KEY TAKEAWAYS:

--Medical record review is a classic bottleneck in the insurance process. It's labor-intensive, time-consuming and prone to human error. Early attempts at automation in insurance couldn’t handle the unstructured documents associated with claims.

--The changemaker is today’s AI workflows. They use algorithms that can read, understand and categorize data and route relevant details to people-powered checkpoints and specialized analysis (for example, a physician expert reviewing medical records previously sorted or indexed by an AI). The result is up to 70% faster claims processing, smoother workflows and more accurate results. 

--And the "paperwork revolution" is just beginning.

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Paperwork backlogs in insurance have evaded even the savviest of technology solutions. In particular, the processing of unstructured medical documents or cabinets filled with claims data was difficult to automate, so many have kept doing the work by hand.

Now, the technology landscape has changed.

AI has been getting plenty of buzz, and it’s no secret why. The rise of artificial intelligence and machine learning tools has made it possible for humans to accelerate everything from legal proceedings to test prep. However, one of the more powerful uses for AI is often overlooked: processing paperwork.

That might not be as glamorous as a robotic law firm or a self-driving car, but AI’s superhuman ability to sift through pages could well and truly change the game in claims.

More paperwork, more delays

Paperwork is tedious. In claims, it’s also unavoidable. When everything from a patient’s previous medical history to the lead-up to a claim requires documentation, the pages add up. The insurance industry is cautious by nature, so paperwork needing high attention to detail usually gets it—which can lead to time-consuming workflows and a backlog of files. 

Medical record review is a classic bottleneck in the insurance process. It's labor-intensive, time-consuming and prone to human error. Early attempts at automation within insurance, such as automated underwriting or telematics, couldn’t handle the unstructured documents associated with claims. However, relying on manual processes leads to unhappy customers and workflow delay. 

This junction between people and programs is where AI can truly transform. Combining automated workflows and expert input offers accurate results, fast. Removing the manual labor from the medical recordkeeping process isn’t just about making offices virtual (although AI can certainly help); it also means processing medical information in less time. This can do more to improve the customer and patient experience than even the best AI-powered service tools. 

Humans join the loop

The real changemaker is today’s AI workflows, which don't eliminate human brainpower. With people-powered checkpoints and specialized analysis (for example, a physician expert reviewing medical records previously sorted or indexed by an AI), processing more data doesn’t come at the cost of professional expertise. AI tools use algorithms that can read, understand and categorize data, identifying relevant details and making these details easier to retrieve. This means up to 70% faster claims processing, smoother workflows and more accurate results. 

Automatically extracting information from medical records means medical experts and claims handlers can make informed decisions fast. This not only reduces costs for providers but also results in quicker payouts for policyholders, something that could benefit both sides of the bottom line—boosting insurer revenue and lowering cost.

Unlocking the potential of AI 

The paperwork revolution is only beginning.

Today's insurance customer expects a swift, smooth experience from their provider and expects the experts involved in their file review, including physicians or legal professionals, to do a thorough and accurate job. Meeting these two needs in a reasonable amount of time necessitates technology. 

When documents can be processed, sorted, indexed and organized faster than a human can, it opens the door for the expert to pay more attention to each file. This expedites the decision-making process, improving the experience for everyone involved. 

Winning the case on claims processing

The paperwork involved in medical records review is a major hurdle in claims. With a combination of technology and expert inputs, it’s now possible to do more in less time—but what does this mean for insurance as a whole?

The entire industry can enjoy the benefits of smoother document review. Accuracy is essential in complex claims, where small details can add significant hours to a file or alter the outcome of a case. Automating the task of document sorting and indexing makes better use of expert time—so claims can be reviewed both faster and more thoroughly. 

Historically, insurers have been reluctant to move away from a manual workflow. Insurance is an industry based on details, and the complexity of the processes within it have led many organizations to delay the change. Still, there’s no better time than now.

The potential benefits of automation are significant both in terms of hours and cost. The impact AI may have on customer satisfaction could be sizeable, as insurers that can process claims faster and more accurately have a competitive advantage.

The future belongs to those who are willing to innovate—and in terms of medical record review, AI presents an opportunity for insurers to do just that.

KEY TAKEAWAYS:

--Every embedded insurance success I'm aware of satisfies all nine requirements. Otherwise, embedded insurance is like multiplying by zero. The value is nil.

--For one, if the value to the seller or partner is little more than a commission, the insurance becomes a commodity, the commission rises, the value to consumers falls and the product develops a reputation for being scammy.  

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Insurance distribution is a $72 billion market in property and casualty and $47 billion in life insurance. Even as margins have been competed out of many industries, profits in insurance distribution have remained consistent or even grown. Hence, it’s no surprise that distributing insurance is seen as an attractive business for many companies outside insurance. 

The vast majority of insurance worldwide is still distributed through traditional channels – captive agents, independent agents and banks – but many insurers are exploring omnichannel approaches based on meeting customers where they are rather than driving customers to agent channels.

