In the first talk I gave to an insurance audience, some nine years ago, I projected out a decade and confidently declared, "He who sells the least insurance wins." As a newcomer to the insurance world at that point, I believed that no one WANTED to buy insurance. People bought insurance grudgingly, because it filled a need or, in many cases, because they were required to. I believed that what people did want to buy was protection, and, as someone with a long background in innovation and in writing about digital technology, I believed that insurers could use their vast stores of data and hard-earned expertise to reduce the risks people faced -- and make a lot of money doing so -- rather than wait for a loss to occur and then make people whole. 

What's become known as "predict and prevent," as opposed to the traditional "repair and replace" model for insurers, was hardly original with me, and I'm just one of many who have increasingly leaned into the model. But I'm struck by a recent confluence of events. The Institutes is developing a podcast series on "predict and prevent," in which CEO Pete Miller will interview thought leaders on the topic. (You'll be hearing much more about this from me shortly, as well as from other arms of The Institutes.) And annual reports on the industry from both Bain and McKinsey in the past week have singled out "predict and prevent" as a major theme for 2023. 

As Sherlock Holmes would say, "The game is afoot."

I'll have to wait until it is launched to provide details on the podcast series at The Institutes, which is being honchoed by ITL's old friend Paul Winston, by Matthew Kahn of the Risk & Insurance Group and, of course, by Pete Miller. In the meantime, I'll steer you toward some smart reading on the subject, including the Bain and McKinsey reports.

For the Bain report, the firm surveyed nearly 30,000 customers in 14 countries and found, according to a summary, that consumers "overwhelmingly want risk prevention and mitigation services from their insurers. In Brazil, 97% of survey respondents indicated interest in risk prevention, as well as 81% of respondents from Japan. Additionally, more than 40% of millennials are willing and interested in paying for life insurance that includes risk prevention."

The McKinsey report says, "Commercial carriers must expand their offerings beyond risk transfer to services that mitigate or prevent risks. For example, in cyber, the most engaged commercial carriers help clients reduce cyber threats and improve risk selection by providing threat intelligence, data center diversification, consulting, and employee training. Many commercial carriers also partner with cybersecurity firms to offer end-point protection or multifactor authentication. Insurtechs, in particular, can leverage this opportunity to offer cyber protection products as a 'vaccine' against risks—in other words, the more that individual companies protect against cyber risks, the lower the risk exposure for the industry as a whole....

"Similar mitigation and prevention solutions can help clients become more resilient to NatCat risks. For example, leading commercial carriers have been working with governments and regulators to ensure that building codes are fit for purpose and adequately address local catastrophe risks. In addition, commercial carriers can help manage clients’ exposure by providing extreme weather warnings (such as for floods or hail) or by advising large fleet owners (such as marine and aviation clients) to relocate their fleets based on upcoming extreme weather events. Commercial carriers can also leverage their expertise to help clients develop supply chain resilience or navigate the jungle of environmental, social, and governance (ESG) and enterprise risk management (ERM) frameworks, as well as supplier certificates."

(The McKinsey report includes a number of other striking observations, including about how much specialist carriers have outperformed their more diversified peers and about the opportunities being created by the transition to net-zero. I give the report a hard read every year.)

Beyond the Bain and McKinsey reports, I recommend an interview I did late last year with Sean Ringsted, an executive vice president at Chubb, who has been a driver of "predict and prevent" for some time. Among other smart things, he said: 

"You can go beyond the 'repair and replace' model for insurance and get to 'predict and prevent' because you have so much information available to you in real time, not just after the fact. When you think about fire, everybody knows the value of smoke alarms. Now think about water. You can use sensors to detect and manage water leaks in the same way. And they’re a major contributor of loss rate in buildings, both in frequency and in severity. It’s not just the cost, either. It’s all the headaches that go along with water damage that can be prevented. You don’t have to get new carpet, worry about mold, deal with the loss of business income. The value proposition is much less about claim payment and is much more service-driven, to prevent the loss.

"You're starting to see applications for worksites. IoT devices can improve safety for workers on degree of bend and lifting heavy objects. Think about sensitive or valuable machinery that you can monitor for temperature and vibration and make sure they’re well-functioning.

"Just the ability to monitor temperature fluctuations and humidity can have a significant bearing on the value of something such as marine cargo or fine art."

