It's frustrating when a transformative new technology is held back because the infrastructure can't yet support it.

Think of electric vehicles (EVs), which are caught in a Catch-22 of sorts. Many people are reluctant to buy them until there are more public chargers available, and charging networks are not being built until there are more EVs to use them.

Genetic testing faces a similar problem. It has the potential to transform healthcare through precision diagnostics and therapies, but it's being held back by health plans' insufficient programs for managing it. Caught by surprise by the rapid growth in the number and applicability of tests, plans have been struggling to handle them through their routine testing programs.

It's not working. More than 180,000 genetic tests are on the market, with an average of 10 added daily. CPT coding has not kept up. There are about 500 CPT codes for roughly 360 times as many tests. This results in a system that is slow, inefficient, expensive, and susceptible to waste, fraud, and abuse. Health plans need management programs built specifically for genetic testing, which will only grow in volume and complexity.

As health plans work to improve their handling of genetic testing, whether internally or with a lab benefits management firm, they should ensure that the following nine elements are incorporated into their genetic testing benefits framework.

1. Accreditation and regulatory compliance: Utilization management is necessary to ensure patients receive the proper care and required services without overusing resources. Accreditation by respected agencies like the National Committee for Quality Assurance and URAC and good standing with state regulatory agencies help ensure that organizations making these decisions follow evidence-based best practices.

2. Coverage criteria based on science: The volume of genetic tests is exploding, and maintaining a current understanding of the clinical science and the appropriate coverage criteria documented in clinical policies requires frequent review. To ensure the latest science and clinical medicine are codified in medical policies, experienced working laboratorians, pathologists, and geneticists should perform a comprehensive scientific and clinical review of the newest literature annually or as the science warrants. If health plans lack the internal resources to do so, they should partner with a business that specializes in it.

3. Optimized laboratory network and quality testing: Not all labs are created equal. Some perform better than others. Quality evaluations, results, and audits can identify these high-performing labs. Once the trusted labs have been designated, plans can promote these labs to patients, providers, and even tiered networks with increased benefits to those who use higher-tier labs. In return, the labs that benefit from promotion can offer unit price reductions.

Genetic testing must meet appropriate scientific and clinical standards beyond just coverage criteria. Guaranteeing that labs have completed sufficient scientific, technical, and clinical validations is essential to ensure the information provided to the clinician informs patients' healthcare needs. Plans should have systems to evaluate labs beyond Clinical Laboratory Improvement Amendments requirements and the quality of specific mutation analysis tests.

4. Prevention of fraud, waste, and abuse: The looser the operating framework for testing, the more likely fraud, waste, and abuse will occur. Integrating test specificity and enhanced claim-to-authorization matching processes will reduce that and save plans money.

5. Claim-to-authorization match during adjudication: In many cases, the criterion for matching allows broad, non-specific matches, which contributes to inappropriate payments, stopped claims for manual review, delays in claims payment, and the potential for fraud. Increasing the flexibility and specificity of matching criteria alleviates those challenges.

6. Continuing utilization management vs. claims adjudication: Plans should continually evaluate laboratory tests, required coverage criteria, and historical laboratory performance to determine when a specific laboratory or a collection of tests should be adjudicated during the claims process without prior authorization (PA) or continue utilization reviews in a PA process. Additional controls, such as regular auditing of laboratories to ensure compliance, are recommended.

7. Enhanced provider education and experience: In many cases, laboratories perform the same or similar genetic tests while billing with different combinations of CPT codes. While coding tools like MolDX and Concert Genetics help, they must be embedded in comprehensive programs to be effective. Establishing coding requirements for each test at each laboratory allows streamlined operations and more comparative analytics within the plan. The test specificity concepts discussed provide a clean, robust, and efficient means to overcome potential code challenges and clarify provider billing requirements. Health plans adopting a specificity method for test identification will see increased efficiency, improved laboratory and physician satisfaction, and reduced potential fraudulent billing.

8. Expedited review of prior authorizations: PA can be frustrating and time-consuming for all parties. It's why the federal government and states are creating requirements limiting PA requirements. A "gold card" program that eliminates PA for top-performing labs can simplify administration, improve patient outcomes, and increase savings for health plans, labs, and patients. A lab benefits manager identifies and supervises the network of top labs, reducing the burden on payers.

9. Managing demand from biomarker legislation: As more states pass biomarker legislation, plans need a lab benefits management program to ensure patients receive the right tests. Alignment with nationally recognized guidelines and evidence-backed clinical utility is necessary to ensure that these mandates don't inadvertently hinder innovation or inflate healthcare costs.

Genetic testing will become an even more critical—and beneficial—part of healthcare. Plans that establish separate, science-based policies for managing it will realize the maximum benefits for patients, providers, and themselves.