Examples:

• “[We intend to] accelerate our efforts to provide customers with personalized solutions in their channel of choice” – president of personal lines at Travelers (source)
• “People buy houses on the internet, right? They buy cars on the internet. There’s really no reason why they shouldn’t buy homeowners insurance on the internet.” – CEO of Allstate (source)

Enter embedded insurance...

A newfangled term describing an ancient concept

"Embedded insurance" is a new Silicon Valley-ism. Yet embedded insurance predates the insurance agent, who is a product of the 19th century Industrial Revolution. Embedded insurance even predates insurance itself. Before insurance existed, an arrangement called bottomry embedded insurance into a marine loan: If the ship was lost at sea, the shipowner did not have to repay the loan. Hence, the interest rate for sea loans was higher than the interest rate for non-sea loans -- often usurious. Abuse of the usury exception by non-mariners led Pope Gregory IX to ban bottomry in 1236. That's when the insurance industry began to form among merchants in the Hanseatic cities, in Lombardy (Italy) and in London -- on Lombard Street, natch. So, yes, embedded insurance predates insurance itself.

In its broadest form, embedded insurance means distribution via any channel other than captive or independent agents, direct response (call centers and websites), aggregators, price comparison websites and lead generation (e.g., affiliate links). That leaves a wide range of concepts that could be embedded insurance, depending on your definition:

• Affinity marketing – selling insurance via associations, groups, etc. 
• Point-of-sale marketing – selling insurance in the flow of selling something else as an opt-in or opt-out
• Providing insurance as part of another product or service, or to people/businesses that purchase another product or service (either included in the product price or opt-in)
• Employer voluntary benefits programs
• B2B2C or distribution to consumers via other businesses

Embedded insurance has been all the rage since some direct-to-consumer start-ups encountered higher-than-expected customer acquisition costs a few years ago. Indeed, a proper embedded offering can be very beneficial for everyone involved, including the consumer. But, like everything in insurance, embedded is easier said than done.

Here are my Nine Requirements for Success in Embedded Insurance. All of the successful embedded insurance offers that I’m aware of have all nine -- or at least a darn good reason why one of the nine doesn't apply. Otherwise, missing any one of the nine is like multiplying by zero – the result is nil.  

See also: Embedded Insurance Is Everywhere

1. Solve a Problem for the Seller/Partner

Embedded insurance is typically insurance sold in the context of some other product or service or buying group. Some examples: 

• Affinity groups: Associations seeking to grow their membership might value having discounted insurance offerings to encourage members to keep paying dues.  Employers might want a shelf of quality voluntary benefits offerings to offer employees.
• Smoothing transactions: A mortgage originator, homebuilder or car dealer might value an insurance offering because their products generally require insurance before a transaction closes (especially if financed), and many consumers turn up without insurance.  
• Improving customer experience: Payroll providers often sell workers' compensation insurance in part because the payroll providers have access to critical data for pricing WC insurance -- who is paid what.
• Solving headaches: By giving customers protection against risks, embedding insurance into a product or service can reduce the potential for customer complaints that damage brands, stress out workers and result in demands for refunds. Think of cruise lines or ski operators embedding accident insurance in their sales processes, so customers have a means of getting a refund if their holiday is spoiled.
• Meeting unique needs: Professional associations sometimes sell their “own” insurance that allows their members substantial control over claims settlements, which can be important for professionals who want to fight bogus claims to protect their reputations, even if the economic cost alone might not justify the fight.

If the value to the seller or partner is little more than a commission, the insurance becomes a commodity, the commission rises, the value to consumers falls (less $$ to pay claims) and the product develops a reputation for being scammy. 

2. Customer purchase occasion

Insurance is a low-interest product, so it’s hard to mobilize consumers to go out and buy it. Hence, an embedded offer needs a purchase occasion for some other product/service where insurance can naturally and easily be attached or inserted. This works where products are simple but becomes challenging in packaged/bundled products and in commercial insurance, where the agent or broker’s consultative role is not easily embedded into a transaction.

3. Unobtrusive insertion point

Embedded insurance cannot be allowed to distract a customer from buying whatever else they intend to buy, lest the insurance become a friction rather than a solution. Thus, underwriting questions must be few, which often means using third party data to customize and underwrite or simplifying the product to a “one size fits most” offer. 

4. Access to unique and relevant data

At the very least, the customer’s identity and basic facts about the consumer or the underlying risk should be known. Ideally, information relevant for rating or product design should be known and provided seamlessly to the underwriter (with appropriate permissions) by the embedded provider. Examples:

• Payroll platforms have information on every employee, their pay and their job – all of which are critical for writing workers' compensation insurance. 
• A gig economy platform might have telematics information on drivers and driver ratings, which could be useful in writing motor insurance.
• For homeowners insurance, a homebuilder should know quite a lot about the homes it builds and the people they sell to, making for a smooth application process and eliminating frictions such as inspections.

However, new data can be friction. Data take effort to be gathered, permissions may be required and ratings algorithms might need to be adjusted. The value of the new data needs to exceed the frictional cost of gathering and processing the data.

5. Breadth of product

Embedded partners want all or most of their customers to get a competitive offer for insurance. This presents two issues for insurers that want to distribute via embedded channels.

