Customer acquisition has been a thorn in the side of life insurance providers in the U,S. The number of American adults with life insurance has declined since the 2010s, leaving more consumers uninsured or underinsured and affecting other corners of the financial sector. Although ownership has stabilized post-pandemic, insurance companies aren't protecting enough consumers financially.

Life Insurance Remains Widely Misunderstood

Out of all mainstream insurance products, life insurance is the most underappreciated. It doesn't inspire a sense of urgency like auto insurance, which is mandatory. Life insurance isn't a legal requirement in financial transactions — the opposite of homeowners insurance, which mortgage lenders demand before releasing funds to borrowers.

The public views life insurance more as discretionary and less as essential. The fact that only 37% of adults surveyed in January 2024 — out of the 42% who admitted they need or need more insurance — said they plan to buy a policy within the next 12 months proves this.

The 2024 Insurance Barometer study by LIMRA and Life Happens found that American consumers don't own any life insurance policy at all or don't own more coverage because of three reasons:

• High cost
• More important financial priorities
• Confusion about what to buy and how much

On the bright side, nearly three-fourths of consumers overestimate the actual cost of a basic term life insurance policy, and more than half rely purely on gut instinct. Debunking the myth that life insurance is out of reach and articulating its value as an estate-planning tool can move the needle on sales.

Unfortunately, insurance companies have yet to close this knowledge gap with marketing. The research commissioned by the SOA and RGA and published in August 2024 suggests that life insurance product information could be more straightforward, resulting in miscomprehension among consumers and stagnant sales.

Curiously, low popularity for estate planning in the U.S. coincides with the downward trajectory of life insurance ownership. Financial advisers' significant role in estate plan adoption reinforces the need for product clarity to inspire sales. After all, the adults with access to sound financial advice are four times more likely to have an estate plan.

History Says Simplifying Language Alone Doesn't Work

Life insurance information complexity is old news. Insurers have known this for a long time and attempted to explain the intricacies of this financial product in layperson's terms to no avail. On the contrary, attempts have backfired.

In the mid-2010s, LIMRA tested the traditional "quick and easy" marketing message to entice Americans to buy life insurance. This strategy didn't work as well on life insurance as it normally does on most retail goods. Out of all the marketing messages the researchers used, this one performed the worst.

The trade association did a follow-up study in 2017. LIMRA tried 10 different messages, emphasizing the benefits of buying insurance online. Although some did better than others, none was a runaway winner.

There are two takeaways:

• Convenience isn't as powerful a motivator as thought.
• Simple language alone doesn't sell.

Incorporating behavioral science techniques into content simplification efforts may be the key to spurring life insurance ownership.

Behavioral Science: Making Life Insurance Easier to Understand

Explaining the nitty-gritty of life insurance is only half the battle. Convincing the public that a financial product generally viewed as only beneficial after death is the other.

Life insurance providers can reduce misconception throughout the sales journey by acknowledging that humans have limited cognitive resources. Only a few people have the time to exert considerable mental effort to understand and appreciate financial products. Naturally, consumers would concentrate their time, attention and bandwidth on those aligned with their near- and long-term goals.

Rising retirement anxiety is one of the reasons life insurance has been a hard sell of late. In 2024, 79% of Americans believe the country faces a retirement crisis — up from 67% in 2020. Discerning life insurance carriers would view this sentiment as an opportunity to debunk the notion that policyholders can't enjoy the coverage while alive.

More adults may give life insurance products a second look if they're aware of living benefits. Marketing cash value accounts as financial cushions and living benefit riders as means to tap the death benefit during the policyholder's lifetime can generate interest and entice consumers to learn more.

Behavioral science can help reinforce a simplified marketing message while shifting the focus to specific life insurance components that resonate with more consumers. Various techniques can help insurers leverage the human tendency to think fast or slow when making decisions.

Fast thinking refers to routine decision-making, which involves no conscious deliberation, while slow thinking involves deeper logical consideration to judge more complex subjects. Designing customer journeys with this in mind can improve life insurance comprehension and may translate to higher customer acquisition.

Behavioral Science Techniques to Complement Simplification

Simplification is a behavioral science technique. However, timeliness, salience and relevance are just as vital to demystifying life insurance. To aid comprehension, insurers should:

• Create marketing content in plain language.
• Present concepts at optimal moments.
• Ensure that the most essential details visually and auditorily stand out.
• Provide a quote matching every individual's unique situation.

There are countless ways to combine these behavioral science techniques to educate consumers about insurance online. Websites and emails with thoughtful typography, engaging visuals, FAQ sections and interactive tools are tried-and-true media.

Social media and artificial intelligence (AI) also supercharge information dissemination and content creation. Video consumption accounts for 82% of all internet traffic, so being on TikTok, producing YouTube Shorts, and uploading Reels on Facebook and Instagram are recipes for success.

Moreover, messengers are as crucial as digital channels. Life insurance buyers are judicious, so using a trusted messenger will lend credibility to content.

AI-generated avatars are also becoming more popular, as they help insurance marketing teams balance rapid content production, customization and cost-effectiveness. Considering that 99% of global insurers have invested or are planning to invest in AI, seeing this innovative approach to marketing gain currency in the future shouldn't be surprising.

Still, insurers should think twice about choosing AI over humans when engaging with prospective buyers and paying customers. While bots can soup up marketing engines and customer service portals, they have limitations. AI excels in analyzing mountains of data, identifying patterns and spotting anomalies, but nothing compares to human resourcefulness.

Human subject matter experts can provide practical advice to promote life insurance comprehension and resolve individual concerns in ways available self-help resources can't. In contrast, AI can hallucinate and spread false information, responding to queries with incorrect, biased or fabricated answers.

Allianz — A Success Story

Allianz has adopted customer-centricity through simplicity to achieve its goal of becoming one of the 25 top insurance brands by 2025. The multinational took this route at a time when most insurers embraced hyperpersonalization — an approach emphasizing providing customers with information based on their personal data, risk profiles and past interactions.

This move raised the eyebrows of many pundits, doubting the company's ability to grow while simplifying its products and processes in markets where it had traditionally sold diverse offerings.

But Allianz's decision to double down on simplicity has paid off. In 2024, the company moved up two places to become the 29th-best global and top insurance brand worldwide. Allianz's value ballooned to $23.5 billion, a 13% increase year-over-year.

Careless Execution May Cause Legal Issues

Employing behavioral science to bridge the insurance comprehension gap and boost customer acquisition carelessly may result in regulatory noncompliance. Penalties and settlements can lighten insurers' coffers, and reputational damage can be costlier.

Using behavioral science techniques effectively and legally involves considerable uncertainty and countless tests. Fortunately, dozens of recent case studies demonstrate how not to do it.

In 2015, Geico agreed to pay $6 million to settle with the California Department of Insurance. The case stemmed from the Consumer Federation of California's allegation that the auto insurer's premium quoting system discriminated against consumers based on gender, occupation and education level.

In 2020, then-Massachusetts Attorney General Maura Healy filed a case against UnitedHealth Group entities for allegedly supplemental health insurance as an alternative to primary health insurance, misrepresenting agents as licensed insurance advisers and using emotional manipulation. Healy claimed the defendants deceived more than 15,000 low-income and Medicaid-eligible consumers and violated the state's consumer protection law and a 2009 Superior Court judgment.

In 2024, Sanya Virani sued NLV Financial Corp. and two subsidiaries for allegedly using rosy illustrations to sell indexed universal life policies. The plaintiff's policy yielded a 0% return after one year. Virani argued the insurer used unrealistic back-tested historical performance. She called the product a "fraudulent sham" because she would have to pay hefty surrender fees if she terminated her policy.

Take Care With Customer Acquisition

Insurance information simplification and other behavioral science techniques aren't foolproof, so learning the lessons from others' mistakes is crucial to avoid finding an organization in hot water.

Cyber incidents such as data breaches or ransomware attacks, and IT disruptions, like the CrowdStrike incident, are the biggest worry for companies globally in 2025, according to the Allianz Risk Barometer.