Banks have an inherent advantage over insurers when it comes to learning how to use AI most effectively, Aditi Subbarao of Instabase says in this interview with Ron Rock of JobsOhio. Banks simply have more data because their interactions with customers are deeper and more frequent, and banks’ data is organized more accessibly. 

So what should insurers learn from banks?

Subbarao says insurers should learn to be braver, especially in using AI for risk management, fraud detection and improving the customer experience. Saying you need to clean your data first is an excuse, she says.

She also says insurers should think about setting up a federation of AI agents, which can pull data from the many silos where insurers store it and provide a clear understanding of a client’s situation. 

That would go a long way to eliminating the data advantage that banks now enjoy.

Ron Rock 

What inspired you to get into AI and be in the financial services industry with AI.

Aditi Subbarao 

I must say, I'm really, really fortunate, because the way I see it, AI is very much kind of the center of activity and innovation in the industry at the moment. Having spent more than 12 years in financial services myself, Ron, I have first-hand experienced the problems and the difficulties that most people working there face in trying to find the information that you need to have to better serve your clients and to do your job better. If there is one thing that any banker or even insurance professional would think of it is, "I wish I knew how to do something. I wish I knew what would happen. I wish I knew." 

And I think AI is the one thing that has the potential to change so many things in the financial services and insurance space, just given the amount of data that they need to deal with. And that was very much the driver behind getting into the field of AI and then helping apply that into a space which I know and love.

Ron Rock 

Where in the financial services space do you see the biggest potential for AI?

Aditi Subbarao 

I actually think the biggest potential exists across the financial services space. AI can genuinely completely transform and revolutionize how practically every single function, every single role, is done in that space. 

However, if I had to pick a few areas, I would say this typically lies in risk management, fraud detection and customer experience. 

So being able to access, process, analyze and then act upon the huge realms of data from across the market, across trades, across customers or across like so many different sources, and then using that to understand your risk better; and then take proactive actions to manage that risk is going to completely change how risk management updates. 

On the fraud side, AI can now analyze and even predict a lot of different occurrences that human beings would have found impossible to, especially at the speed at which they need to be done; like how we now have instant payments. How can you keep monitoring the regulations that you need to on that? 

And the last piece is customer experience. We already see banks and organizations that are genuinely customizing their products and services, their overall experience that the customers are getting. 

I think these are the three areas that would be top of the line for me in terms of impact in F.S. [financial services].

Ron Rock 

So obviously banking is usually at the forefront. When you compare financial services, banking is at the forefront, insurance a little bit lacking. So why do you feel that banking is taking hold of AI quicker? 

Aditi Subbarao 

That's a very interesting question, you know, and something I've thought about for a long time. And now that I have the opportunity of working across both industries, I would again say there would be sort of three reasons. 

The first one is the kind of data that banking has. It's just so much more and so much more frequent. For example, one billion payments are made by the banking industry every single day, and we're not even talking about the deposits or the loans or the investments or trades. It's just payments. On the flip side, claims, which is the most common transaction in the insurance industry, it's orders of magnitude lower. So there's just more data.

A lot of this data tends to be structured, especially because a lot of financial services transactions are either exchange traded or cleared by clearing houses and so on. So banking has had the advantage of much more data, much more frequently, in a more manageable format. 

You can use this data to train AI models and then also apply AI on top of it, so that's one major advantage. 

The other thing, which is slightly nonobvious, is almost the business model or the organizational structure. And what I mean by that is, in banking, the asset and liability sides of the business are very closely linked together. Whether you're taking deposits and then making loans, or whether you're making investments and then managing the risk, it's all together. It's very closely coupled. Whereas with insurance, somebody who's working on underwriting risk or processing claims is so far removed from the investment side of the business that it doesn't really work very seamlessly, and therefore finding the right applications and using AI so that it can create impact also gets very siloed.

And the last piece, which is in fact something that I find most fascinating, is just the variety of functions that a bank provides and how closely they are embedded in their customers’ lives. I'll ask you a question: On your phone, how often do you open your banking app? 

Ron Rock 

Daily. Probably twice, three times a day. 

Aditi Subbarao 

Do you have an app from your insurance company on your phone? 

Ron Rock 

I do.

Aditi Subbarao 

How often do you open it? 

Ron Rock 

Once every couple of months.

Aditi Subbarao

I think banks are just so much more closely embedded in the day-to-day as compared to insurance companies, so naturally you have far more opportunities and far more applications for AI. I think that's where the advantage has been, but it has been so encouraging to see, especially at ITC, that I think that gap is going to start closing very quickly.

Ron Rock 

What can insurance companies learn from the banking industry and how they've adopted AI?

