruption leads to claims not being paid. Significant progress has been made, with risk functions heavily involved in designing operational resilience frameworks and putting in place impact tolerances, with CROs continuing to have an integral role in the review and challenge in these areas. 

Raising the bar on model risk

Actuarial valuation models or day-to-day tools such as Excel used to produce key information to stakeholders are not always well governed, potentially leading to key numbers reported by a life insurer being incorrect due to the data calculations or process involved. This risk is exacerbated with the increased use of open source tools and data science techniques in models. While not a new challenge for life insurers in 2024, we do see a variety of levels of maturity in the market in terms of addressing model risk in the business, coupled with obvious intent by the regulator following a recent supervisory statement to U.K. banks, which we expect will require investment to raise the bar on model risk this year and into next. 

The incentive for insurers to make that investment is clear. Strong model governance provides greater confidence in reported results. Whether it's Solvency II or IFRS 17, quotes on new business acquisition pricing, numbers communicated in letters or online to customers, it's not uncommon to see material errors in reporting. These can and have had real business consequences, needing rework and redress. Yet, all too often, firms only implement strong model governance once they have made a material error.

See also: Behavioral Science and Life Insurance

Preparing for the unexpected

The CRO is responsible for maintaining an effective risk framework to help guide the business through foreseeable regulatory and business change, and with which the company can safely execute its strategy. For example, the business needs to have a clear risk appetite and risk limits to manage certain exposures. In addition to this responsibility, the CRO will also need to have the capability and tools to monitor and respond to a much wider myriad of emerging or horizon risks that have the potential to affect the business, some at high velocity and with little warning. 

You can bet your bottom dollar that the risk event that does arise will be slightly different to any that an insurer has potentially foreseen or modeled in advance. The rapid rise of generative AI is a clear example of a disruptive force, that is both risk and opportunity. The technology has evolved at astonishing speed with insurers finding themselves scrambling on a steep learning curve to recognize the risks and leverage the potential of generative AI. 

With insurers having to deal with increasingly complex challenges and opportunities, we expect to see CROs taking on a wider strategic role within their organizations. The risk function has a pivotal role to play in the most difficult discussions and decisions, helping to identify, assess and mitigate risks that threaten the viability of business models and the achievement of sustainable growth in the face of uncertainty.

Navigating healthcare costs can often be a challenge, as seen when engaging with practitioners. Typically, when a doctor prescribes drugs or recommends tests, they send their instructions to the pharmacy or laboratory, leaving both the patient and doctor unaware of the impending costs. Isn't it better if we could know the cost before it is incurred, taking advantage of various data sources at our disposal?

I experienced this issue firsthand when my wife and I were anticipating the arrival of our first child. The quotes for a simple imaging procedure varied widely among providers, with costs ranging from $100 to $800. As a professional in healthcare technology, I was equipped to untangle this ambiguity, yet it was clear the potential confusion it could cause for someone outside the field.

Experiences like these empower my profound desire to develop a healthcare system that stands not only for affordability but also for transparency and accessibility for all. Despite the geographic disparities, my unwavering vision of establishing advanced healthcare facilities in remote areas of the world holds steadfast. My aspiration is to create a system that capitalizes on data science, using historical data to mold a future where healthcare isn't a privilege but an inherent right for all. My steadfast mission is to guarantee that quality and economical healthcare services are available to every individual, regardless of their socio-economic status or geographic location.

Healthcare Challenges

The primary issues with healthcare cost predictability are rooted in the complexity of the healthcare system and the intricate nature of many contributing factors. These include:

• Lack of Transparency: Healthcare systems and billing can be very complex, making it difficult for patients to understand exact costs upfront. 
• Inconsistent Pricing: The prices of services can vary dramatically among different healthcare providers and even geographical locations, with the patient often unaware of the reason for this variation.
• Complex Billing: Medical bills can be incredibly complex and hard to decipher. They may include medical jargon, coding systems or abbreviations that a layman would not understand.
• Hidden Fees: Hidden, undisclosed or unexpected fees can be tacked onto the bill, such as facility fees or charges for additional procedures or tests, and patients aren't typically made aware of these costs up front.
• Insurance Complications: Insurance policies often involve complex terms and conditions and may not entirely cover certain services, leaving patients with unexpected out-of-pocket expenses.
• Unexpected Costs: There can be unexpected costs included in the final bill, for services like laboratory tests or additional procedures that were not initially accounted for.