Once again, business interruption is also a main concern for companies of all sizes, ranking No. 2. After another heavy year of natural catastrophes activity in 2024, this peril remains No. 3, while the impact of a super election year, rising geopolitical tensions and the potential for trade wars mean changes in legislation and regulation is a top five risk at No. 4. The biggest riser in this year's Allianz Risk Barometer is climate change, from No. 7 to No. 5, achieving its highest-ever position in 14 years of the survey.

The Allianz Risk Barometer is an annual business risk ranking compiled by Allianz Commercial, together with other Allianz entities. It incorporates the views of 3,778 risk management experts in 106 countries and territories, including CEOs, risk managers, brokers and insurance experts.

Large corporates and mid-size, and smaller businesses all perceive cyber incidents as their No. 1 business risk. However, there are significant differences in the rest of the ranking. Smaller companies are more concerned about more localized and immediate risks, such as regulatory compliance, macroeconomic developments and skill shortages, but there are also signs that some of the risks that have preoccupied larger companies are starting to affect smaller firms, too, with climate change and political risks and violence climbing the ranking.

In the U.S., cyber incidents once again top the list of business risks, followed by natural catastrophes at No. 2, up from the third spot in 2024. Rounding out the top three is business interruption. Changes in legislation and regulation is the biggest riser in the region, advancing to the fourth spot from No. 8 in 2024.

Cyber risks continue to increase with rapid development of technology. 

Cyber incidents (38% of overall responses) rank as the most important risk globally for the fourth year in a row – and by a higher margin than ever (seven percentage points). It is the top peril in 20 countries, including Argentina, France, Germany, India, South Africa, the U.K. and the U.S. More than 60% of respondents identified data breaches as the cyber exposure companies fear most, followed by attacks on critical infrastructure and physical assets, with 57%.

According to Rishi Baviskar, global head of cyber risk consulting at Allianz Commercial, "For many companies, cyber risk, exacerbated by rapid development of artificial intelligence (AI), is the big risk overriding everything else. It is likely to remain a top risk for organizations going forward, given the growing reliance on technology – the CrowdStrike incident in summer 2024 once again underlined how dependent we all are on secure and dependent IT systems."

See also: The Evolving Landscape of Cybersecurity

Business interruption strongly linked with other risks.

Business interruption (BI) has ranked either No. 1 or No. 2 in every Allianz Risk Barometer for the past decade and retains its position at No. 2 in 2025, with 31% of responses. BI is typically a consequence of events like a natural disaster or a cyberattack, which can affect the ability of a business to operate normally.

Several examples from 2024 highlight why companies still see BI as a major threat to their business model. Houthi attacks in the Red Sea led to supply chain disruptions due to rerouting of container ships, while incidents such as the collapse of the Francis Scott Key Bridge in Baltimore also directly affected supply chains. Supply chain disruptions with global effects occur approximately every 1.4 years, and the trend is intensifying, according to analysis from Circular Republic. Those disruptions cause major economic damages, ranging up to 5% to 10% of product costs and additional downtime impacts.

Climate change reaches new high.

2024 is expected to have been the hottest year on record. It has also been a year of terrible natural catastrophes with extreme hurricanes and storms in North America, devastating floods in Europe and Asia and drought in Africa and South America.

After dropping down the ranking during the pandemic years, as companies had to deal with more immediate challenges, climate change moves up two positions into the top five global risks, at No. 5 in 2025, its highest-ever position, while the closely linked peril of natural catastrophes remains at No. 3, with 29%, although more respondents also picked this as a top risk year-over-year. For the fifth time in a row in 2024, insured losses surpassed $100 billion.

See also: Why Is the Cyber Insurance Market So Soft?

Geopolitics and protectionism remain on the radar.

Despite continuing geopolitical and economic uncertainty in the Middle East, Ukraine and Southeast Asia, political risks and violence drop one place to No. 9 year-over-year, albeit with the same share of respondents as 2024 (14%). But it ranks as a more concerning risk for large companies, up to No. 7, while it is also a new entry into the top 10 risks for smaller companies, at No. 10.

The fear of trade wars and protectionism is increasing, and analysis shows that within the last decade export restrictions on critical raw materials increased by a factor of five. Tariffs and protectionism may be top of the list of the new U.S. government, but on the other hand there is also the risk of a "regulatory Wild West," particularly around AI and cryptocurrencies. Meanwhile, sustainability reporting requirements will be high on the agenda in Europe in 2025.

Read the full 2025 Allianz Risk Barometer here.

Amy Radin is a transformation strategist, a scholar-practitioner at Columbia University and an executive adviser. As a member of the Fast Company Executive Board and author of the award-winning book, "The Change Maker's Playbook: How to Seek, Seed and Scale Innovation in Any Company," Radin regularly shares insights that help leaders reimagine their approach to organizational change. Her thought leadership draws from both her scholarly work and hands-on experience implementing transformative initiatives in complex business environments. Previously, she held senior roles at American Express, served as chief digital officer and one of the corporate world’s first chief innovation officers at Citi and was chief marketing officer at AXA (now Equitable) in the U.S.  Radin holds degrees from Wesleyan University and the Wharton School.

Insurance Thought Leadership

You’ve said that companies need to change the way they change. How do you approach that problem, both generally and in the context of the course you teach at Columbia?

Amy Radin

The whole premise of the course, much of which is drawn from my own lessons learned, is about moving a complex bureaucracy forward and having people accept the idea of change. For a long time, I was an operating executive on the bleeding edge of change, often in conflict or intense discussion with colleagues. In a zero-sum, fixed-resource environment, which is how most big companies operate, doing something new often is perceived as coming at the expense of something else. 

Starting in the early eighties, consulting firms built businesses around what's called change management. The eighties' idea of change management, which is still prevalent, is that change happens from the top down—incremental changes at a predictable pace, often within organizational silos, and in a command-and-control mode. Leaders plan and direct, leveraging their hierarchical authority to get things done. 

However, in today's world, with AI, robotics, advanced data analytics, and the integration of technology to enhance human creativity and problem-solving, that traditional mode of change management is no longer effective. Change will happen in organizations that can rapidly adapt and iterate, promoting engagement and collaboration across silos, and where employees are empowered rather than told what to do. Leaders need to build a culture of empowerment and participation, where the customer comes first, experimentation is promoted, and failure is treated as learning. 

The shift is from hierarchical authority, where leaders plan and direct, to a world where change is driven by the power of networks, and leaders inspire and empower belief in a vision of the future. This is something I've learned from the executives I work with in my course at Columbia and from my own experiences as an operator. Instead of just telling people what to do, which frankly doesn't work, it's about building change leadership skills, mindset, and capabilities to help employees and stakeholders navigate the integration of human-centric technologies, anticipate and pivot quickly as new challenges and opportunities arise, and provide transparent communications and a clear vision. Leveraging networks rather than hierarchical authority is key to winning support and accomplishing change. 

This approach resonates with those leading change because the work is really tough, especially with everything that's happened in the last couple of years with AI and advanced data analytics layered on top of the usual challenges of change. Old methods just don't work anymore.

Insurance Thought Leadership

I was always rather skeptical of the change management stuff, even as a partner at one of those consulting firms, because it seemed a little too packaged.

Amy Radin

You make an interesting point. One of the things I talk about in my class is that one of the worst things you can do when you want to drive transformation is get everybody together and say, "Okay, we're all going to change now." What you're doing is essentially telling the resistors in the room what they need to resist, enabling more resistance while confusing most of the other people. 

One of the books we read in my course is a best-seller called "Cascades." The author, Greg Satell, spent about 15 years in Ukraine. He was there during the Orange Revolution and became really interested in the history of social movements and how they take hold and build steam. He tells the story of how the Orange Revolution started with just a handful of guys in a coffee shop, and how they went from this small group to a couple hundred, to a few thousand, to tens of thousands in the course of a year or so. 

Greg's idea was that the lessons learned from how social movements build momentum could be replicated in the corporate world. Not that we want to promote overthrow, but rather to build momentum and scale change. It's really about starting with a small team, then finding other small teams, helping them, and building networks across all those small teams of believers, uniting them against a common purpose and vision. 

I find it fascinating. When I think back to some of my corporate experiences, it makes so much sense. We did some of that, but more because we stumbled into it by accident, not because we could label it as an effective strategy. 