If you've stuck with me this far, you might also be interested in a "future history" of insurance that I wrote a year and a half ago for Six Things, where I laid out a vision for where "predict and prevent" could take us by the end of the decade.

I may have been too optimistic nine years ago about how quickly we could get to "predict and prevent." I'm usually too optimistic, even though I allow for the fact that I'm too optimistic. But I'm excited to see the progress.

Cheers, 

Paul

P.S. Yes, I know that the line, "the game is afoot," originated with Shakespeare, not Arthur Conan Doyle, but a lot more people have read Sherlock Holmes stories than have read Henry IV, Part 1, and even more have seen the various TV series and movies where Holmes used the line. 

The insurance sector frees businesses and individuals to conduct their day-to-day tasks without constantly worrying about risks they might encounter, enabling growth for organizations as well as the economy at large. 

But, while being protected by insurance provides peace of mind to numerous individuals and businesses, insurance companies themselves are at increased risk of fraud. According to the Association of British Insurers (ABI), detected fraud comes to over £1 billion in costs yearly, with undetected fraud adding a further £2 billion in the U.K. alone. 

Online threats are becoming increasingly prominent, to the point where £4 million is lost to fraud daily just in the U.K., jeopardizing the entire economy. Learning about online risks and how to protect from them is no longer an option but a priority, especially for insurance companies.

Annual Losses of Over $300 Billion

As more companies embrace digital transformation and transfer their operations online, the frequency of cyber attacks will only rise. While financial institutions such as banks and fintechs are more likely to be targeted, insurance companies are also high on the list as insurance fraud is steadily becoming one of America’s largest crimes, with at least $300 billion stolen each year. While this number seems high, the cost is even higher considering all additional expenses connected with increases in premiums, legal costs and law enforcement expenses or even dealing with consequences of reputational damage and customer retention.

The most significant danger of insurance fraud is its range, as it can span from opportunistic claims by policyholders to fraudulent claims orchestrated by crime rings. Just consider how much damage the crime ring of conniving doctors and healthcare providers from Queens did when they fraudulently billed an insurance carrier for months of treatment and extensive testing. The broad span of these fraudulent activities makes them harder to predict and detect, which is why implementing an effective fraud prevention strategy is more important than ever. 

This is especially important as insurance companies need to pay the claims as quickly as possible while maintaining the balance between investigating potential fraud and ensuring genuine claimants do not suffer in the process. By prioritizing their fraud prevention strategy and embracing new trends, insurance companies can take the proper steps in preventing fraud while ensuring that legitimate claimants stay satisfied with the service.

Fraud Trends Affecting Insurers in 2023

As digitization is changing the demands and needs of customers, every business industry had to adapt to the changes. The insurance industry has always been among the first to accept changes that can help it grow, and digitalization was no different. It allowed insurance companies to launch new business models and optimize revenue streams. Not only can they now offer online insurance sales, but there are companies that exist solely online, offering quick and efficient service to their customers. 

While using big data and AI strategies made it easier for insurance companies to ensure customer satisfaction, their growing online presence also increased the risks of fraudsters using the same technological developments to exploit them. For example, it has been alleged that fraudsters are using deepfake AIs to create synthetic identities – and the prevalence of ChatGPT is expected to exacerbate this. Staying informed about the rising fraud trends affecting insurance companies and adapting your fraud prevention strategy accordingly can be the only thing that stands between you and fraudsters.

1. Identity Theft and Synthetic IDs

Both of these fraudulent activities happen when fraudsters pretend to be someone they are not, to exploit innocent victims. With identity theft, fraudsters can use stolen personal details to conduct their schemes. While similar, synthetic identity fraud brings a different type of danger.

Synthetic identity fraud is a new sophisticated type of financial crime that many companies are still not ready to fight. It happens when fraudsters create fictional identities by combining stolen personal information and fake details. As the identity they are using doesn't actually exist, the fraud attempt can fly under the radar. It is predicted that synthetic identity fraud will grow from $1.8 billion in 2021 to $2.42 billion in 2023, making it the number one threat fraud executives are concerned about in the near future.