Aditi Subbarao 

I'd say this falls into two pieces. The first is slightly the more cultural aspect of it. I would almost say insurance needs to be a bit braver, take a bit more risk. And this is so counterintuitive, because the very DNA of insurance is risk aversive, avoiding risk, protecting from risk. But especially with AI and generative AI and the new advances that are happening there, you need to be brave. You need to go and do stuff which hasn't been done before. You need to experiment. You need to try things out. So what if they fail? Try it and move on. And I think insurance needs to kind of make that mindset shift a little bit, like banking has done and started to do. That would be my first piece of advice, just go and try it and experiment more. 

The second piece of advice is kind of what we referred to before, which is, I think insurance has always been more about "here is the protection we can give you; take it on our terms," whereas banking has now oriented a lot more to "what does my customer need, at what point, and how do I structure it that way?" I think the more that insurance starts becoming customer-centric, the more that it starts creating new products and services based on what protection people actually need, the more they will find the natural drive to start adopting AI, because you cannot do it without AI. So those would be my two pieces of recommendation, or like areas where insurance can learn from banking. 

Ron Rock 

For emerging technologies in this space, there's a lot going on. I mean, you see it across the expo. What are some of the emerging technologies that you think are going to impact the industry?

Aditi Subbarao

I will narrow down your question, if you don't mind, and again, focus on Gen AI, because that's what I do. Even within that space, I'd say, searching across all the data, irrespective of where it lives: Being able to now do that is something we're already seeing live in action. It doesn't matter whether you have really complex variable pieces of data, like a PDF sitting in somebody's shared drive who left two years ago, or like an Excel sheet sitting on some cloud database, you can now literally ask a natural language question to query across all of those sources of data. I think enterprise search is a very powerful technology, which is now already starting to be used.

The second piece that I am really excited about is agentic AI. There you have autonomous AI agents who can now take decisions, perform their actions, and even figure out what the next best action is all by themselves. I think that has the power to change the game completely, to use a cliche. But the best part of it is we are now at a stage where those AI agents will go to the data rather than the data coming to them. So we can operate AI in a federated manner. Especially for industries like insurance, where data is sensitive, it lives in multiple different places. You can't move it across jurisdictions. All of that will be tackled because we now have the ability to do federated AI agents.

Ron Rock 

So finally, a lot of leaders in the financial services space are looking for the next best thing, looking for how to transform their organizations. What advice could you give them?

Aditi Subbarao

I'll give you one sentence, which is the correct "textbook" answer, and then I'll give you the other sentence, which is the sort of "come on, guys” answer. 

The textbook answer here is, find your why, like the genuine reason why you want to do it, not just because your competitor is doing it, or not just because your marketing department expects some sound bites to provide to your customers, but what is driving you to do it. Then find the right use cases where you can actually see the value, to be able to demonstrate it and see it and feel it across the business, to energize the people. Then find the right partners and the right ecosystem to go do it with. The what, the where and the with whom are what you need to find out. 

But there's also the "come on" answer here, which is something I feel more strongly about. One of the biggest obstacles to organizations getting started with AI has been data, and a lot of leaders come to us and say, "Well, I can't get started on AI because my data is not in order. I first need to tidy up my data." In my opinion, that's a chicken-and-egg situation. It's an excuse, because you can actually use AI to clean up your data, to find you the data that will then go back into the AI to actually access all of these records that are sitting across your organization that you think you can't do anything about because they're not clean, but use AI to clean them up. It's almost like, use the AI to get your data shop in order, and then once it is in order, use the AI to give you the insights and make the actions that you need to take. 

It's almost like my advice would be, nothing is holding you back. If there's a will, there's a way, 

Ron Rock 

Thanks, Aditi. 

In today’s complex risk landscape, organizations need unified, efficient responses to interconnected threats. This Boosting Productivity eBook explores the rising demand for efficiency, the impact of silos and disconnected systems, and how a single-platform approach can drive engagement, streamline operations, and deliver actionable risk insights—without adding headcount.

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Sponsored by: Origami Risk

Businesses have ranked political risks and violence as a top 10 global risk for the third straight year, according to the Allianz Risk Barometer 2025, demonstrating that it has become a key concern for companies of all sizes. According to a new report from Allianz Commercial, civil unrest ranks as the biggest concern for more than 50% of company respondents globally, reflecting the fact that incidents are increasing and lasting longer.

Not including continuing social unrest in the Balkans and Türkiye, there have been over 800 significant anti-government protests since 2017 in more than 150 countries, with more than 160 events in 2024 alone – with 18% of protests lasting more than three months.

Following the "super election year" in 2024, policy changes by governments will continue to be trigger factors for protests and flashpoints in many countries, as could any economic hardships that result from tariff wars. In addition, an increase in terrorist attacks from religious and political extremists – motivated by both far-right and -left ideologies – is also a major concern for businesses. Companies need to adapt to volatile and uncertain geopolitical conditions to avoid negative surprises and mitigate risks.