If you're interested in learning more, you can search for Gene Sharp and “How to Start a Revolution” on YouTube. He worked with resistance movements all over the world to help them apply best practices of resistance. If you cross out the word "resistance" and repackage it as "transformative change" in the corporate world, it becomes very relevant. 

Based on my student evaluations, it seems this approach resonates with people in organizational settings. I've always been a fan of learning from completely different sectors. 

This is about the power of networks and starting really small, uniting people around a common purpose or vision. It's about abandoning the idea that just because you have a big title and a big budget, you're going to get people to pay attention.

Insurance Thought Leadership

I’m betting that the wave of innovation involving AI creates an environment where people are thinking more about change.

Amy Radin

That's hugely important. Too many people are approaching AI as just a way to automate and eliminate jobs. The early data is already showing that the economic value of AI and these technologies, including robotics, is much greater when viewed as tools to augment and expand human creativity. In fact, the economic value of creativity enhancement is triple the value of productivity gains from efficiency and staff reduction. Most people are missing the point by seeing AI purely as an expense reduction tool versus a means of expanding human potential with many other benefits, not just cutting costs.

I'm experiencing this firsthand while taking an online course in generative AI. Yes, it's making me more productive, but more importantly, it's expanding my thinking and capacity to imagine things, driving me toward higher order of thinking and expanded impact for my clients.

If you're approaching this as a CEO or CFO simply asking how to save money using AI and pushing that on the organization, versus thinking about how it's a tool to increase human capacity to perform and engaging employees to begin to experiment, you're missing the boat. If you want to focus on the bigger opportunity -- enhancing human performance -- by definition, you must start engaging your organization and experimenting with small pods of people who are up for doing something different.

Insurance Thought Leadership

Do you have an example from your experience in financial services about how a CEO should approach organizational change?

Amy Radin

First, you truly have to start with deeply listening to your customers and other stakeholders. Everybody says they're customer-centric, but most people aren't. You have to start with understanding who you really want to do business with and deeply listening to understand where they are and what they're looking for right now.

Then you need to identify sparks of interest, activity, or commitment within your organization to pursue solving those customer needs using new technologies. Rather than starting change with a big announcement and program, thinking it's all about communications, seed activity that helps prove what your change path should look like and empower your people to expand from that small group to other parts of the organization. It's much more about driving real collaboration versus telling people what to do.

I just started writing an article this morning on the power of asking the right questions. Rather than going into a room and presenting a new idea only to have it get shot down because everybody thinks they're the expert, what if you promoted a culture where the expert was willing to say, "Wow, that's really interesting. How did you come to that insight?"

I don't know if you can make people be more curious - much of that may be innate or cultivated through childhood. But, you can hire for this attribute. We've become so transactional that just having the conversation matters. Promoting a culture where there's actual curiosity, conversation, questioning, learning through experimentation, and accepting failure as learning - these cultural attributes are vital to transformation. People think that, through rigid control, they'll get change done faster, but you won't.

Insurance Thought Leadership

My innovation mantra for decades has been, Think Big, Start Small, Learn Fast. Tell me a bit about how you approach experimentation.

Amy Radin

You pull a few people from different departments like claims, underwriting, distribution, and put them together. Explain your vision of the future. Give them a well-defined problem to solve aligned with your vision, some time and budget, and see what they come up with, what kind of tools they need. Assess the experience, then improve upon your approach with a view toward scaling across many small teams.

When someone comes into your office and says, "I have this crazy idea," and they've got some customer insight, whether it's from a policyholder or distributor, don’t discount it. Ask, “Why don't you develop that further? Can you come back with what the next step would be to help validate your hypothesis?"

It's not about throwing a million dollars at an idea right away. Instead, it's about creating some open time, allocating a little budget for follow-up client interviews, giving permission, creating space in the organization, and encouraging people to come forward with ideas aligned to the vision.

Insurance Thought Leadership

I assume this approach should be a sort of fractal, happening not just at the top levels of an organization but at every level.

Amy Radin

It's more important to encourage the middle and lower parts of the organization to open up.

This is not about having a suggestion box or any of that nonsense. What leaders can do that's powerful is help the organization understand the vision for what we want to become. Create a framework and structure around that vision, and then you can say we want to promote experimentation to help us move and change toward it. You have to tell people where you want to go. It's about uniting people around a common sense of purpose and vision.

Insurance companies like to talk about their purpose, but it's often at such a theoretical level. You have to bring it down to the ground and help people understand what that means in claims, what that means in servicing, what that means in underwriting. Too many insurance companies treat purpose and vision as just a marketing slogan. But it's not - it's about what goes on at every level of the organization, across all functions and business units. 

You've got to frame that out to people and help make it concrete, maybe even by example, and then create some process and structure that's not heavy-handed and not hierarchical that helps people understand we think it's valuable for them to help us cultivate concepts that can move us toward our vision.

Insurance Thought Leadership

I've become a big believer in teams. When you talk about middle and lower management, one thing they can do that those in the trenches can't is to connect people. For example, if someone has an idea here and another person has an idea there, the managers can bring them together. They can mix and match, so you're not just dealing with people in finance or claims or whatever.

Amy Radin

Totally. That's why I said one of the most important roles for leaders, rather than just telling people what to do or focusing solely on reporting relationships, is to inspire and empower belief. It's about cultivating the expansion of these networks across the organization.

Insurance Thought Leadership

How do you encourage a culture that embraces failure as part of the innovation process?

Amy Radin

It's not just about saying failure is okay - you have to build that idea into your processes and how you work. When we do an experiment and don't get the ideal result, we need to talk about what happened, what we can learn from it, and how we apply those learnings to the next iteration.

Too many organizations struggle with this. I remember in one of my insurance experiences, we were trying to move more marketing activities online. We went into the market, did a test, and got a result. When we took that into a management meeting, one of the senior executives immediately said, "That's terrible!" This not only brought down the whole room's energy, but they were wrong - the result for that particular type of digital campaign was pretty good. They just weren't accustomed to seeing results for digital campaigns. And even if it was terrible, the question should have been: "Help us understand how that test was constructed, what can we learn from it, and what would the next test look like?"

There's this tendency toward a "one and done" attitude that won't work. It took Steve Jobs nine years to perfect the iPad. When a great innovation comes out, when something has its miracle moment, nobody asks how long it really took to get there, and what their struggles were.

That's the reality of how transformative change happens: iteratively, through learning from how things go in each stage of experimentation.

Insurance Thought Leadership

I love the iPad example and have written about it in some detail. The idea actually originated some 25 years before the iPad’s introduction and was embodied in a video, driven by a longtime colleague of mine, about a Knowledge Navigator in 1987. That idea kept percolating along in the labs until Jobs grabbed hold of it and, as you say, perfected it. He did another super smart thing, too. During the experimentation process, he saw that he could introduce a phone, with a smaller screen, three years before the iPad was ready. That iPhone sparked the real revolution in communication even though it wasn’t the original intent.

Amy Radin

I think there are a lot of lessons in that. Your vision is crucial, and this is where executives trained in traditional management styles often struggle. People want things to be structured in black and white, but this is not just a world of gray; it's a world of many colors, and things happen serendipitously. It's important to set a vision and understand that you're embarking on a journey where you'll explore many paths.

Setting that vision gives people permission to start down the path and avoid being incremental or sticking to current methods. Another point about why we need to change the way we change is the shift in workforce attitudes and the work environment since the pandemic. You can't just gather everyone in a meeting room, even if you wanted to.

I don't know about you, but I don't know many Gen Zers or millennials who want to be told what to do. If you want to engage today's workforce and have them do their best work, these ideas about empowerment and fostering an environment where people can pursue new ideas are crucial. If you don't offer that to your best people, they'll go elsewhere.

We have to really reframe what it means to accomplish transformational change.

Insurance Thought Leadership

Thanks so much, Amy. It’s always a pleasure.

There is a fundamental tension underlying the wildfire disaster playing out in California, and it's not going away. The tension is between climate change and human nature, as represented both in individual behavior and in the actions of our governments.