(A) Broad and competitive risk appetite. This is somewhat in conflict with the "risk selection" capabilities that every good underwriter has spent years honing. Rejecting a customer or providing an uncompetitive price reflects poorly on the embedded partner. 

(B) Broad licenses. No embedded partner outside insurance cares that U.S. insurance is 57 different state/territory markets, each with its own rules around product design, seasoning and rate filings.

An embedded offer is valuable only to the extent it can serve a large number of customers. 

6. Adjustments to product design, ratings and filings

A smooth integration with an embedded partner is table stakes, but the partner probably also wants unique product features or discounts. Forms may need to be adjusted to reflect a new/different distribution process. Data provided to the underwriter by the partner also have to be considered in ratings. Underwriting rules might need to be flexed to reflect different characteristics of customers that come via partners rather than agents. In admitted insurance, new filings might be required, which can require separate approvals of up to 57 regulators. 

A different type of customer might be attracted by the embedded offer compared with traditional channels. Are they the desired customers or not? How do they react to pricing, coverage options being presented and the design of forms?

7. People who can design, build, underwrite and sell

A person with all four skills is a unicorn! The general manager of an embedded partnership needs to be as close to a polymath as is ever found in insurance, a business that I've argued overvalues specialism. Think of the skills needed in a manager of an integration of car insurance with a car seller. The leader needs to be fluent in both insurance and car selling, including their respective customer journeys, sales processes and IT systems. They need to be fluent in designing a solution, building that solution, underwriting the insurance and selling/negotiating with a partner. Not to mention dealing with all the requirements that I’m writing about here. Try doing that at scale.

See also: A New Approach to Embedded Insurance

8. Reasonable split of the economics

One of the biggest challenges in embedded insurance is the embedded partner demanding too much commission. Take travel insurance. In extreme cases, travel providers take 75% or more of the premium when selling travel insurance, leaving little to do what the product is supposed to do – pay claims to consumers. With so much money to be made in distribution, some travel providers aggressively sell insurance, and few customers actually buy it. That’s a shame, because travel insurance can be an excellent product. But too often the product is attenuated as insurers compete for embedded distribution and pay distributors handsomely. 

9. Enough volume to cover fixed costs

With all the difficulty and complexity of making a successful embedded product, a slick embedded offering might be really cool in a Silicon Valley sense, but it’s only viable if it scales. The required scale depends on the fixed costs each party incurs and the gross margins they generate from the partnership. Often, the minimum efficient scale is higher than the parties realize or takes longer to achieve than the parties have patience for.

***

The insurance industry is moving toward omnichannel distribution, where products are made available in the consumer’s channel of choice rather than requiring the consumer to go through the insurer’s channel of choice. But there are strong reasons why agents came to dominate distribution of insurance globally starting in the mid-1800s – notably their ability to provide specialist expertise, geographic reach, consultative services and a variable cost structure. 

Embedded insurance is surely part of the future of insurance, just as it has been part of the past for millennia. But, as with everything in insurance, embedded insurance isn’t as easy as it might look. Those who figure it out will have a piece of a $120 billion market for insurance distribution (just in the U.S.).

***

Disclaimer

The views expressed are the author's views as of the date of publication and may not consider material economic, market, regulatory and other factors. Certain information has been obtained from sources believed to be accurate and reliable – any of which may be erroneous or change without notice. HSCM has no obligation to update or advise you of any changes or errors. There can be no guarantee that any prediction, projection, forecast, or opinion will be realized. Certain information discusses general information related to the specific industry, activities and trends, or other broad-based economic, market or other conditions and should not be construed as research. The information contained herein does not constitute an offer to buy or sell, or a promotion or recommendation of, any financial instrument or product or strategy. The views expressed may change at any time subsequent to the date of issue hereof. 

KEY TAKEAWAY:

--AI can help brokers improve efficiency, customer service and risk management, creating a competitive advantage.

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Artificial intelligence is well on its way to becoming the number one game-changer in insurance. The key will be learning how to use it to maximize efficiency and assist with time-consuming tasks to free industry experts to focus on the areas where they can make the biggest impact—building meaningful client relationships and providing personalized service to exceed the expectations of their clients.

According to McKinsey, “AI and its related technologies will have a seismic impact on all aspects of the insurance industry.” With the rapid pace of technological change, some insurance brokerage firms will inevitably find it difficult to keep up. They will lose ground to competitors that embrace it. 

Some insurance brokers may be concerned that technology will replace them due to the increasing use of AI in underwriting, claims management and customer service. Instead, they should realize how they can use AI to support their growth. Focusing on what it means to be a broker and which activities can only be done by humans is essential, as is understanding how AI-powered tools can absolve them from the mundane, repetitive tasks that take them away from what they should focus on.

Commercial brokers' responsibilities extend beyond transactional duties. They have industry knowledge and the ability to establish trustworthy relationships. AI will not be able to replicate their strategic thinking, negotiating abilities and unique approach, making them essential for navigating complex business transactions.

A valuable partner

AI provides commercial insurance brokers with data-driven insights, streamlines operational processes and helps automate mundane tasks. By adopting such tools and digital platforms, brokers can obtain a competitive advantage, enhance their efficiency and customer service and mitigate their E&O risk. In a nutshell, technology can help brokers thrive in an industry that is rapidly transforming.  