See also: Using Data Science to End Surprise Billing

Technological Challenges

From a technical perspective, implementing a solution to predict healthcare costs brings a host of challenges:

• Data Integration: Integrating data from a multitude of sources, each with different data storage systems and formats, is a significant hurdle.
• Real-Time Processing: Given the dynamic nature of the healthcare industry, the system needs to process data in real time (or near real- time) to provide accurate estimates, which is technically demanding.
• Regulatory Compliance: Compliance with healthcare regulations, notably HIPAA in the U.S., is mandatory when handling patient data. Fulfilling these requirements while implementing advanced data analytics can be complex.
• Data Quality: Inconsistent, incomplete or erroneous data can impede the development of accurate predictive models. Ensuring high-quality data is challenging but essential.
• Security: Healthcare data is sensitive, making robust security measures a necessity to prevent data breaches.
• Resource -Intensive: Developing, implementing and maintaining a solution is resource-intensive, both in terms of cost and technical expertise.
• User Acceptance: The solution needs to be user-friendly and easily interpretable by non-tech users like patients and healthcare providers, which is an additional challenge in design and implementation.

See also: Insurance Models Driven by Hourly Wages

Comprehensive Solution:

To address the problem of unpredictability in healthcare costs, a comprehensive solution can be designed in the form of a Healthcare Cost Prediction Platform. This platform would integrate AI and machine learning algorithms to process and analyze huge datasets from various relevant sources. Here is a broad overview of the solution:

• Multi-Source Data Integration: The platform will integrate data from various healthcare providers, pharmacies, laboratories and insurance companies. It will use robust application programming interfaces (APIs) and data connectors to bring all this data from disparate sources into a unified environment.
• Data Standardization and Quality Control: After the data integration phase, the platform will standardize data to remove inconsistencies and attain uniformity. The integrity of the data would be ensured by regular quality checks to increase the reliability of the predictions.
• Predictive Analytics Tools: The core of the platform would consist of sophisticated AI-driven predictive analytics tools. These tools would analyze the historical data and extrapolate that into future costs, giving the patient and doctor a clear idea about the cost implications even before the treatments commence.
• Real-Time Updates: The platform would be designed to handle real-time data, allowing for cost updates as prices change at healthcare providers and insurance policies get updated.
• Security and Compliance: The entire solution would be designed with privacy and security at its core, maintaining strict compliance with regulations like HIPAA to safeguard sensitive patient information.
• User-Friendly Interface: The platform would be equipped with an easy-to-use interface, providing cost estimates and comparisons in a comprehensible format. An integrated dashboard could allow users to input their specific needs and get an accurate estimate of costs.
• Continuous Learning: The platform would be capable of learning from the previous data to improve the accuracy of its predictions over time, making it more reliable.

By implementing this Healthcare Cost Prediction Platform, we can tackle the challenge of unpredictability in healthcare costs, making healthcare more affordable and transparent for everyone.

Extreme weather across the globe—including heat, wildfires and floods—is escalating. Meanwhile, the East Coast is sinking, and only 14% of Americans have flood insurance, according to a survey commissioned by Selective and conducted by the Harris Poll. That same survey also found that the majority of Americans severely underestimate their own personal flooding risk while overestimating what their policies actually cover.

What gives?

For agents and consumers, the insurance landscape—which, by all indications, will only continue to be affected by extreme weather—is in complex, unprecedented territory. There’s no denying it: We’re all being forced to maneuver through turbulent headwinds, which is why it’s all the more important to examine the powerful forces at play. Doing so will ensure that insurance professionals and consumers alike are equipped and positioned to navigate the months and years ahead.