The damage from hurricanes, severe convective storms, drought and wildfires has grown even faster than expected over the past several years, and the increases show no signs of slowing. At the same time, we keep building in areas, such as along coasts and in the wildland-urban interface, that are especially vulnerable. 

And that's just the start of our behavioral problems. We aren't wired very well for planning for crises like wildfires. You're telling me I have a 2% chance of wildfire in the 10 years I'm going to own this house, and I'm supposed to spend how many tens of thousands of dollars to harden the property? Even if the math makes sense, most people will glide past the issue.

In theory, governments step in and represent all of us on issues like wildfire that we can handle collectively better than we do individually. But governments will slow roll solutions that require hard choices. Job 1 as a politician is getting reelected, so why tick off voters by letting insurance companies raise rates rapidly or not renew policies on properties that have become too risky? Why not stall as long as possible?

So we have a crisis that's accelerating, and our response is moving at the same old, snail-like pace. I'd love to wish the tension away, but I can't. I suspect we'll be wrestling with this tension for many, many years, while wringing our hands about the devastation caused by events such as the wildfires in Southern California. 

What I can do is offer a few thoughts on how we in the insurance industry can at least start to accelerate society's response, to mitigate the damage even as climate-related problems continue to proliferate and intensify. 

To be clear, I'm not saying homeowners insurance is in crisis everywhere in the U.S. — but we're not just talking California, either. A recent congressional report said Florida, Louisiana and Texas face the same sort of climate-related insurance problems. Colorado officials have said they worry their state could fall victim to the sorts of wildfire problems that afflict California. Insurance markets in Hawaii, Massachusetts, Oklahoma, and North and South Carolina are also unstable, according to a recent report.

I'm also not saying insurers have been asleep at the switch about the growing dangers of wildfires. A New Yorker article says:

"In 2019, the number of homeowners’ policies in California that were not renewed jumped by more than thirty per cent. In 2023, two giant insurers, State Farm and Allstate, announced that they would stop writing new policies for various forms of property insurance in California. State Farm said the move came in response to inflation and 'rapidly growing catastrophe exposure.' Last summer, it canceled coverage for more than fifteen hundred homes in Pacific Palisades, the wealthy enclave where the first of the L.A. blazes began."

Seven out of the 12 insurers with the biggest market share have cut coverage in California since 2022.

What I am saying is that the tension between the acceleration of climate change and the slow response caused by human nature is overwhelming the signals that insurers are sending about increasing risks. As a result, the insurance industry isn't being as effective as it could be at heading off the economic and personal devastation of climate-related catastrophes. 

What to do?

First, once the immediate danger is behind us, insurers should take the opportunity to argue for a suite of aggressive changes to the thinking about insurance in California and other states with climate-related insurance crises. This will be difficult, both because of the normal inertia and because so many people are spreading disinformation in the interest of scoring political points. (No, whatever you think of the state's policies on water and endangered fish, they didn't affect the firefighting efforts. No, however much you despise the billionaires who have bought up so much of the water rights in the Central Valley, they didn't affect the firefighting efforts. The reservoirs in the state are full or nearly fully, as usually happens during the rainy season.)

People tend to buy flood insurance after a flood and earthquake insurance after an earthquake, so we now surely have the attention of a lot of people about the growing dangers of wildfires. Let's use it. 

California has recently made some important changes to insurance regulation. Insurers can now use predictive models when pricing home insurance, letting them account for climate change rather than having to rely solely on (outdated) historical data. Insurers can also include in filings the costs they pay for reinsurance. But those changes should just be the beginning of an acknowledgment that California's rates have been artificially depressed since voters passed Proposition 103 in 1988 and that premiums need to catch up with risk.

Second, insurers should use every means at their disposal to encourage those who are rebuilding their homes to build them to more resilient standards. Mike Zukerman, CEO of CSAA, the third-largest home insurer in California, says his company "offers guaranteed renewals to customers who achieve a Wildfire Prepared Home certification from the Insurance Institute for Business and Home Safety, which mandates home hardening measures. (There are about 1,000 such homes in the entire state, according to IBHS.)" 

Building to the higher standard costs almost nothing, so let's get as many homeowners as possible to get those certifications.

Third, I'd love to build on Zillow's recent announcement that it will provide likely insurance costs up front in its listings, so prospective buyers can crank that information into their decision-making, rather than only considering insurance once they've completed the purchase. Insurance policies are annual, so, while Zillow's approach gives a homeowner valuable information, the information is just about the first year for what's likely a 30-year mortgage. We're getting better and better all the time at projecting the effects of climate change; why not provide guidance to homeowners up front about the whole 30-year lifetime?

Yes, the information will be imprecise, models will disagree and sellers will surely push back if they feel they're being maligned, but I'm idealistic enough to think there must be a way to make buyers more sophisticated at the time they're making key decisions. 

An article in Fortune says:

"Climate science can help us figure out how to live well in a warmer world. The same models that accurately anticipated rising heat and humidity, increased drought and deluge, rising oceans, bigger tropical storms, elevated wildfire risk, and weakening jet streams warned sophisticated investors away from insuring the [long-tail risks that are geting fatter]. The same research and data can help decision-makers of all kinds integrate this information into processes as diverse as city planning, building codes, mortgage underwriting (including by FNME and FMCC), and REIT valuation."

Fourth, I hope risk management consultants can help communities stress test their plans for climate-related disasters. As far as I can tell as of this writing, the big failure of government in the California disaster was that the city of Los Angeles counted on its experienced firefighters and a system of water tanks and hydrants. The approach was fine if a house is burning down, even if several are burning at once. But a whole community? Several communities? You can't fight wildfires with a few water tanks. 

Wouldn't that be useful? Come up with a simple methodology to help communities see how they'd handle a flood, a fire, a whatever? Then help them get the word out so they can better prepare, whether through a series of individual actions or through group efforts?

Chunka Mui and I have used a stress test methodology for years with corporate consulting clients and, just based on interviewing internal teams to surface concerns, have identified any number of efforts that were as clearly misguided as hoping fire hydrants could protect against wildfires.

We've also, I'm sorry to say, seen clients go ahead and spend tens of millions of dollars anyway on those brain-dead projects. One wasted billions of dollars by moving too fast into a market that, based on our devil's advocate review, was years away from being ready.

There's that human nature again.

I warned you this won't be easy.

Cheers,

Paul

Every strategic plan starts with ambition and vision, yet most of them fail or fall short. In fact, it is estimated that 90% of strategies are not successfully executed, and only a fraction of transformations hit the mark.

We are in the early days of a technology revolution that will exceed the transformative impact of electricity, the automobile and the internet. With both traditional insurance players and tech-savvy upstarts already investing billions into modernizing the industry in recent years, the rapid pace of AI development adds additional opportunities but also creates more complexity and, for some, strategic uncertainty.

Given this environment, in a highly competitive industry with compressed margins and a bumpy track record on growth, strategic missteps in the next few years could create devastating setbacks for businesses. Now, perhaps more than at any other time in a generation, it's critical that strategies and transformative projects are thoughtfully planned and brilliantly executed.

See also: How to Respond at Inflection Points

Common Reasons for Strategic Failures

The times may be changing, but the biggest reasons for failure are evergreen. We'll break down the top six reasons, but at the heart is poor execution.

1. Lack of Clear Vision and Objectives; Misalignment With Mission

Many strategic plans and initiatives fail due to the lack of a clear, actionable vision or poorly defined objectives that do not align with the company's core competencies or market reality. For example, "We must invest in and embrace AI" is not a strategy—it is a tactic. Yet many leaders are chasing the technology, without a clear objective.

2. Underestimating and Misunderstanding Disruptive Technologies

Predicting the future isn't easy, and it shows. Most business leaders tend to overestimate the impact of technology in the short term and underestimate it over the long term. Leaders often expect new technology to fix a range of problems, but unless they plan carefully and set realistic expectations, they are just digitizing many of their problems and sometimes even amplifying them. Over the longer term, technology often disrupts even the most unlikely and insulated of businesses.

Being too quick to adopt can lead to costly disappointment, while being too slow can put you at a competitive disadvantage.