2. Money Laundering and Terrorism Financing

Around 62% of global insurance firms have been exposed to fraud or financial crimes in the past 24 months, making money laundering a growing issue. Criminals always find different ways of exploiting unsuspecting companies, and the insurance industry offers them few options. For example, they can launder money by opening an insurance policy using dirty money, after which they submit a fraudulent claim and quickly receive the funds through insurance funds. Another option is opening a life insurance policy, as they offer highly flexible options, allowing them to deposit and withdraw large amounts of cash with a slight loss. Not only will insurance companies be at a financial loss due to paying out a fraudulent claim, but they most likely weren't following AML regulations, leaving them subject to hefty fines.

3. Ghost-broking

This happens when fraudsters pretend to be insurance brokers to sell policies to actual customers while buying those policies from your company. When innocent customers discover the scam, they will come after your company, which might result in reputational damage. 

See also: Global Trend Map No. 11: Fraud

How to protect your insurance company from fraudulent activities

Fraudsters and cybercriminals are constantly searching for ways to commit their malicious actions, while experts continue to come up with new methods of detecting and preventing them. 

This is why it is essential to use cybersecurity solutions such as know your customer (KYC), credit card fraud detection or identity verification. The first thing any insurance company should do is to use the power they have, the data. 

Your potential customers are required to provide you with specific data during the onboarding process, which can be used to confirm their identity if used correctly. By using device fingerprinting during sign-in, you can make sure those logging on are who they say they are, and catch multi-accounting attempts. The process continues once the customers are onboarded, as the accounts are continuously reviewed to verify there are no discrepancies or unexpected changes that might indicate an account takeover. 

Digital footprint analysis is another incredibly useful tool. Using the data the customer has already submitted, such as their email address and phone number, data enrichment solutions source additional information from across the web in real time. For instance, SEON uses over 50 social media and online platforms to tell insurers not just whether the customer is legitimate but to also help gain alternative data on them and even segment them. For instance, you can see if someone travels a lot and stays on Airbnb, if they subscribe to several streaming services and so on -- helping assess their financial situation using openly available data. On the flipside, if someone doesn’t have a digital footprint, that’s a high risk signal and you shouldn’t trust them without investigating.

Velocity checks are another fraud prevention strategy you should aim to use. Velocity checking allows you to analyze data points to determine patterns of standard user behavior, allowing you to recognize any deviations from those patterns that can indicate fraud. These patterns can be anything from multiple accounts being opened from the same IP address or a certain account using several invalid payment details, indicating card testing. Using velocity checks can prevent multi-accounting and account takeovers.

Insurance companies need to ensure they stay compliant with anti-money laundering regulations. Staying compliant will prevent your company from being exploited by criminals while avoiding paying hefty fines or even having a license removed -- and there is AML software to help with this, too, such as tools that check PEP, sanctions and crime watchlists to help companies be compliant with the due diligence part of AML.

Determining the most common risks and identifying any vulnerabilities fraudsters might exploit while using fraud prevention solutions, you can stay ahead of scammers and fraudsters. 

Change 'Beyond Recognition' Coming Up?

The insurance industry is constantly growing by adapting to new customer demands and technological trends. By accepting the changes and offering new services, insurers can attract more potential clients. The insurance industry landscape will continue going through monumental changes as technology advances, with 67% of insurance industry leaders predicting that current business models will change beyond recognition within five years. By establishing effective fraud detection and prevention, you can ensure that your business lives to see the changes.

In this article, discover how insurers are paving their way to success in 2023 with artificial intelligence (AI). Being an insurer in today’s environment is tough, but utilizing the right technology makes it all the more simple. With increased industry pressure, we’re in a moment of time where AI is the only solution for the growing workload.  

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Sponsored by Daisy Intelligence

Incredible as it may seem, the average underwriter today spends seventy percent of their time on tasks unrelated to underwriting—creating a degree of (unnecessary) operational pain that stunts innovation, reduces efficiency, and undermines their true raison d’être: making the best, fastest risk selection decisions possible.

As a result, underwriters struggle to service all the submissions for coverage they receive. Responses back to brokers are often measured in weeks. In some cases, those frustrated brokers place their business with another carrier. In addition, underwriters will say that they usually are making decisions on less data and information than optimal.

The bottom line: Underwriting quality is declining, leading to poor risk selection, poor broker and customer experience, lost new business acquisition opportunities, and profit leakage.