See also: Why AI-Assisted Selling Is the Future

AI supports:

Improved Customer Experience

The most effective use of AI in insurance companies, according to a 2021 PwC survey, is in delivering a more positive customer experience. AI enables brokers to provide faster and more accurate responses to customer inquiries. Additionally, AI-powered analytics help brokers understand their clients' needs and preferences, allowing them to tailor their services accordingly.

Better Risk Management

AI also helps brokers better assess and manage risks. AI can analyze vast amounts of data and identify patterns and trends that humans are not able to see, allowing brokers to make more informed decisions. Additionally, AI helps brokers identify potential fraud and other risks, so they can take steps to avoid them.

Competitive Advantage

Ultimately, by embracing AI, brokers gain a competitive advantage over peers that are slow to adopt the technology. Customers expect highly personalized experiences, and brokers that are tech-savvy can deliver on those expectations faster and more easily and are better-positioned to attract and retain clients.

According to one Deloitte study, only 1.3% of insurance companies are investing in AI. But according to Next Move Strategy Consulting, AI use is expected to grow twentyfold by 2030. 

Fifty-two percent of companies accelerated their AI adoption plans because of the COVID crisis, a study by PwC found. Nearly 86% said AI was becoming a “mainstream technology” at their company.  

See also: Technology and the Agent of the Future

It is the era of digital transformation in insurance. With AI moving full steam ahead, insurance brokers can realize real value from its adoption. They should not shy away but rather embrace it as a tool to improve efficiency, customer service and risk management, creating competitive advantage.

Fear of the unknown is human nature—but there’s no need for fear. Early adopters have a lot to gain, whereas laggards may find it tough to catch up. So, while AI may change the role of brokers in the insurance industry, it will not replace them. Rather, it will allow brokers to focus on higher-value tasks, provide better service to their clients, and build more business than they ever thought imaginable.

The 2023 Atlantic hurricane season officially started June 1 and is forecast to be a busy one, which is why homeowners need to prepare. Yet many lack even the most basic preventative measures, unaware of the risks they face, according to a new survey by Triple-I, in coordination with Munich Re.

The new report, Homeowners Perception of Weather Risks, provides insights into trends, behavior and how experiencing a weather event affects consumer perceptions of future events. 

In the first half of 2023, Triple-I, in coordination with Munich Re, asked homeowners across the U.S. about their experiences with weather-related risks.  Among the key findings:

• Twenty-five percent of respondents don’t expect to be affected by weather risks.
• Thirty-two percent report that they have been affected by weather in the last five years.
• Two primary ways to prepare for weather risk are: creating a home inventory and preparing an evacuation plan in case of emergency. Yet only 47% of respondents have a home inventory and just 52% have an evacuation plan.
• Thunderstorms are reported as the chief weather concern, with 54% citing it nationally. This concern includes flooding and tornados and varies by geographic region. The Midwest leads the area of highest reported thunderstorm risk, with 75% citing it, and the West reports the lowest proportion of concern, at 33%.

The survey suggests awareness and education around flood risk are the greatest opportunity for getting homeowners to take the necessary steps to protect their property. For example, while just 22% of respondents reported understanding their flood risk, 78% of those respondents said they had purchased flood insurance. 

You can find the full Triple-I report here.

KEY TAKEAWAYS:

--San Jose, California, will be a test case. It began requiring liability insurance for gun owners on Jan. 1, 2023.

--It remains to be seen whether gun ownership liability will become the next frontier for insurance companies — though if it does, it could become a big business.

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Regardless of where one stands on gun control, it’s no secret that gun violence is a prominent issue in the U.S. — one many agree is worth making policy changes to solve. In fact, some 95% of Americans support some form of restriction on firearm access, according to an April 2023 ValuePenguin survey.

But there could be another way to minimize the threat of gun violence — one that’s compatible with the right to bear arms.

According to that same survey, 75% of Americans believe that liability insurance should be required for gun owners. If such a policy were to be widely enacted, future firearm regulation could end up, at least in part, in the hands of insurance companies.

In fact, this policy is already being tested in one American city.

San Jose passes first U.S. law mandating gun liability insurance

Last year, San Jose, California became the first American city to mandate liability insurance for gun owners. The Gun Harm Reduction Act, which also requires owners of firearms to pay an annual gun harm reduction fee, went into effect on Jan. 1, 2023.

Along with providing coverage for losses, medical costs and deaths due to an accidental use of a firearm — such as a child accessing a gun and unintentionally shooting someone — the liability insurance requirement could encourage gun owners to be more thoughtful about the security of their guns' handling and storage.

Insurance companies often reward safe behavior. For instance, a homeowner might get a discount for installing smoke and carbon monoxide detectors or buying homes closer to fire stations. Car insurance companies also use a driver’s history of accidents and traffic violations, including personal safety measures like seat belt laws, when calculating rates.

In a similar way, gun owners might be given incentives to take a gun safety class or ensure their firearm is kept in a safe. After all, if the gun is lost or stolen, the owner would still be held liable for any damage it caused until they reported the weapon missing.