3. Resistance to Change; Poor Change Management

This frustrating obstacle appears in multiple industries and environments. There are two distinct, though closely related, issues here:

First, there is likely a segment of your company who absolutely does not want your strategy or transformative project to succeed. This may manifest simply as indifference, but there are often one or more people actively working to undermine your plans. This is usually due to either (a) fear for their job or (b) fear of or unwillingness to change.

Second, companies often undervalue the impact of good change management and simply don't do enough of it, failing not only to combat the first problem but actually compounding it. When stakeholders do not clearly understand what the plan is, why it is important, how they will be affected, and other key details, the likelihood of failure skyrockets, confusion takes hold, and morale deteriorates.

4. Misalignment of Resources

If you like delays, errors, unexpected expenses, and poor morale, misaligning resources may be one of the best ways to unintentionally sabotage your plans. This comes in a variety of flavors, including not having enough people or budget allocated, having the wrong people or skills involved, bringing resources in at the wrong time, spending money in the wrong places, doing too much at once, and not prioritizing projects and resources for maximum alignment with strategy.

Having been through many strategic plans and transformational projects, I can assure you improper resourcing will always result in a greater cost and negative impact to the company.

5. Lack of Agile Development and Inability (or Unwillingness) to Pivot

Executing a significant strategy shift or transformational project often takes years, not months. Given the fierce competition for market share and the lightning-fast pace of innovation, your strategic plans may be outdated before you've even finished launching.

Leaders who refuse to embrace agile execution will almost certainly find themselves at a competitive disadvantage and at high risk for delays, rework, or completely missing the market opportunity. Leaders must be willing and able to adjust course and adapt during the process of executing their strategy.

6. Lack of Follow-Through and Continuing Improvement

Strategic execution is rarely a one-and-done effort. Failure to complete "day two" items, monitor results, and make continuing improvements has been the death of countless "successful" projects. Too often, senior leaders are eager to move on to the next big thing or bring a premature end to the project funding in an attempt to harvest the savings. Clients don't receive the full benefits promised, shareholders don't see the profits expected, and employees bear the brunt of systems and processes that "almost" do what was intended.

See also: 5 Key Mistakes in Long-Term Planning

Case Studies

1. Early in a career, one might participate in a "paperless transition" project. It could be a significant effort involving new teams, systems, and processes. Imagine the surprise when some teams were using just as much paper as before—and some even more! The capabilities of the new imaging system were not well understood, and some users resorted to printing documents to review, highlight, and annotate. Others were simply uncomfortable or struggled with visibility on their screens.

The problem? Key stakeholders on the front lines weren't properly engaged, and the change management and training were poorly executed. The solution? Additional training and the introduction of portrait-oriented monitors. Only then did paper usage begin to drop, as the mistakes were addressed, and lessons were learned for the future.

2, During the implementation phase, a groundbreaking project delivered a smooth launch of the desired capabilities despite inadequate resourcing. However, despite millions of dollars and years of effort into the project, the resulting sales were well below expectations, and as a result, the platform's costs were unsustainable.

The problem? The original objectives weren't aligned with the mission, and the strategy had been developed in an echo chamber without sufficient input from broader stakeholders. The solution? Because key elements weren't aligned to the core mission, they were repurposed and successfully implemented elsewhere in the organization, and the initiative was closed down.

Turning Strategy Into Results

The ability to make an honest assessment of both your past results and your current situation is the first step to improving your odds of success. Based on statistics about strategic failures, it's almost certain that your organization—no matter how capable—needs improvement in one or more areas. An assessment requires more than a report from the project manager; the C-suite should actively engage with stakeholders at all levels, particularly those on the front lines, along with customers and key partners, to gain an unfiltered, well-rounded perspective.

You may not like what you find—but that's how you learn and adjust.

The challenges of strategic execution are significant, but they are not insurmountable. By addressing common pitfalls—such as misaligned objectives, resistance to change, and inadequate resourcing—you can dramatically improve your chances of success. It begins with a clear vision and actionable objectives, continues with thoughtful planning and agile execution, and demands relentless follow-through and a commitment to continuous improvement.

In a world where technological disruption is rewriting the rules, businesses must rise to the occasion. Strategies that balance ambition with adaptability, supported by strong leaders and engaged teams, can drive transformation and deliver results. The road from vision to victory is rarely straightforward, but with focus, resilience, and the right execution, it is absolutely achievable.

Despite advances in technology, medical billing errors remain alarmingly prevalent.

75% of medical bills contain coding errors, creating a ripple effect of financial inefficiencies and regulatory risks. The impact extends beyond providers and insurers: 45% of consumers encountered faulty bills last year, and many chose not to dispute them, overwhelmed by opaque rules and coverage exclusions.

This decay of trust signals an urgent need for change. Artificial intelligence and human-in-the-loop machine learning (HITL/ML) offer a path forward. By streamlining claims processing and reducing errors, these technologies can enhance accuracy and compliance, restoring transparency and confidence in the healthcare system for all stakeholders — from patients to policymakers.

See also: Using Data Science to End Surprise Billing

Financial and Regulatory Impact of Medical Billing Errors

Medical billing errors burden healthcare providers and insurers with significant financial challenges, exacerbating inefficiencies across the system. Hospitals and health systems spent $19.7 billion attempting to overturn denied claims, reflecting the immense cost of addressing billing inaccuracies.

These errors disproportionately affect higher-cost treatments, with the average denied claim tied to charges around $14,000 or more. Additionally, 15% of claims submitted to private payers are denied, including many with prior authorization. For providers, each denial represents not only lost revenue but also the added expense of multiple rounds of appeals; more than half of denied claims are eventually overturned.

Regulatory compliance adds another layer of complexity, particularly as payer policies grow more burdensome. A recent survey by the American Hospital Association revealed that 84% of hospitals reported rising costs to comply with insurer policies, with 95% noting that staff now dedicate more time to prior authorization processes. These administrative burdens increase financial strain while introducing delays in patient care, undermining trust in the system. Moreover, gaps in interagency collaboration, such as those seen between the Centers for Medicare & Medicaid Services and the Veterans Health Administration, have led to costly errors, including $128 million in duplicate payments. 

These challenges highlight the urgency for industry leaders to adopt solutions addressing financial and regulatory inefficiencies. AI and machine learning offer transformative potential by automating claims processing, identifying discrepancies and ensuring compliance with complex billing regulations. By leveraging these technologies, healthcare organizations can reduce costly errors, streamline operations and refocus resources on delivering high-quality patient care.

Transforming Revenue Cycles With AI and ML

Revenue Cycle Management: AI and machine learning improve data quality and accuracy, providing insights that optimize financial performance for insurers and healthcare providers. These tools analyze billing data, coding trends and reimbursement patterns, uncovering potential up-coding or down-coding scenarios and improving charge capture accuracy, ensuring providers are compensated fairly.

These insights empower healthcare organizations to make informed decisions about billing strategies and payer negotiations. By addressing inefficiencies and pinpointing areas for improvement, AI-driven analytics not only boost revenue but also enhance the overall financial stability of healthcare institutions.

AI-Driven Compliance and Risk Reduction: Compliance with complex healthcare regulations and payer guidelines is a critical challenge in medical billing. AI automates compliance-related and routine tasks — checking claim status, posting payments — by continuously updating coding guidelines, regulatory changes and reimbursement policies. It reduces the risk of errors and associated penalties, protecting organizations from costly regulatory violations. By integrating AI systems, healthcare providers can efficiently navigate intricate regulatory landscapes, maintaining operational integrity and safeguarding their reputation while optimizing financial outcomes.

Fraud, Waste and Abuse: AI identifies and prevents fraudulent activities within the healthcare revenue cycle. It detects suspicious patterns in accounts payable transactions, such as unauthorized vendor payments or schemes involving bogus claims — in some cases reaching up to $2 billion in fraudulent claims to Medicaid and Medicare. AI systems monitor for anomalies, flagging inconsistencies for review and mitigating fraud risks before they escalate. Simultaneously, AI can reduce billing errors by meticulously analyzing claims for inconsistencies or missing codes, minimizing denials and ensuring accurate reimbursements. This dual capability not only protects financial resources but also strengthens trust and transparency within the healthcare ecosystem.