As Jonathan McGoran noted in Risk & Insurance last December, “Roughly sixty percent of underwriters thought improvements needed to be made around the quality of their organizations’ processes and tools. They expressed much more confidence, however, in the skillset and capabilities of underwriting professionals as they perform their core functions.” Yet, “only a quarter of P&C underwriters reported that half or more of their underwriting process is automated, with robotic process automation (RPA) and natural language processing (NLP) seen as particularly deficient.”

The respondents listed priorities for future investments as predictive analytics, new underwriting platforms, business intelligence and reporting tools, customer/broker portals, and self-service solutions.

To free up the time necessary to allow underwriters to nurture broker relationships, price risk, and, ideally, optimize proper risk selection, and secure new business we must address the most common hurdles to success: inefficient processes, outdated systems, lack of information/analytics at the point of need, poor access or organization of underwriting information, and insufficient focus on training/talent development.

For the last 3 decades, the industry has been investing significantly in “Core Systems” like policy administration, claims, and billing. Yet, still today one of the most important insurance functions to “profitability & Growth” remains significantly under-automated, placing the burden on the underwriters themselves resulting in less than optimal underwriting quality and profit & growth leakage.

The window for addressing the decline in underwriting quality and the growing gaps in process automation, integration with legacy systems, customer and broker collaboration, and access to required data in a timely manner is closing fast. The technology is available today to address these hurdles without waiting to replace legacy systems or the maturity of new and emerging technologies. Leveraging technologies designed for integration with existing systems, including APIs and microservices, data lakes, and data mesh solutions, intelligent document processing technologies (e.g., RPA, NLP, AI) will automate the end-to-end underwriting process and improve performance.

In short, now is the time to focus on a “Core Systems Platform” to support the Underwriting Process. Leveraging an intelligent workflow automation approach to the deployment of an end-to-end automated underwriting platform (e.g., underwriting workbench) that insulates underwriters from having to jump between multiple systems to fulfill their tasks. Instead, data from diverse platforms can be made available to underwriters in the platform’s single, stable user interface.

The Opportunity

The opportunities to drive significant improvements in underwriting performance, broker/customer experience, and profitable growth are staring us in the face.

• Streamlines more efficient Improved Underwriting process
• Increased Underwriting capacity to support growth
• Improved risk selection and profitability
• Improved time to market of Underwriting decisions
• Improved Broker and Customer Experience
• Providing a foundation for straight-through processing for low complexity / fast flow risks
  

The New Underwriting Platform – Key Automation Capabilities

To realize these opportunities today’s target Underwriting Platform should seek to include the following automated capabilities.

Key automation capabilities include:

1. Digitized Submission Ingestion
   • Automated Triage & routing (RPA) and digitization (NLP) of Broker emails, forms, documents, and Big Data sources
   • Collaboration and self-service portals
   • Underwriting dashboard and integration APIs
2. Underwriting Capacity Management & Assignment
   • Automated Underwriter Assignment
   • Rules-based assignment-driven authority, expertise availability & capacity
   • Capacity & SLA Tracking, monitoring, & Reporting
3. Manage Forms & Correspondence
   • Broker & Client Collaboration & Communication
   • Submission & UW Status via a self-service portal
   • Communicate additional information requirements
   • Status of Pending information & Document requests.
   • Producers and underwriters can share documents, notes, and emails, providing real-time visibility into the submission process for new business, renewals, and endorsements
   • Automatically Create and deliver forms as needed for clients and brokers (forms management & Automation)
     

Case Management & Tracking

• Centralize the work queues to provide an end-to-end view of the requests and interactions
• A holistic view of the submission, forms, documents, policy and claims information, underwriting notes and data, SLA performance, correspondence, etc.
• Analysis of Customer Risk & Rating Engine Input
• Pricing and client proposal
• Workflow automation to enable work will flow seamlessly and timely between Underwriting Branch offices & Operations.
  

Centralized and Easy Data Access  

• Intelligent document automation using NLP to digitize documents, forms, and unstructured data for easy access and retrieval
• Real-time policy and claims data access (dashboard & APIs)
• Real-time 3rd Party data access (dashboard and APIs
• Improved naming and indexing of imaged documents and forms for easier access (dashboard, APIs, & RPA)
• A centralized, holistic view of underwriting data and original submissions (forms, documents, etc.)
  