Gun owners in San Jose who fail to comply with the act will not lose their guns or even be faced with criminal charges. They may, however, face steep fines for their choice to forgo insurance: the penalty starts at $250 for your first violation. If you receive a second violation within a year, the fee jumps to $500. After that, you’ll pay $1,000 every time you receive a violation within a year from your first offense. 

See also: Keys to Limiting Litigation Liability

Could liability insurance prevent gun violence?

The measure is part of a broader movement toward stricter gun control laws in majority-Democrat cities. But detractors say the act may not deter the most common and disturbing type of shooting events in America: intentional ones. 

Liability insurance only covers accidental damages. And in the vast majority of firearm-related injuries and deaths, the shooter was acting with intent, even if that intent was self-defense.

According to the Educational Fund to Stop Gun Violence, unintentional shootings (the kind liability insurance would apply to) account for less than 2% of all gun deaths. Of course, those deaths are still tragic, especially when accidentally inflicted by unwitting children who gain access to firearms stored unsafely. (Everytown Research keeps an index of unintentional  shootings by children; at the time of this writing, there have been 114 of them in 2023 thus far.)

Additionally, many gun owners already have liability insurance coverage for accidental firearms-related damages through their homeowners insurance policy.

Time will tell whether the measure will have an effect on the overall rate of gun violence in San Jose and, thus, whether such a policy stands to help ameliorate the problem in other parts of the country.

Insurance or no, most Americans support gun restrictions

Liability insurance mandates are only one tool in the effort to minimize gun violence, but most Americans agree that some sort of restriction is called for.

Of those surveyed, most support gun restrictions based on documented mental health issues (73%) and criminal history (70%).

Most respondents also supported limitations based on age, proof of gun safety training and proof of safe storage, along with proof of gun ownership liability insurance. Some 41% also supported requiring gun ownership permits, while only 5% of Americans think there should be no restrictions on gun ownership whatsoever.

It remains to be seen whether gun ownership liability will become the next frontier for insurance companies — though if it does, it could become a big business. Almost half of respondents say such insurance should be purchased on a per-gun basis. Although the average gun owner might have just one or two firearms, there’s a not-insignificant class of “super-owners” who own more than a dozen. That’s a whole lot of opportunity for insurers — and, we can hope, a whole lot less needless violence.

My 93-year-old mother was taken by ambulance to the emergency room last Tuesday in the middle of the night, with acute pneumonia, and died Friday afternoon. 

I tell you that partly to explain why I'm being so brief this week and partly to allow me to make a quick point about how much crazy complexity our healthcare system has added in the U.S. We've all become worn down by the cost and complexity, like the proverbial frog in the water that's being brought to a boil, but the issues grab you by the nosehairs when, for instance, you're helping your siblings clean out your mother's apartment and find statements from earlier encounters with the healthcare system.

While I haven't yet seen the bill for my mother's final trip to the hospital, I can imagine what an ambulance ride, a visit to the emergency room and three days in an ICU cost. The bill will be many thousands of dollars, perhaps tens of thousands (covered by insurance, but still...). 

By contrast, what was the bill when she broke her leg skiing in 1955? The break was severe enough that she required an operation and spent a night in the hospital. So, the bill mounted all the way up to $46.60.

The telegram she sent my father cost almost as much as the charge for use of an operating room ($3).

How about the bill from 1967, when my sister Katy was born in the same hospital where my mom died? It was a difficult birth, so my mom and sister spent six nights in the hospital. The entire bill came to $419.75.

I'm not dinging the quality of care by any means. The folks at St. Clair Hospital in suburban Pittsburgh were great, to a person, and my mom felt loved and supported as she left this world behind. She died with her intellect and personality intact and had recently spent a great deal of time with her eight kids, her 17 grandchildren and her three great-grandchildren, including at the weddings of two of the grandkids. She just wore out after a series of health problems. Sign me up for that sort of exit when my time comes.

There is just such a stark contrast between my experience of healthcare today and what I saw in those old bills. The one from 1955 was just a page torn from a notepad, on which someone had used a typewriter to check boxes and to add the dollar amounts (the very small dollar amounts). By 1967, the hospital was using a computer, but the bill was almost as simple as the earlier one. Neither showed any of the elaborate coding that comes with today's bills, as hospitals employ small armies of professionals to make sure they maximize what the insurer and patient will pay -- this, even though I'm sure insurance covered those earlier bills, as my mom worked for United Airlines in 1955 and my dad worked at Westinghouse in 1967. 

I'm not proposing a solution, at least not today. Today, I'm just passing along what I hope was some intriguing historical perspective from the meticulous files my mom kept -- and to maybe rant a little.

My mom's name was Yvonne, by the way. She lived a long and splendid life. Rest in peace, Mom.

Cheers,

Paul

KEY TAKEAWAY:

--Innovation goals cannot be achieved with traditional, repetitive, paper-based processes. Insurers need to take five technology-based steps to accelerate innovation.