Politics is increasingly perceived as being dominated by populism, blame and division, geopolitics by nationalism and a changing world order, and economics by mismanagement, corruption, and continually rising disparity between the rich and the rest. Political violence can affect businesses in many ways. In addition to endangering the safety of employees and customers, the violence can cause those in the immediate vicinity to suffer business interruption losses and material damage to property or assets.

Civil unrest now the major political violence concern

Businesses are more concerned about the disruptive impact of anti-social behavior on their operations than that of any other political violence and terrorism exposure. The impact of civil unrest or strikes, riots and civil commotion (SRCC) activity also ranks as the top concern in countries such as Colombia, France, South Africa, the U.K. and the U.S. Just in the top 20 countries for frequency of protest and riot activity around the world during 2024, there were more than 80,000 incidents, with India, the U.S., France, Germany, Türkiye and Spain among the hotspots, according to Allianz Research.

This view is shared by insurers, which have seen the SRCC peril increase in frequency and severity in recent years. Events, including riots in Chile and South Africa, have contributed to insured losses well in excess of $10 billion over the past decade, surpassing other levels of political violence and terrorism insurance claims. In certain hotspot territories, losses can rival or surpass those from natural catastrophes, while in others, although the direct impact may be minor, events can still trigger long-lasting changes in societies.

All kinds of civil unrest and protest activity remain a problem. Contributing factors such as high inflation, wealth inequality, food and fuel prices, climate anxieties and concerns about civil liberties or perceived assaults on democracy have not eased.

Religious and political terrorism on the rise

The increasing frequency of plots and attacks from Islamist groups and individuals, as well as supporters of far-right and far-left movements, are among the factors driving the complex global landscape. A growing concern is the Islamist terrorism threat in Europe, with an increasing number of attacks or plots happening over the last 12 months.

Terrorist attacks jumped by 63% in the West, with Europe most affected, as attacks doubled to 67. At the same time, analysis shows there were more than 100 reported terrorism and right-wing extremist incidents during 2024, driven primarily by events in the U.S., followed by Germany. Meanwhile, far-left extremists are targeting individuals or companies who they see as contributing to issues such as climate change and inequality.

Businesses need to be alive to the shapeshifting nature of political violence risk and protect their people and property by ensuring safe and robust business continuity planning is in place. Companies also need to review their insurance. Property policies may cover political violence claims in some cases, but specialist protection is also available. Businesses with multi-country exposures are showing a greater interest in political violence coverage, but there is also greater engagement from the small and medium-sized enterprises (SME) about these risks, a true reflection of increasing concern.

To read the Allianz Commercial Political Violence and Civil Unrest Trends report, click here.

Water perils not related to weather are a part of all insurance books of business. But our environment is experiencing what seems to be increasingly unpredictable and extreme weather events that can create havoc on those same books of business. From strong ice storms and blizzards to prolonged arctic blasts, these conditions disrupt daily life, damage infrastructure, and challenge business continuity. In this evolving landscape, organizations must consider adopting monitoring solutions to anticipate and mitigate weather-related risks.

Recent events have demonstrated that severe cold now affects regions across the entire country, from the Northeast to the Gulf Coast. Real-time monitoring is essential for managing these emerging risks effectively.

A consensus has emerged among insurance carriers leading the way in IoT adoption: Connected insurance represents a societal good. This shift is driven by several key benefits:

• A reduction in expected losses
• Improved alignment of rates with risks
• Increased efficiency in claims processing

These advantages may allow a significant number of policyholders to benefit from lower premiums while maintaining the technical balance of insurance portfolios. As a result, carriers can achieve sustainable profitability while expanding the availability and affordability of coverage.

HSB (part of Munich Re) and the IoT Insurance Observatory previously explored the industry's progress in integrating IoT-driven protection in their article, "Creating the Tipping Point for Insurance IoT: A Playbook for the Future." This article outlined the advantages of a connected insurance portfolio for carriers, policyholders, and society at large.

HSB has deployed hundreds of thousands of sensors across U.S. properties. This connected portfolio enables the identification of key trends affecting insured properties while demonstrating the effectiveness of proactive protection strategies.

The Role of Networked Sensor Technologies (IoT)

Most would agree that IoT sensor technologies are critical in mitigating the impact of extreme winter conditions. Their effectiveness is built on a sophisticated ecosystem of capabilities that work together to detect adverse conditions, alert relevant parties, and enable swift action to prevent potentially costly damages.

Key components of an effective IoT approach include:

• High-Quality Sensors: These frontline devices detect water leaks, temperature fluctuations, and flow deviations. To function reliably, sensors must be highly accurate, durable, and resistant to extreme conditions.
• Real-Time Monitoring and Alerts: Continuous data transmission enables instant notifications to relevant stakeholders via SMS, email, and mobile apps.
• Responsible personnel: Alerts are only half of the equation—there must be personnel who will act in response.
• Robust Connectivity: Reliable communication through Wi-Fi, cellular, or LoRaWAN networks ensures redundancy—even during power outages.
• Advanced Analytics: Predictive algorithms identify risk trends and potential failures well in advance. Over time, these insights inform maintenance and risk management strategies.
• User-Friendly Interfaces: Intuitive dashboards focus attention on the most critical, actionable information, complemented by training and support for end users.