Automation Strategy & Roadmap

While emerging technologies like ML and NLP are maturing quickly they are not a requirement to attain significant progress in the automation of the Underwriting process. Replacement of legacy core systems is also not a prerequisite for automation as target architecture solutions leveraging APIs and data lakes can enable real-time data access. RPA platforms have attained a significant level of maturity and can and are being used to automate many manual, repetitive activities and tasks. To address this issue, Insurers should develop an Underwriting Intelligent Workflow Automation Strategy and Roadmap that provides for incremental and continuous automation.

A typical strategy and road mapping Project to maximize profitability and growth will include:

• Define the business objectives and goals to be satisfied
• Define the future state workflow enabled by the automation capabilities
• Identify the corresponding automation opportunities and capabilities to meet those goals
• Identify and Access current and emerging technology solutions to provide automation capabilities, performing proof of concepts (POCs) as needed
• Design the target solution architecture and associated enabling technologies
• Develop a roadmap to deliver the target solution in incremental release
• Look to identify opportunities for continuous improvement and automation (inclusion of big data, predictive and prescriptive modeling, Ml and AI enriched data, etc.)

Overall, investing in Intelligent Workflow Automation of the Underwriting process, leveraging technologies such as predictive analytics, Al, ML, NLP, case and event management will help improve underwriting capacity, underwriting quality, and the ease of doing business for customers/producers leading to improvements in profitability and growth.

There will not be a better time nor a greater need for urgency than today to fill the void in your core systems portfolio to enable underwriters to do what they are highly trained and skilled to do – risk analysis, selection, and pricing.

Footnotes: The Institutes’ study was sponsored by Accenture, quoted in Risk & Insurance – We Talked to Hundreds of Insurance Underwriters. What They Have to Say May – Surprise You | Risk & Insurance

Sponsored by ITL Partner: OZ Digital Consulting

Providing customers and agents with robust, fully integrated self-service tools can lower an insurer’s costs and improve customer satisfaction. Whether a policyholder needs help at 2 a.m. with a policy change or claim, or an agent on the road seeks coverage details, many companies aspire to full self-service capabilities. But few are delivering.

Sponsored by Pypestream 

Ever since the dawn of the Digital Age some 50 years ago, economists have debated the “productivity paradox.” We all see the incredible, accelerating power of digital technologies and watch them pervade all aspects of our lives, but where are the productivity gains? 

The Industrial Revolution increased productivity so fast and created so much wealth in the 1800s that it transformed the world. Why isn’t what is often called the second industrial revolution (or third or fourth, depending on who’s counting) boosting productivity as effectively? Why has productivity merely been on a steady, unspectacular incline since the early 1970s? 

Some economists say the problem is with the productivity statistics, not with productivity itself. They note that a lot of the gains from digital technologies simply aren’t measurable. Searching on Google lets you learn lots of things you wouldn’t have otherwise known, but how do you measure the increase? Even in a work setting, having the world’s information at your fingertips typically doesn’t mean that you’re producing the same output at lower cost or increasing your output at the same cost – the definitions of improvement used in productivity statistics. You’re maybe producing a better output at the same cost, but economists have a hard time measuring that gain. In fact, some digital technologies show declines in productivity. We no longer buy CDs, so all the work that goes into making the music on them now produces less revenue, even though people are listening to far more music than ever before.

Other economists say we simply need to be patient. It takes years, even decades, before fundamental economic changes can percolate their way through business practices and cause the kind of improvement that we saw in the Industrial Revolution. James Watt’s rethinking of the steam engine in 1776 created the technological breakthrough, but it wasn’t until someone else invented the factory and yet another person invented the limited liability corporation that the power of the engine was fully unleashed – and that wasn’t until roughly 1820. There was, in fact, a brief surge in productivity in the late 1990s, roughly three decades after the start of the Digital Age, and many economists say we can expect more in the future, based on all the technological gains.

I’d note that the disappointment about digital sometimes stems from a simple issue: unrealistic expectations about profitability. Companies will see efficiencies to be gained from digitizing and will predict improved profitability. But they forget that, while they’re becoming more efficient, the other guy is, too – and that those efficiency gains will be competed away. 

That’s all a long way of saying that, while I’m generally an evangelist for technology, I’m cautious about accepting grand claims on how digital technology will transform business in short order. 