Furthermore, AI can enhance the patient's experience and satisfaction. By personalizing communication and optimizing billing processes, ML algorithms can tailor payment plans to individual needs, fostering transparency and trust between patients and providers. These patient-centered improvements raise satisfaction rates.

See also: How Data & AI Can Shape Group Benefits

Ensuring Ethical AI Implementation With HITL/ML

With the growing integration of AI in medical billing, establishing comprehensive ethical frameworks and regulatory guidelines is essential to ensure fairness and equity. One significant concern is the potential for algorithmic bias, which can arise from incomplete or unrepresentative data. Inaccurate or biased outcomes in medical billing, claims processing or patient care can exacerbate existing disparities and erode trust in the system. These frameworks must address critical issues such as privacy, fairness, transparency and accountability to safeguard patient rights and promote equitable practices.

HITL/ML frameworks address this challenge by combining AI's efficiency with human oversight. Skilled professionals validate and refine AI outputs, ensuring decisions align with ethical standards and real-world nuances. This collaboration introduces a critical layer of accountability, reducing the risk of biased or incorrect outcomes. Moreover, HITL/ML systems foster transparency, allowing healthcare organizations to explain AI-driven decisions clearly.

HITL/ML frameworks also play a pivotal role in preventing AI hallucinations — instances where the AI generates inaccurate or misleading information. By incorporating human expertise into the machine learning pipeline, these frameworks enable real-time validation and correction of AI results.

Collaboration among healthcare organizations, technology developers and global regulatory bodies is crucial to creating standards that promote responsible AI use. These guidelines should mandate the protection of patient data, unbiased billing decisions and clear communication of AI processes. This openness builds patient and stakeholder trust, ensuring AI technologies are applied responsibly and equitably. This approach mitigates potential risks, reinforcing the integrity of AI-driven processes and ensuring that technological advancements benefit all stakeholders without compromising ethical standards.

The property/casualty insurance litigation industry maintains the largest negotiation network in the world. Tens of thousands of insurance claim professionals partner with more than 30,000 defense attorneys to reach the most appropriate resolutions on more than 750,000 litigated claims annually. 

Because our company’s mission is to help insurance litigation defense teams be more successful, we are obsessed with data that paints a clear picture of the litigation environment in which a litigated file is being defended. 

Why? Because the litigation environment defines the true BATNA, or Best Alternative to a Negotiated Agreement. And in our world of litigation, the only BATNA available to us is taking a case to trial. 

The litigation environment is composed of many factors. The venue, the plaintiff attorney, the judge – all these entities have track records, and that information is critical to quantifying the BATNA, establishing settlement values, deciding which cases to try, and not overpaying on files. 

Doing this well yields significant short- and long-term benefit. The amounts paid on litigated files drive the case values on pre-litigated files. Given this broad impact on all negotiated settlements (the #1 expense for liability insurers), the tort litigation environment is arguably a core driver of the pricing and cost structure of the carrier itself.  

The challenge for insurers is that they only see their slice of the litigation data, commensurate with their market share, which for the average insurer is 1% or less. In contrast, our industry-wide database gives us an unprecedented understanding of the litigation environment to understand the BATNA, including how it is affected by specific venues and attorneys.

To better understand whether and how trial verdicts have changed in the post-COVID period, we analyzed 11,000 validated plaintiff tort verdicts in our database. This article summarizes our findings and discusses implications for both understanding the BATNA and trial selection at a tactical, actionable level. 

Pre- and Post-COVID Verdict Analysis - Methodology

To better understand the litigation environments in the pre- and post-COVID timeframes, we analyzed 11,000 validated plaintiff verdicts in our database, broken into three distinct periods: 

• Pre-COVID (2015-2019)
• COVID (2020-2021)
• Post-COVID (2022-2023)

We examined verdict size (both including and excluding punitive damages), as well as non-economic damages award levels across these time frames. 

Our methodology included: 

• The use of detailed actual jury verdict numbers
• A non-economic performance assessment using a machine learning model
• Rigorous bottoms-up analysis, controlled for inflation and other factors

The Relevance of Non-Economic Award Levels

We focus significantly on non-economic damages performance because it is one of the purest indicators, in our view, of the social inflation pressures that juries bring to bear. We all know what the economic damages are in a file; the unknown is what a jury might do with the non-economic award. 

To maximize insight into non-economic performance, we use a machine learning model, as this enables us to account for changes in injury severity, plaintiff age, and a host of other factors. Using this model also enables us to isolate venue influences from individual attorney influences, and we think defense teams are stronger when they can distinguish between those two. 

Data that shows which plaintiff attorneys are better at extracting higher non-economic awards, and which venues are more likely to give them, is critically important to understanding the BATNA on a specific case.  

Our Most Important Finding: Granularity Matters

Our most important observation from this detailed analysis is that granularity matters. A lot. 

Although we arrive at some sweeping conclusions about jury verdicts and non-economic performance in the post-COVID timeframe (see below), what stood out more for us was how granular the data needs to be to be helpful in understanding the litigation environment. 

More specifically, two things are very clear: 

• Geography matters
• The attorney matters

Just focusing on geography for a minute, our data shows that the most plaintiff-favorable large venue in Maryland (Prince George’s) is more favorable to the defense than the most defense-favorable large venue in the state of Connecticut (Hartford). This may be irrelevant to a litigation executive with all their files in Maryland, but it is highly relevant to an organization with litigated files in both places. 

In the same vein, but within a single state, non-economic damages performance in Los Angeles County is significantly higher than San Diego and Orange Counties. These differences suggest that thinking about the case as being “in California” may be less helpful than understanding the litigation environment in each county. 

On the plaintiff attorney front, we all know that specific attorneys are simply better at extracting high non-economic awards from juries than other attorneys. Understanding the specific verdict track records of these attorneys enables defense teams to quantify more accurately file-specific BATNAs. (As an aside, those track records can also be compared with the accomplishments that plaintiff attorneys list on their websites, which can be quite amusing). 

See also: Insurance Industry Faces Major Changes in 2025

Example – 10 Large Counties

In our analysis we examined 10 large litigious counties nationally in our database and compared their non-economic model results. 

The results emphasized for us how difficult (or at least unhelpful) it is to make sweeping generalizations about the COVID and post-COVID timeframes. 

During the actual COVID period (2020-2021) itself, more of these 10 counties went down than up. In fact, two went “way down” while one went “way up.” 

Key:

• Way down = more than 40%
• Down = between 15% and 40%
• Neutral = within 15%
• Up = between 15% and 40%
• Way up = more than 40%

Our point about the granularity is that, while overall non-economic performance has increased post-COVID, that may not be relevant to you if your case is in a jurisdiction where that performance has actually decreased. 

Example – Texas and New York

Results were also mixed across counties within the same state. Texas demonstrated the most extremes. For two of the largest counties, one went way down while the other went way up. 

Other states were not so extreme. Across the three largest counties in New York, one remained neutral, one went up, and one went way down. To say that “New York as a whole has gotten worse” would be inaccurate. 

Example – Philadelphia County

Other venues have experienced dramatic changes in non-economic model performance. As an example, prior to COVID, Philadelphia County was somewhat favorable to the defense. During the pre-COVID period, this venue produced a -27% non-economic model result, meaning that it under-performed the machine learning model by 27%. 

However, in the post-COVID period, Philadelphia County is at +75% and a scary place for the defense.  

Findings: The Post-COVID Litigation Environment

With the important caveats listed above about the need to understand the litigation environment at a very granular level, the key findings produced during our analysis included: 

Verdict Size

• With punitive damages excluded, average verdict sizes rose 28% during COVID and rose 179% from the pre-COVID period (2015-2019) to the post-COVID period (2022-2023), nearly tripling over that timeframe.
• Applying statistical methods to account for outliers, the values were 18% and 107%, respectively
• When punitive damages are included in the results, average verdict sizes have risen by 12% over the COVID timeframe and have increased by 274% when compared with the pre-COVID period.  