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Insurers, globally, are on the proverbial edge of disruption as they are constantly facing challenges due to changing customer needs, increased customers' expectations, heightened competition from insurtech firms and increasing regulatory requirements. Now, customers want to be onboarded not in days but in minutes. They are no longer willing to wait for weeks and months to settle claims. The pressure on insurance carriers and adjustors is mounting to accelerate product innovation. Maintaining the status quo is not going to work. 

They need to launch innovative products faster, transform the underwriting process, improve policy administration, speed claims processing and enhance risk compliance. These business goals cannot be achieved with traditional, repetitive, paper-based processes. 

Considering the well-known inertia of insurance companies and propensity to be slow about technology adoption, how can they fast-track innovation in the top gear and speed up go-to-market strategies?  

1. Accelerate time to market by partnering with technology services providers

Most insurance carriers don't have enough tech capability, but they can forge partnerships to capitalize on other firms' expertise in new-age technologies to expedite product innovation. For instance, such collaborations can be established with insurtech service providers to create fit-for-purpose customized solutions based on unique business requirements.

2. Adopt Advanced Products to Automate Processes

Insurers can take advantage of advanced technology platforms to develop fit-for-purpose products and bring them to market quickly.

With advanced policy management systems, insurers can automate time-consuming tasks such as underwriting and issuance. Brokers can develop feature-rich software for end-to-end policy management, client services, underwriting, claims processing and more. A customizable self-service portal can be developed to let brokers, intermediaries and agents automate receiving customer requests, creating quotes, guiding prospects/customers and selling policies. 

See also: From Vision to Product (Part 1)

3. Leverage Platform Development Accelerators 

Platform accelerators can fast-track innovation by enabling insurers to leverage pre-built functionalities, integrations and modernization capabilities. These accelerators also can provide consulting on products, on platform development and enhancement, on integration with other enterprise and third-party applications and on comprehensive implementation and support.

4. Take Advantage of New-Age Tech Services 

An adjustor client of ours used optical character recognition (OCR), machine learning (ML) and technologies such as Pytorch and Fast AI to correct a problem with bad data they were getting from surveyors and to quickly generate accurate reports on property damage. The company is now settling claims faster and generally providing better service.

Other tech services to take advantage of include:

Cloud

Migrating to the cloud offers a significant advantage over traditional environments in terms of the speed with which new capabilities, business features and products can be developed, tested and launched. Using application programming interfaces (APIs), insurers can quickly connect their systems with third-party providers, enabling them to access new functionality and data. Insurers can also easily host insurance platforms, facilitating the deployment of cloud-native applications.

Low Code

Low-code development services can allow insurers to rapidly build, test and deploy new products in underwriting, claims management and claims processing and policy management systems. Even small insurance companies can innovate faster with low code.  

Robotic Process Automation (RPA)

RPA can automate repetitive and rule-based tasks, such as data entry, validation and policy administration, minimizing manual errors and freeing employees to focus on essential tasks. RPA also improves process efficiency and accuracy, leading to faster product development and a more streamlined customer experience.  

5. Adopt Digital Modernization 

In the traditional insurance model, launching a product is very difficult. Insurers have to invest significant time and resources into designing the policy, as evaluating underwriting risks and deciding premiums may take considerable time. However, if the insurer has migrated to the cloud, they can leverage the power of data analytics and machine learning and automate the entire underwriting and pricing aspect. As a result, an insurer can cater to fast-changing consumer needs. 

The Crux

Factors such as regulation and product complexity have made insurers slow to innovate. However, technological advancements have reduced the barriers to entry, so insurers must step up their game on product innovation to retain their competitive edge and grow business. 

KEY TAKEAWAYS:

--Being data-driven is becoming more difficult because of the sheer volume and complexity of the data being generated. Data privacy concerns also complicate matters, as does the potential for bias in AI models.

--Organizations can take four steps to overcome the obstacles and tap into the benefits of an intense relationship with their data.

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With AI's potential to dramatically change how businesses operate and make decisions, becoming data-driven has never been more important. However, as technology advances and the world becomes increasingly connected, organizations are finding it more and more difficult to become truly data-driven. Organizations are collecting more and more data from consumers, but the processing and harnessing of this data stays limited.

Let’s explore some of the key challenges that organizations face in the age of AI and discuss potential solutions.

Challenge 1: Data Volume and Complexity

One of the main reasons that becoming data-driven is becoming more difficult is the sheer volume and complexity of data being generated. With the rise of IoT devices, social media and digital transactions, it’s estimated that by 2025, 175 zettabytes of data will be created annually. This exponential growth in data has made it increasingly difficult for organizations to process, analyze and draw insights from their data.

Moreover, the complexity of data has also increased. Unlike traditional structured data, which can be easily stored and analyzed in relational databases, the majority of the data generated today is unstructured or semi-structured. This includes data from social media, images, videos and natural language text. Processing and analyzing this type of data requires advanced techniques, such as machine learning and natural language processing (NLP), which can be resource-intensive and require specialized skills.

Challenge 2: Data Privacy and Security

Data privacy and security concerns have also grown in the age of AI. With data breaches and cyberattacks on the rise, organizations must navigate a complex landscape of regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), to protect their customers’ data. These regulations impose strict requirements on how organizations collect, store and process personal data, adding complexity to becoming data-driven.