Notable Weather Events: A Sensor-Driven Perspective

Several extreme weather events have underscored the value of IoT-based monitoring, with Winter Storm Elliott (December 2022) and Winter Storm Enzo (January 2025) serving as key case studies.

Winter Storm Elliott (December 2022)

Winter Storm Elliott was a historic extratropical cyclone that disrupted nearly every U.S. state, including typically warm regions such as Texas and Florida. In the Midwest and Northeast, wind chills dropped as low as –30°F.

HSB's sensor network detected freezing conditions in Western states first, then tracked the storm's eastward progression. In areas unaccustomed to extreme cold (e.g., Texas), sensor alerts surged by 500% above normal levels. These timely alerts helped prevent damages worth millions of dollars by enabling preventive actions.

Winter Storm Enzo (January 2025)

From Jan. 18–25, 2025, a Siberian Express polar vortex, followed by Winter Storm Enzo, brought record-breaking cold across the U.S., affecting over 70 million people and leaving more than 75% of the country in freezing conditions.

In southern Texas and Louisiana, temperatures plummeted into single digits, with Baton Rouge's airport recording 7°F—the lowest temperature in 95 years. New Orleans experienced up to 10 inches of snow, matching a record set in 1895. For the first time, blizzard warnings were issued for coastal Louisiana and Texas.

During this period, HSB's sensor network issued approximately 9,000 alerts, with 90% related to freeze conditions. The peak of the storm (Jan. 21–22) saw 3,760 alerts in just 48 hours. Jan. 21 alone recorded 2,000 alerts—10 times the normal daily average.

The most significant impacts were observed in Mississippi, Alabama, and South Carolina, where alert volumes soared up to 40 times their normal daily levels. Thanks to these real-time alerts, policyholders were able to take preventive action, helping to avert potentially millions of dollars in water damage losses from frozen pipes. This event demonstrated a strong return on investment, with many programs exceeding a 200% ROI. This ROI is calculated by comparing the savings from this specific event to the total annual investment of IoT.

The Insurance Angle

The insurance industry must continue scaling these measures to maximize the prevention benefits demonstrated by HSB's experience. As IoT-driven solutions mature, they provide primary carriers and policyholders with critical tools to strengthen safety programs across commercial and residential property portfolios.

According to research by the IoT Insurance Observatory, carriers are pursuing several go-to-market strategies to integrate connected protection solutions:

• Complimentary Protection Solutions: Some carriers offer IoT protection services at no cost to existing policyholders. While the insurance contract remains unchanged, the insurer absorbs the service cost, expecting the reduction in claims to outweigh the investment.
• Certified Protection Solutions: Policyholders purchase and install certified protection systems, and in return, carriers provide annual premium credits. Over multiple coverage periods, the cost savings generate a positive return on investment for policyholders.
• Mandated Protection Solutions: Certain insurance products now require specific IoT technologies to qualify for coverage or receive favorable terms. This approach integrates technology directly into the insurance offering, fundamentally reshaping the industry's value proposition.

Even brokers and agents are recognizing the advantages of connected insurance. In the commercial property sector, some intermediaries now advise clients to:

• Invest in Protection Solutions: Businesses are encouraged to install mitigation technologies tailored to their specific risks.
• Adjust Deductibles for Mitigated Risks: Policyholders can opt for higher deductibles on covered perils, offsetting the cost of IoT protection with reduced annual premiums.

This strategy ensures that the investment in prevention technology is recouped through premium reductions while minimizing claims—creating a win-win scenario for insurers and policyholders alike.

Conclusion

As climate patterns continue to shift unpredictably, the insurance industry must embrace solutions to safeguard policyholders and mitigate losses. The increasing severity of winter storms, as evidenced by Winter Storm Elliott and Winter Storm Enzo, underscores the critical role of IoT sensor technology in protecting properties, reducing financial impact, and enhancing resilience.

HSB's deployment of sensor networks has demonstrated the tangible benefits of real-time monitoring, allowing carriers to see success in both weather- and non-weather-related damages. The average return for $1 invested in an IoT program is $8. These successes highlight the need for broader industry adoption, where insurers, brokers, and policyholders can collaboratively scale preventive measures to create a more resilient insurance ecosystem.

The future of property insurance lies in connected protection. By leveraging IoT-driven insights, insurers can enhance underwriting precision, reduce claim frequency, and offer more sustainable coverage options. Whether through complimentary protection, certified solutions, or mandated requirements, the integration of IoT technology is reshaping the industry's approach to risk management.