The cause of this is mixed. From the pre-COVID to post-COVID period, there was both a rise in case severity (based on medical specials and injury severities) and a rise in non-economic damages performance 

Non-Economic Performance 

• Average non-economic performance has increased by 37% over the COVID timeframe and has increased by 40% when compared with the pre-Covid period.
• The state of Texas is responsible for about half of this increase. Average non-economic performance increased by a whopping 211% during COVID, only retracting slightly in the post-COVID period (2022-2023) for an overall rise of 165%. This was despite near-zero changes in medical specials or injury severity during the COVID and post-COVID periods. Again, this was not consistent across the state.
• Excluding Texas, average non-economic performance was flat during COVID and then increased by 21% post-COVID (2022-2023).

See also: Does the P&C Insurance Cycle No Longer Exist?

Moving from broad generalizations to actionable intelligence

Historically, we have tended to speak about the litigation environment at a macro level. We are inundated with bad news stories about runaway juries and detailed reports reminding us that nuclear verdicts are a growing problem. While this information is very important for highlighting generalized social trends and setting the stage for broader societal policy reform, it is less helpful to a defense team facing a trucking lawsuit in San Diego County.  

From our vantage point, focusing only on the macro (nuclear verdicts) is having a chilling effect on our industry. We are taking fewer cases to trial, are paying more in settlements, and have been unable to diminish litigation costs. Attorney representation on pre-litigated files has skyrocketed. 

On the other side of the battlefield, the plaintiff bar is investing heavily in technology to make itself even more effective. We have written before about EvenUp Law, a company that secured more than $220 million in investment in 18 months, has achieved unicorn status, and claims thousands of plaintiff firms as their clients. The use of data that maximizes trial and settlement amounts is attractive to the plaintiff bar, to say the least. 

We believe it is time for the defense to do the same, and, in light of our findings, there is no question that the BATNAs we face across our litigation portfolios are changing.  

For us, the more relevant question is a fundamental one about how we respond as an industry. 

One option is to feel powerfulness and blame the problem on others, by saying that juries have gone crazy and the plaintiff bar is beating us. This option doesn’t accomplish much and simply becomes a self-fulfilling prophecy. We cannot think of any litigation executive with whom we interact who finds this option attractive. 

Option two is to respond to the plaintiff bar by taking a more data-driven plan of action that improves litigation outcomes. This option stems from the knowledge that a deep understanding of the litigation environment in which a case resides yields a better quantification of the true BATNA on the file. Further, it recognizes that our perception of the BATNA translates to values on pre-litigated files as well, and therefore has wide-ranging implications.

Litigation settlements involve “bargaining under the shadow of trial,” which requires an in-depth understanding of the BATNA (verdict risk), which requires an in-depth understanding of the litigation environment. As in other areas of insurance, values need to reflect risk, and to understand risk we need data.

Option two requires three things:  

• Being highly granular in our litigation environment analysis
• Using detailed data about venue and geographic differences
• Leveraging a deep understanding of actual track record (instead of reputation), for both plaintiff attorneys and venues

These actions will help us to make more informed, data-driven, settlement decisions. They will help us to better understand which cases to try, and to make higher-quality decisions overall. 

Said another way, they will help us to reclaim our BATNAs. 

2024 was a turbulent year for the insurance industry, characterized by inflation, a devastating series of natural disasters, and increasingly advanced, sometimes creative, fraudulent tactics. Despite these challenges, the year also brought new opportunities through technological advancements and initial steps toward digital transformation and successful AI adoption.  

As we look ahead to 2025, I believe three major trends will continue to shape the sector's trajectory: effective, more practical implementation of AI, the adoption of aggressive fraud detection tools, and greater collaboration among carriers.

AI implementation will focus on practical realities

2024 saw professionals, regardless of industry, push the envelope on AI integration, seeking to identify the areas with the most significant potential value. Now, 2025 will be about scaling the AI pipe dreams back and instead using it to automate everyday tasks. The insurance industry, a sector that’s historically been held prisoner to manual and time-consuming processes, is poised to benefit greatly from this approach. While 77% of insurance companies tried to make up for past hesitancies by launching themselves onto the AI hype bandwagon in 2024, only 5% are currently set to reap tangible benefits due to prioritizing speed and scalability over strategic implementation.

In 2025, the most successful AI strategies will be those that embrace a more balanced and deliberate approach, focusing on areas of the business that deliver the highest ROI. For insurers, this involves automating manual, time-intensive tasks while keeping a human in the loop for larger decision-making tasks. One area where AI implementation can deliver significant benefits is in monitoring claimants' online activity. Instead of relying on overburdened adjusters to conduct labor-intensive searches manually, AI can perform the same task in seconds, saving adjusters a minimum of 15 minutes per claim. Once AI flags any suspicious or concerning activity, adjusters can then simply review and approve it, saving time, improving accuracy, and ensuring honest policyholders receive the prompt payouts they deserve.

Successful AI adoption isn’t about being the most innovative; it’s about being innovative in the right ways. Insurers need to be thoughtful when implementing AI across their business, ensuring they’re balancing moving the innovation needle forward with realistic business value.

See also: 10 Tech Breakthroughs Likely in 2025

Fraud in the spotlight

Insurance fraud, already a $300 billion problem (equivalent to 10 Hurricane Helene-sized disasters occurring every year), is set to worsen in 2025. Drivers include a staggering 30% of people under 45 who don’t view insurance fraud as a crime (equating to approximately 50 million Americans), combined with a sharp rise in exaggerated claims, often exacerbated by attorneys who prioritize maximizing settlements for their own benefit rather than acting in the claimant's best interest. While deepfakes and AI-generated fraud tend to occupy the spotlight, most fraud occurring today stems from neglecting the basics and relying on little to no tools beyond an investigator’s intuition.

In 2025, carriers will be required to take more proactive, data-driven measures to combat the growing fraud epidemic, as current methods remain largely ineffective. We’ll see the most successful insurers leverage tools that automate the review of open injury claims, compiling real-time, evidence-based data to inform their decision-making and streamline the time-consuming tasks that are stopping them from finding fraud in real time.

See also: Insurance Industry Faces Major Changes in 2025

Carriers band together in the fight against fraud

While leveraging fraud detection tools is a critical aspect of combating fraud, it will still take more to flatten the curve. A key focus for Carpe Data in 2025 is finding ways for carriers to collaborate and share data in a more meaningful way – what we’re calling “the network effect.” By sharing critical intelligence, patterns and data, insurers can more effectively identify and disrupt organized fraudulent activity that has exploited gaps in an individual carrier’s defense. The idea is that insurers become part of a trusted partner exchange where they have access to previously generated alerts or information on policyholders that have been run through the system. The result is alerts on suspicious activity being shared more promptly and increased access to historical injury information so we’re able to provide better care recommendations and facilitate fairer claims settlements. 

In 2025, I’m optimistic that insurers will prioritize shared success over competition, ultimately lowering costs for consumers and delivering greater value across the industry. 

The insurance industry is at a crossroads. Modernization isn't a choice — it's a necessity. Yet, as firms race toward the future, they face a pivotal decision: Should they build or purchase entirely new platforms or "wrap" their existing legacy systems with modern technology? The answer isn't straightforward. Both approaches have their merits, risks and complexities. What's clear is that the stakes couldn't be higher. Conversion risks are large, and advanced technologies driven by artificial intelligence are poised to tackle the legacy transformation problem.

Let's delve into the debate and help you navigate the path forward.

Legacy Systems: The Double-Edged Sword

Legacy systems are the backbone of many insurance operations. They've served reliably for decades, processing claims, underwriting policies and managing customer data. Yet they're also infamous for their rigidity, inefficiency and inability to adapt to new technologies. Many insurers hesitate to part with these systems because of the cost, time and risk involved in full-scale replacements.

But here's the reality: clinging to outdated systems is like driving a horse-drawn carriage on a highway. You might get there eventually, but you'll be outrun by modern competitors driving high-speed cars.

See also: Legacy Systems: Modernize or Overhaul?

New Builds: Starting Fresh with a Clean Slate

Building a new platform from the ground up is the dream scenario for many. Imagine a sleek, cloud-native system, designed to leverage AI, automation and data analytics seamlessly. A new build promises:

• Flexibility: Tailor-made solutions that can adapt to changing business needs.
• Speed: Faster integration with emerging technologies and third-party solutions.
• Scalability: The ability to grow alongside your business and handle increasing data volumes.