Moreover, as AI models become more sophisticated, they can inadvertently learn and reveal sensitive information about individuals. For example, machine learning models trained on large datasets have been found to memorize and leak details about individuals, such as their medical records or credit card numbers. As a result, organizations must be cautious when using AI to analyze their data and take steps to ensure that they protect sensitive information.

Challenge 3: Data Bias and Fairness

Another challenge is ensuring that data and models are free from bias and promote fairness. AI models learn from data, and if the data used to train these models is biased, the resulting predictions can also be biased. This can lead to unfair treatment of certain groups, such as when AI is used in hiring, lending or medical diagnosis.

Addressing data bias and ensuring fairness requires organizations to carefully curate their data, develop techniques to detect biases and apply methods to mitigate these biases. This process can be time-consuming and requires a deep understanding of both the data and the domain in which the AI model will be applied.

See also: Achieving a 'Logical Data Fabric'

Potential Solutions

Despite these challenges, organizations can still become data-driven in the age of AI. Some potential solutions include:

1. Investing in Data Infrastructure and Tools: By investing in scalable data infrastructure and tools, organizations can better manage and process the growing volume and complexity of data. This includes investing in cloud-based services, data and advanced analytics platforms that can handle both structured and unstructured data.
2. Fostering a Data-Driven Culture: Encouraging a data-driven culture can help to overcome some of the challenges associated with becoming data-driven in the age of AI. This involves promoting data literacy, providing training and education on data and AI, and encouraging collaboration among data scientists, domain experts and decision-makers.
3. Implementing Robust Data Governance: Establishing a robust data governance framework can help organizations tackle data privacy and security challenges. This includes implementing data encryption, access controls and regular audits to ensure compliance with data protection regulations.
4. Developing Ethical AI Guidelines: To address the challenges of data bias and fairness, organizations should develop ethical AI guidelines and best practices. This can include investing in research to detect and mitigate biases in AI models, incorporating fairness metrics into model evaluations and developing diverse and inclusive datasets.

Becoming data-driven in the age of AI presents a unique set of challenges. However, by investing in data infrastructure, fostering a data-driven culture, implementing robust data governance and addressing ethical considerations, organizations can navigate these challenges and harness the full potential of AI.

KEY TAKEAWAYS:

--IoT sensors can accurately forecast not only the likelihood of a flood event, but more importantly identify exactly which buildings or facilities will be affected. A combination of flood forecasts, nowcasts and real-time IoT data can let companies act before or during a flood event to mitigate the impact.

--The spread of IoT technology will likely increase the use of parametric insurance, with payments triggered by precise data from IoT sensors.

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Rising risks from flooding in every part of the U.S. will require an innovative response from insurers and risks managers, and the Internet of Things (IoT) is set to become key to how risks will be managed and mitigated.

Flood data facts 

Today, half of all U.S. economic losses from flood are due to pluvial flooding (Nature.com 2022). At the same time, current flash flood warnings lack actionable data, as they cover large geographies, which generate many false alarms, with a resultant lack of action. In addition, a threefold increase in damage to commercial property from climate-related risk is now predicted by risk analysts XDI 1000 by 2050. 

A recent study by the Pew Charitable Trusts found flooding in the U.S. is a year-round threat. (Flooding Is Nearly a Daily Occurrence Throughout the U.S.)

While flooding from large-scale extreme weather events such as hurricanes tends to grab headlines, they are only part of the nation’s flood story. The Trusts analyzed storm data and other events, including heavy rains and rapid snow and ice melt, which now cause varying degrees of flooding across the country, often inundating homes and businesses, compromising infrastructure and impairing local economies.

Pew’s analysis of the National Oceanic and Atmospheric Administration’s Storm Events Database, which includes reports from a variety of government and nongovernment sources, found that, since 2000, at least one flood occurred in the U.S. on nearly 300 days per year, on average. The NOAA database also shows that all 50 states and the District of Columbia were affected by flooding in 2021. 

See also: The New IoT Wave: Small Commercial

The knock-on effect

The flooding has led to a more cautious approach from underwriters to the coverage they offer, which has been made all the more difficult by reinsurers’ reluctance to provide capacity for natural catastrophe risks in the 1/1 and 1/4 renewals. Primary markets have had to raise their attachment points significantly, assuming more of the risks themselves. 

They are becoming far more deliberate in how they deploy capacity that is, in effect, unsupported. Those concerns are passed down to the policyholder in the shape of higher deductibles, lower limits and higher premiums.

As a result, we are seeing a tangible shift in focus away from simply post-event restoration and recovery to a system of robust risk management with prevention and mitigation pre-event at its heart.

IoT is the answer

To deliver such a strategy early identification will be key, and technology can and will play a significant role.

Policyholders, be they personal homeowners or businesses, need to be able to identify the threat of flooding before the event so they can put in place flood mitigation systems to reduce damage and loss of property.