So, having chronicled for years how digitization is creating opportunities in insurance, without quite producing the Holy Grail, I was more than a little intrigued when I saw a report from Liberty Mutual that highly digital agencies were growing 70% faster than their less digital rivals. To learn more, I sat down with Tyler Asher, Liberty Mutual’s president, independent agent distribution, for this month’s interview. I hope you find it as enlightening as I did, both on where the opportunities for breakthroughs are, and where they aren’t.

P.S. Here are the six articles I'd like to highlight this month for agents and brokers:

AN AGENT’S GUIDE TO OUTREACH IN 2023

In this new year, agents should branch out of their comfort zones and consider how to improve their efforts to identify and capture new business.

ENDING THE TEDIUM IN INSURANCE

Anyone who has purchased insurance by phone and a series of back-and-forth emails knows how slow and difficult that process can be. But it doesn't have to be that way. 

20 ISSUES TO WATCH IN 2023

While there are certainly more than 20 issues to discuss, here are high-impact matters relating to workers’ comp, healthcare and risk management that need more attention.

7 KEY TRENDS IN 2023

To help industry players orient themselves, compete more effectively and better serve customers in an increasingly volatile world, here are trends to watch for. 

HOW TO RISE ABOVE DISRUPTION IN 2023

Insurers started 2022 in a position of strength and still are in a good spot to drive down costs and increase demand, unless rising claims costs and market volatility continue.

BRANDED COMMUNICATION: A STRATEGIC ENABLER

At a time when few answer a call from an unknown number, insurers can identify themselves as a legitimate caller by displaying logos and a reason for the call on the recipient’s device.

Touchless claims aren’t just the future of the insurance industry – they’re the present. Customers today have shifted from being familiar with doing business online to largely preferring it in many cases, and that ripple effect has been felt and registered by insurance companies globally. But the industry at large has some catching up to do to meet this demand. Recent statistics from Price Waterhouse Coopers indicate that 41% of insurance customers are likely to switch insurance providers due to dissatisfaction with their carrier’s digital capabilities. 

The problem isn’t that insurance companies refuse to update old technology. It’s that technology is only a component of a successful touchless claims implementation. And having the best, latest tools won’t help if you don’t allow processes to evolve and leverage the full capabilities offered. 

My daughter was involved in an automotive insurance claim last year. Because I have some experience working with insurance claims, I offered to help her through the process. My experience with this claim in 2022 was essentially identical to how it would have been handled in 1995. Situations like this aren’t uncommon, but it is worth examining why they’re happening.  

The processes insurers use haven’t adapted to the capabilities of the new technology they have adopted. Insurance claims today involve vastly more data than they did decades ago, yet the way that data is being handled and the number of touchpoints in the process haven’t kept up. This leads to a heavier workload for everyone in that chain due to multiple handoffs and slows workflow. Ultimately, customers aren’t served as well as they could have been. 

People are generally resistant to change, and while they may be open to trying new technological solutions, they are hesitant about changing their workflow and established ways of getting things done. This is one of the key roadblocks the industry faces in moving to a truly touchless claims future: New tools are often seen in a narrow focus instead of as part of an integrated system. 

This bolt-on approach rarely solves many problems, and after a while frequently causes more trouble as compatibility issues arise when pieced-together parts don’t play well together. What is needed isn’t necessarily more tech but a perception shift about the way technology should be integrated, not only as individual components working together but also with processes and workflows. When you have seamlessly integrated solutions and make use of their full potential, you’re not only getting the most from your technology investment, you’re also freeing your employees to do what they do best. 

See also: Turkey's Disaster Was Preventable... by Insurers

I see a future, not far off, when a claim can be initiated and begin processing before the claimant gets back home. Imagine you’ve just been in an accident. There’s a QR code on the insurance card you carry in your car that takes you directly to your carrier’s claims portal mobile phone application. You are instantly identified once the code is scanned, and there are no extensive forms to fill out and no typing. Just a few clicks to take photos of your vehicle and any other vehicles involved, capturing damage and license plate information, which is used to retrieve vehicle information. 

From there, the app will activate, managing the claim from start to finish: providing the estimate, arranging for a local body shop to do the work and setting up a vehicle rental. Claims professionals and claimants can communicate through the app, and everything customers need to handle claims is right there on a device that they carry with them every day. 

We’re not there yet, but nothing is stopping us from taking more steps in that direction now. With a slightly different approach to the way technology and processes work together, that could be a reality in just a couple years. The tools are already there, and the customers have made their preference of touchless claims widely known. 