However, the dream comes with challenges. A new build is time-intensive and costly and carries conversion risk. Data migration can be a nightmare, with the potential for loss, corruption or downtime that disrupts operations. Employee adoption can also be slow, as new workflows require training and adjustment.

Wrappers: Breathing New Life into Old Systems

For firms wary of the risks and costs of starting fresh, wrapping existing legacy systems with modern application programming interfaces (APIs) and other interfaces offers a compelling alternative. This approach allows insurers to:

• Extend the Life of Legacy Systems: By integrating modern tools, firms can enhance the capabilities of older platforms without a full overhaul.
• Reduce Costs: Wrappers are generally more affordable than building a new system from scratch.
• Accelerate Deployment: Wrappers can be implemented faster, ensuring quicker ROI and less disruption.

But this approach has its limits. Wrapping a legacy system doesn't eliminate its inherent flaws. The underlying system remains brittle, and scalability can be an issue. Over time, the patchwork of old and new may become more cumbersome to manage, potentially leading to higher long-term costs.

See also: Where Next for Insurance Ecosystems?

Conversion - The Elephant in the Room

No matter which path you choose, conversion risk is a major consideration. Migrating data, ensuring compatibility and maintaining operations during the transition are monumental tasks. This is where careful planning and strong partnerships become critical. Insurers must:

• Conduct Thorough Assessments: Evaluate the current state of your legacy systems and the specific needs of your business.
• Choose the Right Partners: Collaborate with technology providers experienced in minimizing conversion risk.
• Test and Validate: Use phased rollouts, sandbox testing and pilot programs to identify potential pitfalls before going live.

Disruption is another key factor. The technology landscape is evolving rapidly, with advancements like quantum computing and advanced AI knocking at the door. Insurers that delay modernization risk being blindsided by competitors who leverage these breakthroughs to deliver faster, smarter and more personalized services.

The Case for Bold Action

Whether you choose a new build or a wrapper, the key is to act decisively. Staying stagnant is not an option. The insurance industry is on the brink of transformation, and the firms that thrive will be those that balance innovation with practicality.

What Lies Ahead

As you weigh your modernization options, consider your long-term goals. Are you seeking to simply keep up with the competition, or do you want to lead the charge? Your decision today will shape your ability to compete in a world where customer expectations are higher, and the pace of change is faster than ever.

Despite the average cost of a ransomware attack reaching $4.9 million in 2024, the cyber insurance market remains soft, with premium rates falling and capacity still abundant.

What's driving this trend? It's a combination of factors. Insurers are writing broader and more adaptive policies in response to evolving cyber threats, helping to maintain market stability and keep premiums competitive. At the same time, many organizations have scaled their cybersecurity defenses, making it less risky for insurers to write cyber policies with higher limits.

Yet cyberattacks continue to evolve, introducing new mechanisms and extortion tactics that challenge traditional approaches to risk management. Continued policy innovation is essential to address the full spectrum of consequences of modern cyber incidents.

The current soft market provides underwriters with a unique opportunity to test new coverage models while deepening their market insights to effectively mitigate emerging risks.

See also: The Evolving Landscape of Cybersecurity

Recent cyber events haven't swayed the soft cyber insurance market

The most significant cybersecurity incident of 2024 was the CrowdStrike software glitch, which led to a major tech outage that grounded airlines and disrupted patient care at hospitals. But it barely registered for insurers.

Because the culprit was a routine software update — and not a malicious actor — the impact was limited to specific operational disruptions. Additionally, the quick resolution of the issue and its classification outside the typical scope of cyber claims allowed insurers to avoid systemic losses.

However, things could go differently next time. The next widespread cybersecurity event could lead to a surge in claims severity that dramatically shifts market conditions.

Now is the time for underwriters, brokers and insureds to take advantage of the soft market to get ahead of emerging trends and identify creative solutions to offset evolving risks. With the cyber insurance landscape evolving rapidly, proactive measures today can make all the difference when the next major incident hits.

The current market conditions present a unique opportunity to explore new coverage models, strengthen client relationships and position both insureds and insurers to respond with resilience to future threats.

Keep an eye on the following trends and opportunities as 2025 unfolds so you can stay flexible and adaptable, and help your insureds do the same.

1. Insurers will continue to write broad cyber policies.

Organizations face an average of 1,300 cyberattacks per week, a record. However, companies have also gotten better at thwarting these threats.

Logins that require multifactor authentication are now table stakes at many organizations. And three-quarters of companies with cyber insurance invested in strengthening their defenses against ransomware and other cyberattacks to qualify for coverage. That has helped keep rates from rising alongside attack frequency.

As a result, the soft market will likely persist for the foreseeable future, with insurers continuing to offer broader coverage and higher limits. Many policies now include provisions for both first- and third-party losses, encompassing everything from ransomware payments to regulatory liabilities. For insureds, this means greater flexibility and protection — but it also underscores the need to carefully review policy terms to ensure adequate coverage for emerging risks.

How to prepare: Evaluate your current cyber portfolio and explore opportunities to expand coverage options. Ensure that your policy provisions align with emerging risks and consider working closely with specialist brokers who are on the frontlines of new trends and exposures.

2. Ransomware attacks will continue to evolve.

Traditional ransomware attacks in which bad actors encrypt stolen data and demand payment in exchange for the decryption key have become less effective. Many organizations now have robust backup systems, so they can simply restore their data without paying off the attacker.

This has caused cybercriminals to pivot tactics, prioritizing data theft and extortion attacks that focus on stealing personal and sensitive information and threatening to release it publicly. Examples could include company financial records or damaging personal information about executives or clients.

Consequently, insurers are seeing more demand for cyber policies that include coverage for reputation and crisis management costs. Demand for customized policies is especially high among professional services firms. In particular, law firms and wealth management advisers are more likely to be targeted with data theft and extortion attacks due to the sensitive nature of their work.

How to prepare: Stay ahead of evolving ransomware tactics by developing comprehensive policies that address both traditional and emerging ransomware risks. Schedule regular meetings with your brokers, underwriters and breach response teams to share information on claim trends and active cybercriminal groups.

3. AI will make social engineering attacks more efficient.

Social engineering attacks that exploit trust and human error will grow more prolific in 2025. Generative AI has made it easier for scammers to create automated fraud campaigns that are more targeted and convincing.

For example, a classic social engineering attack formula is for scammers to pose as a CEO asking an employee to initiate a funds transfer. Using generative AI, the attacker can more effectively mimic the CEO's communication style and target employees with highly personalized messages that reference specific projects or job duties, making employees more likely to fall victim to the scam.

A higher share of social engineering attacks are also focused on property theft, which makes them even harder for employees to recognize and report. In these scams, fraudsters order expensive goods or equipment, pick it up without making payment and vanish without a trace.

We've already seen an uptick in physical property losses being added to cyber policies, expanding the scope of what cyber insurance covers and requiring underwriters to adapt policies that address blended threats. It's too early to predict how else generative AI-enabled scams might affect the cyber insurance market, but insurers should continue to monitor events closely and adapt their coverage options and limits as risks evolve.

How to prepare: Equip your team with reliable market insights to stay informed about the evolving impact of AI threats on claims so you can adapt your policy terms. Additionally, emphasize to insureds the importance of employee training to recognize social engineering attacks, including those driven by AI.

See also: Trends in Data Breach and Privacy Risk

Staying ahead in 2025 hinges on creative solutions and actionable market data

As the soft cyber market continues, insureds will look to eliminate supplements and consolidate coverage under broader policies with improved limits and policy language. Agents and brokers should work closely with clients to ensure policies include expanded provisions for the wide-ranging consequences of modern cyber incidents.

Meanwhile, underwriters will take advantage of the soft market to develop insurance products that address both emerging and traditional cyber threats. Access to robust market insights will be critical for maintaining flexibility to adapt as the threat landscape evolves.

The time to address emerging cyber risks is before the next major incident occurs. Planning and innovative policy design will be key to staying resilient in the face of increasingly sophisticated attacks.