See also: How to Prepare for Extreme Weather

Examining the Insurance Landscape

The insurance industry remains in a hard market, and no one knows exactly when it will end. There are numerous contributing factors to the hard market—from lingering effects from the pandemic to increased interest rates and inflation, as well as broader economic uncertainty and extreme, volatile weather.

More frequent extreme weather and natural disasters inevitably lead to increased losses for insurance carriers, which compounds the challenging market. Meanwhile, late spring marks the beginning of hurricane and wildfire season, which creates problems in the short term and, depending on the severity of the season, could carry long-term implications, as well. 

In addition, many carriers are struggling to maintain adequate (and often mandated) reserve capacities. Rate increases and underwriting discipline will be at the core of insurers’ measures to carve a path forward. Until the landscape changes, these challenges will remain forces that insurers must contend with to remain competitive and profitable.

While the economy and hurricane season can’t be controlled by agents, what is within their control? What opportunities exist? 

As mentioned, only 14% of Americans have flood insurance—and, according to that same survey, two-thirds of Americans with homeowners or renters insurance incorrectly believe their current policy covers flood-related damage. Those statistics show that a laser-eyed focus on consumer awareness, education and engagement is crucial, and the key to how agents can successfully navigate the hard market and add value to their clients amid extreme weather.

Consumer Communications Amid Extreme Weather and the Hard Market

There are three key points that consumers need to know—and that insurance agents need to clearly communicate in their messaging to their customers, both current and prospective. Whether the communication is on social media, via email, over the phone or in person, these are the points to drive home with consumers: 

• Standard Policies Rarely Include Flood Protection: While millions of Americans assume that their homeowners or renters policy includes coverage for flood damage, the reality is that standard policies almost always omit flood protection. Flood insurance is typically a separate policy, obtainable through either the federally backed National Flood Insurance Program (NFIP) or the private market. 
• FEMA Flood Maps Are Not a Sufficient Guide: According to the National Association of Insurance Commissioners, approximately 25% of flood claims covered by insurance policies occur outside FEMA-designated hazard zones. While FEMA certainly serves an important role in providing resources and guidance, solely relying on FEMA flood maps will, for many homeowners and renters, pose the risk of being underinsured. And as extreme weather continues, this risk only escalates.
• Anywhere It Rains, Flood Damage Is a Threat: Flooding can occur due to various scenarios, including persistent rainfall, river and lake overflow, rapid snowmelt and even wildfires. It’s also essential for consumers to be aware that there is a 30-day waiting period for both purchasing and renewing flood insurance, and that flood protection policies can be purchased at any time—except during an actual flood. Considering the extent to which consumers are underestimating the threat of flood damage, it’s all the more important for insurance industry professionals to focus on communicating these basics, and doing so with clarity and empathy.

See also: Property Underwriting for Extreme Weather 

In addition, it’s crucial to be proactive about renewals and cultivating strong relationships with fellow industry professionals, including carriers and underwriters, who can be vital in securing that favorable policy and helping both the agent and policyholder maneuver through the hard market. For agents, that relationship-building ability combined with local expertise and access to multiple markets will go a long way to alleviate customers’ pain points. 

While the focus here has been mainly on extreme weather and flood protection specifically, much of this analysis also applies to the broader complex insurance market. Across the board, the story remains largely the same: Premiums are increasing, while many consumers remain unequipped with the knowledge and tools to adequately protect themselves, their assets and their families. 

What this all underscores: the critical and ever-increasing role of independent agents and industry professionals in helping consumers make wise decisions and successfully navigate this landscape. 

The good news, if you’re an insurance industry professional: today, is that your job is more important than ever—and as a consumer educator and advocate, you are primed to make a tangible, positive difference for policyholders, their loved ones and their financial futures.