To fully realize these benefits, carriers must accelerate adoption, refine implementation strategies, and drive market education. With sensor-based monitoring, the industry can shift from a reactive claims model to a preventive protection paradigm—one that benefits insurers, businesses, and society as a whole.

This article was originally published at Carrier Management.

Political violence coverage (strikes, riots and civil commotion, or SRCC, plus terrorism and war) is currently sitting in a shifting market. Losses due to SRCC have increased by 3,000% (!) as per Swiss Re, largely due to increasing geopolitical instability and the arrival of social media. Riots in France in June 2023 are estimated to have cost the insurance market close to $780 million, and the 2024 July/August riots in the U.K. (which started and quickly spread due to misinformation and disinformation on social media) have estimated insurance losses of $320 million (which are assumed to have been limited due to the 2016 U.K. Riot Compensation Act). Terrorism coverage follows the same path, as recent losses have led to hardening markets, resulting in challenged capacity and increased premiums.

War coverage is somewhat different, with policies often containing flexibility for coverage to be withdrawn within a specific time if a threat escalates in certain industries. Even so, the 2022 Russia-Ukraine war was preceded by warnings of an imminent invasion from the Americans, while some European intelligence agencies failed to predict the onset of the war (which could have affected how many policies remained in place or were altered in time in favor of the insurer). The Ukraine war will affect insurance policies and premiums, and in October 2022 the Organization for Economic Co-operation and Development (OECD) estimated overall insurance industry losses would reach $20.6 billion.

What coverage is actually needed?

Looking specifically at the terrorism threat, do you need to buy coverage for the full value of your asset, including business interruption? This obviously depends on what kind of asset you are considering, its location, its defense lines and your risk appetite (which might include lenders' requirements). As an example, would a large-scale wind farm with a total insured value of $1 billion need to buy full value terrorism coverage? The analysis starts by quantifying the risk. There are plenty of ways to determine the risk of a specific scenario occurring, and a couple of commercially available solutions for the insurance industry exist, although they currently come with geographical limitations to their capabilities. You could argue that your estimated maximum loss (EML) for a terrorism scenario is a total loss of the asset, in a scenario that might not be fully realistic or with an extremely low probability (e.g., an aircraft impact, a 20,000-pound bomb or something similar).

The rationale for instead using a probable maximum loss (PML) approach as the trigger is that rather than purchasing terrorism coverage for the full value of assets and associated business interruption costs, alternative worst-case scenarios that do not result in the total loss of the asset are considered. This can potentially enable coverage to be tailored to the more probable events. Before that can be done, a detailed threat assessment should be completed to determine which specific scenarios should be evaluated in the PML study.

Threat Assessments

The threat assessment needs to include a full analysis of the current political situation, including historical data, which can be found from both open source and credible commercial providers. For a terrorism event, hostile actors and potential resources can be identified and used as input to the PML study for the asset. The assets actual defense lines will also help to identify the most probable scenario and how that scenario would play out in the unlikely event of an attack. There are plenty of both national and international standards in place that provide guidelines for a choice of scenario (e.g., FEMA 452), as well as theoretical bomb size. This is typically expressed in TNT equivalent, i.e., the amount of energy released in an explosion.

Blast Damage Modeling

Once the scenario has been chosen, a blast damage model can be used to determine the effects of a specific event, depending on the location of the bomb. This is a key aspect often overlooked and related to the assets defense lines. By analyzing the resulting incident overpressure, one can determine the structural damage to property. An example of an analysis done on an energy facility using the tool ALERT can be seen below.

As another example, a hotel with bollards in place outside the hotel entrance might reduce the effects of a terrorist attack significantly, as the attacker will be hindered from detonating the bomb inside the hotel. That could not just save lives but also prevent a full collapse of the building. Bollards have the benefit of always being functional, which can't be said about other protective systems, like drone defense systems, which have shown weaknesses in recent attacks on energy facilities in the Middle East. These are just two examples of security details that will affect potential scenarios and subsequent choice of insurance coverage.

To summarize:

1. Risk environments are highly volatile and territorial. The insured should look at each political violence peril in detail to determine how much coverage is required to balance capital versus risk appetite.
2. Political violence coverage can be advisable based on a targeted scenario approach.
3. A tailored PML approach offers the possibility to analyze how various safety and security measures could reduce the exposure.
4. Detailed blast damage is a critical part of the assessment process.

References:

S. Collins, "Swiss Re warns of rising riot losses," Commercial Risk, 16 October 2024.

L. S. Howard, "Insured Losses From UK Riots Will Be Manageable, With Claims Below £250M: Report," Insurance Journal, 13 August 2024.

F. Churchill, "Political violence market hardening amid rising losses: AGCS," Insurance Day, 23 February 2023.

F. Churchill, "Defining 'unprecedented' in the world of political violence," Insurance Day, 19 August 2024.

OECD, "Impact of the Russian invasion of Ukraine on insurance markets," Business and Finance Policy Papers, Paris, 2022.