The companies that act today to improve their customers’ digital experiences will see dividends in both customer service and operating expense.

Modernization of core policy admin systems is a foundational piece of a life insurer’s digital transformation journey‒but legacy system replacement introduces data risk and complexity. Join our expert panel on this webinar to find out how taking a Greenfield approach as a first step in a PAS modernization can reduce risk, accelerate innovation and help carriers stay ahead of the digital transformation curve.

Webinar Date: February 22, 2023 at 11AM EST

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In this webinar, you'll learn:

• How to dramatically increase the speed of product innovation
• How to define digital transformation goals and implement new products in a way that supports achieving those goals
• Tools and techniques to make your greenfield initiative successful

Webinar panelists:

• Alan Dulin, Global Head & Senior Managing Director, Oracle
• David Shively, COO, Equisoft
• Chip Bircher, Analyst, Aite-Novarica Group
• Alec Mendez, Consultant, Equisoft

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Sponsored by Equisoft 

It’s a new year for the insurtech industry. While the market has left its nascent stage, it hasn’t reached maturity yet. We are in the midst of what many consider its “2.0” era, where companies have learned what works and what doesn’t, along with new approaches. All this is taking place against the backdrop of the economic downturn and broader challenges that are affecting businesses in every sector. 

Here’s a look at what’s likely ahead. 

Top of mind for many insurtech leaders is consolidation, which is generally consistent with the economic climate companies are navigating. Recessions, rising costs and inflation typically affect funding at a macro level. As that happens, organizations that are not profitable or that rely on funding to survive often look to sell. Others face more drastic measures such as cutting staff or, in the worst cases, are forced to close their doors. Consolidation starts to rise as a result, sparking an uptick in merger and acquisition activity. Larger organizations begin to buy smaller players, or businesses merge. We’re seeing this consolidation now and will likely see it for a while. 

Market consolidation isn’t limited to down cycles. It can be a natural part of an industry’s lifetime, even in relatively positive economic conditions. The shift is ultimately good, in general, regardless. Markets can’t support companies that aren’t profitable or can’t show a clear pathway to profitability. Consolidation cuts the fat and reduces saturation. It typically creates efficiency and opportunity, freeing funding where it is available and enabling top-performing organizations to rise. Those in a position to capitalize can get great deals, merge, make moves and generate other benefits. Amazing businesses are often built in these conditions. Companies that need to be bullish and acquire companies can do so, and companies that are struggling can find a way out. Watch for consolidation in the coming year, and, if considering M&A, now may be the time to start. 

2023 will also likely see less investment funding in insurtech. Signs of change began last year, with potential impact to continue in the next 12 months. This will in part play a role in further market consolidation, though funding won't completely stop. It will just become more focused and selective. VCs are looking to deploy investments more carefully, with an eye on organizations that can win the game of insurance, versus the moonshot risks and high valuations of the past. Successful companies with a track record can gain during this stage, as investors become more selective on where dollars are deployed and attention turns to companies that have insurance fundamentals and established paths to profitability. 

See also: 20 Issues to Watch in 2023

Technology is always at the forefront of insurtech. However, it’s getting increasing attention among legacy insurance companies, which will likely drive a bigger focus on technology in the market this year. It will play a role in helping companies do more with less, reduce inefficiencies, streamline processes and create capital. We’ll likely see this also drive consolidation in the category as bigger insurance companies opt to buy insurtechs in niche markets instead of building innovation in-house. Smaller insurance and insurtech businesses will also do the same where they can, either merging or acquiring to gain technology assets. It’s not likely that there will be large, sweeping disruption or change that will uproot the whole industry. But we will see highly specialized insurance companies continue to leverage technology and do really well. 

The coming year will likely present a lot of opportunities for big carriers to buy whatever they’re interested in. Larger companies are well-capitalized and tend to remain relatively recession-proof, with a lot of resources to deploy. They will be scrutinizing insurtechs and taking a hard look at their core business and fundamentals and their odds of achieving profitability in the coming years. The days when insurtechs could rely on outside capital and hitting milestones to get to the next funding round are gone. Business this year will be about hitting target milestones to be self-sustaining or finding other ways to make money. Highly specialized insurtechs that stay focused on their market niches will likely do well and will gain the most interest and attention from investors as well as large carriers looking for acquisitions.