For business, the ability to reduce the losses and the impact can be the difference between success and failure -- over 40% of businesses fail to reopen after suffering a flood event. And IoT sensors can accurately forecast not only the likelihood of a flood event, but more importantly identify exactly which buildings or facilities will be affected. A combination of flood forecasts, nowcasts and real-time IoT data can provide insights into flood risk, letting companies act before or during a flood event to mitigate the impact.

See also: The Intersection of IoT and Ecosystems

Plugging the protection gap

Insurers will be able to redesign how they can offer insurance cover, likely using more parametric products. Because parametric covers require the ability to access unequivocal independent data on which the payment can be triggered, it is where IoT sensors that can measure the height of water at a given point come into their own.

For businesses that have had challenges settling past flood claims, parametric insurance, backed by highly accurate IoT sensors, offers greater certainty about when and how claims are paid. 

It will even allow insurers to better understand their clients’ individual risk and offer parametric coverage where conventional insurance isn’t viable, while delivering accuracy in underwriting product structure and pricing.

All in all, IoT sensors enable insurers to work with their clients to mitigate and manage flood risks better, which should consequently help reduce the number of businesses for which a flood event spells failure, especially in hardening economic and financing conditions

KEY TAKEAWAYS:

--When a patient attempts to register online for the first time, they should be asked to capture a government-issued ID through their computer webcam or mobile device. The registrant should then be instructed to take a live selfie, which ensures that the person listed on the ID is the same as the person trying to open the account.

--After an account has been opened, medical offices and pharmacies can approve future treatment and prescription requests simply by requesting a new selfie of the patient.

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Being a chief information security officer (CISO) in today’s healthcare environment is increasingly challenging. The modern threat landscape forces healthcare CISOs to protect not only against malware and ransomware attacks but also to defend against more traditional vulnerabilities in legacy equipment. 

Between the headlines discussing ransomware groups and organized cybercrime, organizations may not have fraud prevention squarely on their radars. They should. Fraud costs the U.S. healthcare industry more than $50 billion annually, according to data from the National Health Care Anti-Fraud Association. 

Identity theft is at the root of the industry’s insurance fraud problems. When someone’s identity gets compromised, malicious actors can use that patient’s information to make fraudulent claims with providers. This not only harms the patient but also the healthcare organizations left to deal with the phony claims. 

To help combat this issue, healthcare can borrow countermeasures from the finance industry. The financial sector has turned to the Know Your Customer (KYC) process to verify the identity of their clients and help prevent financial crime. Similarly, healthcare providers can adopt Know Your Patient (KYP) processes to address the rising threat of insurance fraud. 

Knowing your patients

In the world of finance, the KYC process is a central component of the modern regulatory environment. KYC helps institutions verify their clients’ identities and ensure they are not being used in any money laundering activities. In confirming the client’s identity at the beginning of the customer journey — when that customer first attempts to open a bank account — organizations are able to keep malicious actors from gaining entry to their systems in the first place. 

The KYP process functions similarly in healthcare. KYP is designed to help eliminate fraud risk at the front of the patient experience by strengthening the onboarding process and verifying at the beginning of the journey that someone is who they claim to be. 

Considering the rate at which the healthcare industry is falling victim to fraud, now marks a good time for organizations to reevaluate their security protocols and explore the adoption of a KYP program. 

See also: How Synthetic Data Aids in Healthcare

Developing the program

Establishing an effective KYP program consists of a few key components in tandem with a continuing authentication process. Organizations must remember that identity verification cannot be a one-time event and necessitates a more elaborate approach. 

To begin the process, organizations need to verify that a patient matches up with their government-issued ID. When a patient attempts to register online for the first time, they will be asked to capture their ID (such as their driver’s license, passport or other form of ID) through their computer webcam or mobile device. The registrant will then be instructed to take a live selfie, which ensures that the person listed on the ID is the same as the person trying to open the account. The biometric template created at this step will be useful for future authentication.

Once the ID and selfie have been collected, organizations will need to determine whether the provided ID is legitimate and if the selfie matches the picture on the ID. 

There are a handful of warning signs that may indicate a particular ID is fraudulent or being misused. Fraud detection analytics can reveal if an individual has any potential history with, or active connections to, fraudulent activity. Additionally, minimum age requirements may affect a registrant’s ability to open an account. 

Depending on the outcome of these various checks on the government-issued ID and the biometrics of the individual, the KYP program will provide a verdict for the organization to permit or deny the registrant’s new account. If the patient’s ID correlates with the biometric results, the process is complete and the account will be opened. 

After an account has been opened, medical offices and pharmacies can approve future treatment and prescription requests simply by requesting a new selfie of the patient. With each selfie taken, a new biometric template is generated for comparison with the template that was initially captured at enrollment to authenticate the returning patient.  

See also: Why to Customize Employee Healthcare Plans

Building a stronger future

It can be difficult for modern healthcare organizations to strike the right balance when it comes to fraud deterrence. They want to make the identity verification process seamless while deterring fraud and reducing friction for actual patients who are merely attempting to seek care. 

A sophisticated KYP program is intended to help organizations find that balance by letting in the legitimate patients and simultaneously keeping fraudsters out. By employing identity verification and authentication, providers can quickly confirm real patients, adhere to regulations and help thwart costly instances of insurance fraud.