S. Kalin et S. Westall, "Costly Saudi defences prove no match for drones, cruise missiles," Reuters, 2019.

As 2025 unfolds, one persistent challenge remains at the forefront: the rising cost of employee healthcare. Traditional health insurance plans continue to grow more expensive, pushing employers to seek innovative solutions to maintain both affordability and quality. Captive insurance companies are emerging as a compelling option, offering businesses a way to take control of healthcare expenses while addressing the evolving needs of their workforce. This article explores the trends shaping employee healthcare in 2025 and why businesses are finding that captive insurance can play a pivotal role.

Rising Healthcare Costs: A Pressing Challenge for 2025

Average health insurance premiums have risen by 7% in 2025, marking four consecutive years of increases, according to a report by Lending Tree. This trend is driven by increasing medical costs, expanded coverage requirements, and economic uncertainty. Employers, facing tighter budgets and a competitive labor market, are under pressure to provide attractive benefits without overburdening their finances.

The Aon 2024 Global Risk Management Survey underscores  this issue, reporting a marked increase in the use of captives for managing employee benefits risks, particularly healthcare. Employers are recognizing that the traditional approach to health insurance may no longer be sustainable in the face of mounting costs.

A Solution for Modern Employee Healthcare Challenges

Captive insurance companies offer an innovative approach to managing employee healthcare. These entities allow businesses to self-insure their workforce by creating a subsidiary that assumes responsibility for healthcare coverage. By doing so, employers gain greater control over plan design, cost management, and provider networks, leading to customized and often more affordable solutions.

Key benefits of captive insurance for employee healthcare include:

• Cost Savings: By cutting out traditional insurance carriers and negotiating directly with healthcare providers, businesses can reduce administrative costs and premiums.
• Enhanced Coverage: Captives enable employers to tailor plans to meet the unique needs of their workforce, often resulting in more comprehensive coverage options.
• Risk Mitigation: Through reinsurance, captives can protect against high-cost claims, ensuring financial stability even in the face of unforeseen medical expenses.
• Data-Driven Insights: Captives provide employers with detailed claims data, empowering them to implement wellness initiatives and identify cost-saving opportunities.

The Impact of the 2025 Presidency on Employer-Sponsored Healthcare

The recent change in presidency has introduced new dynamics to the healthcare landscape. Early signals suggest potential shifts in regulatory policies affecting employer-sponsored healthcare programs. These changes are likely to emphasize affordability, transparency, and employee access, with potential tax incentives for businesses that invest in innovative healthcare solutions like captives.

Employers must remain vigilant as new legislation could affect how healthcare benefits are structured and funded. Captive insurance companies offer the flexibility to adapt quickly to regulatory changes, allowing businesses to stay compliant while maintaining control over costs and plan design.

Trends to Watch in 2025

Several emerging trends are shaping the future of employee healthcare and are likely to drive increased adoption of captive insurance:

1. Increased Focus on Mental Health and Wellness: Employers are recognizing the importance of holistic health benefits, including mental health coverage and wellness programs. A survey by Wellable Labs found 80% of employers surveyed plan to increase their investments in employee mental health. Captives allow businesses to integrate these elements seamlessly into their healthcare plans.
2. Customization and Flexibility: As remote and hybrid workforces continue to become the norm, employees expect benefits that cater to diverse needs and geographic locations. Captives enable tailored solutions that address these complexities.
3. Technology-Driven Healthcare: Telemedicine, wearable health devices and data analytics are transforming how healthcare is delivered and managed. Captives have the flexibility to leverage these technologies to improve outcomes and control costs.
4. Regulatory Changes: With new regulations expected to affect employer-sponsored health plans in 2025, captives offer businesses a way to adapt quickly and maintain compliance.

Barriers to Adoption and How to Overcome Them

Despite their advantages, captives are not without challenges. Establishing a captive requires upfront investment, expertise and careful planning. Companies with fewer than 75 employees may find it difficult to achieve the scale needed for financial viability. However, as more businesses recognize the long-term benefits, these barriers are being addressed through:

• Partnerships with Experienced Brokers and Captive Managers: Brokers and captive insurance management companies specializing in captives can guide businesses through the setup process and connect them with reinsurance providers.
• Collaborative Models: Group captives, where multiple employers share the risk, are gaining popularity as a way to make this approach accessible to smaller organizations.
• Education and Awareness: As awareness of captives grows, businesses are better equipped to weigh the costs and benefits and make informed decisions.

Preparing for the Future

The year 2025 promises to be a turning point for employee healthcare. Businesses that explore innovative solutions, such as captive insurance, will be better positioned to attract and retain top talent while controlling costs. Captives offer not only financial advantages but also the flexibility to adapt to a rapidly changing healthcare landscape.