Over the past half decade, several organizations in the workers’ compensation industry have promoted their business by saying they apply artificial intelligence, or AI. I looked at their offerings a few years ago. I found that what they meant by AI was worthy of consideration. However, AI today means computational power dramatically more effective than what was then promoted. AI has the potential in 2023 to dramatically raise the quality of claims handling and underwriting, to name two functions in workers’ compensation. 

One might say that a breakthrough has just taken place that makes AI work in the way we’ve implicitly expected for a long time, and until now have not experienced.

In late 2022, OpenAI released for free public use a system called ChatGPT, heralding a new generation of what will be widely used AI products.  As of the end of January 2023, some 100 million persons are estimated to have used it, making it the most rapid large-scale launch of a consumer product in history.

ChatGPT is the first sign of a quickly emerging AI generation. It is very easy to use. Responding to a request posed in conversational English, it writes plans, analyzes your writing, fixes computer software, writes a poem. I compare it to driving a car without any knowledge of how the engine operates. It is much more insightful and efficient in many instances than Google search.

I tested it out posting many workers comp-related requests. Some responses were vapid, but most ranged from useful to very insightful. With more preparation, the system has great promise as a practical tool. Claims staffs can use this generation of AI to more accurately predict claims outcomes and to select interventions, such as case management or subrogation reviews. Underwriting staff can better price premiums.

We’ll get into some scenarios in a moment. I want now to provide a very basic (albeit somewhat rough) introduction to machine learning using large language models, which is at the heart of ChatGPT.

Machine learning using large language models does not use what we might normally call algorithms-based or logical thinking to predict. It will confidently predict that the word “you” usually comes after “thank,” not because it knows the meaning of words and grammar. Its prediction process is so complex that it can’t be explained or audited by the user.

Consider how to predict the second to last elements in “The quick brown fox jumped over the lazy [word] [punctuation].” 

The computer, without any intrinsic, original knowledge of what a word is, or word meaning, or grammar, will produce a numerical score for each element relative to the probability of each element coming before or after each of the others. Hence the three elements in “the” will have a relatively high predictive score to precede “quick.” And “jumped” will have a lower predictive score to follow “fox.” That is because the elements that precede "quick" are easier to predict than the elements that follow "fox."

The computer has been trained by inspecting many millions of texts, one at a time, converting letters and punctuation into numbers. For each string of numbers, the computer will recalibrate scores for each number relative to its probability of coming before or after each other number. It is searching eventually for strings of words followed by a period. It will assign a very high probability, with a great deal of confidence, that the missing word is “dog,” much more likely than it is “cat” and far more likely than it is “cloud.” 

ChatGPT describes itself in these words: A model which is exposed to vast amounts of data and learns to predict and respond with “human-like text with a high level of coherence and relevance.” It is trained to handle tasks such as language translation and computer code writing. It can be fine-tuned to perform on limited data sets for claims or underwriting.

See also: The Key to 'Augmented Intelligence' 

Consider the adjuster with a new workers’ compensation claim involving multiple bodily trauma. AI of this generation will predict ultimate claim cost – that doesn’t sound very impressive. But it will also advise the adjuster what additional information will improve the prediction. And, it will predict which medical treatment and what treatment will lower the cost, and by how much. 

For the underwriter, AI predicts ultimate costs of all claims and advises on what information and what interventions (such as loss control and experience rating/deductibles) will improve prediction and will increase profits for the insurer. 

Is this what we want? The answer is yes, with caveats. What if AI enables decisions that might conflict with ethics and public policy? For instance, it might predict that a combination of experience rating, high deductibles and no loss control may yield more injuries but higher insurer profits than a program of aggressive loss control.  

And, how concerned should we be about not being able to track the computations, generating lessons on how to peel a boiled egg and the probability of medical fraud? As in the example of predicting “dog,” the computer operates at an unbelievable level of complexity. It cannot tell you the meaning of dog, or trauma, or subrogation, or high deductible, except to predict that a set of numbers compose what we humans call words, which we humans give meaning, such as “dog” as an animal rather than as the verb for giving chase. One can say that the computer is very useful and unaccountable.

Industry organizations such as large insurers, the National Council on Compensation Insurance, the Workers Compensation Research Institute and medical reimbursement services may be the first ones to bite into the apple. And none too soon for all others to grasp the potential of this new generation of AI.