As the challenges of rising premiums, evolving employee expectations, and shifting regulations persist, captives provide a forward-thinking solution that aligns with the needs of modern businesses. By investing in this approach, companies can secure a healthier, more stable future for both their workforce and their bottom line.

Artificial intelligence is set to transform the insurance industry. According to one study, 99% of insurers are either already investing or making plans to invest in Generative AI (GenAI).

They're targeting ways to streamline operations, improve decision-making and enhance customer service. The opportunity is clear: One study found that GenAI could reduce payouts by between 3% and 4%, and drive a 20-30% reduction in loss-adjustment expenses in claims alone.

Yet intent does not guarantee success. Insurers are not investing in AI to secure small gains, but that is often what happens because they start with off-the-shelf AI models.

The limitations of AI models

These services deliver incremental benefits, and there is certainly value in that. What they do not offer is a fundamental change in how firms work and operate.

The reason is that these off-the-shelf models are often positioned as quick, plug-and-play services that need little time to integrate. They might work well on simple, repetitive tasks such as answering internal queries but struggle on more nuanced, complex work such as underwriting, claims processing, and fraud protection.

At the heart of these limitations is data quality. Generic solutions are trained on generic datasets lacking industry- or use case-specific context, and as a result, deliver generic responses. They also risk providing outdated and incorrect information, hurting customer satisfaction and increasing compliance and regulatory issues.

Can models be improved?

There are ways to tackle these challenges. Techniques including retrieval augmented generation (RAG) and fine-tuning do allow insurers to adjust performance:

● RAG involves engineering prompts using specific knowledge to provide context

● Fine-tuning deploys private data to teach models how to respond to prompts

These approaches can enhance accuracy, but they require insurers to have high levels of internal AI literacy. The success of RAG and fine-tuning efforts is closely linked to having subject matter experts who can work on prompts, know the right data to include in training, and review output quality. In other words, it is resource-intensive for relatively little gain; AI remains an assistant to human decision-making.

Ultimately, even off-the-shelf models that have been enhanced through RAG or fine-tuning are only transformative at an application or service level. They can accelerate processes, but what can be achieved is limited by what humans themselves can accomplish.

The real transformation – AI agents

The real opportunity is found in agentic AI, software that performs tasks autonomously with at most limited human intervention. Agents make decisions, plan and learn from new information to complete work defined by clear instructions, delivering focused and precise execution.

They adapt and learn in real time, rather than needing to be retrained regularly. As such, once deployed, they remain aligned with current business needs and industry conditions, ensuring reliability and adaptability.

What sets agents apart from off-the-shelf models is that as well as completing the task, agents can redesign processes to work more effectively.

For instance, a customer has a car accident and needs to make a claim. The traditional process will have been shaped by a human workforce and will likely involve multiple steps, all of which require different information, with no chance of progressing until the previous step has been completed. As a result, a decision can take weeks, if not months, as all parties are consulted.

With an agent-led process, the same information will still be required, but it could all be gathered simultaneously from multiple sources and assessed in real time. It does not matter whether it is incident details, imagery, vehicle value, historic claims data, or the cost of a replacement; the agent can continually gather and review to make a decision in days if not hours.

Complete transformation with full-task automation

This is full-task automation. It allows insurance companies to not just get more work done, with higher levels of accuracy, but to transform how they operate in ways in which they previously never had the time or resources to do. They can:

• Scrutinize every claim like it was the only one they received that day
• Predict risk with deeper levels of accuracy
• Personalize products to a degree that makes the customer feel like they have been created just for them
• Be confident that the potential for fraudulent claims is hugely reduced

AI agents will have a truly transformative effect on insurance, but only if they are deployed at scale. One agent is a pilot; hundreds is a transformation.

To achieve that requires an enterprise-wide AI infrastructure that supports autonomous operations. This needs to ensure that AI agents can integrate with existing systems, operate autonomously, and allow subject matter experts to configure AI agents according to their specific business objectives.

Investing in hundreds of agents may seem like a huge investment, but it is not; right now, agents are good enough to start taking ownership of simple tasks, and they are continually learning. A year from now, they will be 10 times better at 1/100th of the cost. The cost barriers to entry are dropping dramatically.

That also means that competitors will be using them. Can a firm compete against other providers that deploy agents alongside human teams of specialists?

Unlocking operational transformation

AI models, procured off the shelf, will not transform insurance. They will drive incremental benefits, and if deployed at scale those benefits may improve the bottom line by a percent or two. They will not completely overhaul processes that have been designed and built to accommodate the limitations of human workforces.

Only agents can deliver the operational level transformation insurers need, when AI no longer assists teams but takes full responsibility for tasks. By adopting autonomous agents, insurers will be in a stronger position to unlock the opportunities AI offers.

In today's globalized economy, businesses face numerous challenges, including tariffs and fluctuating supply prices. Trade credit insurance is a critical tool for protecting businesses engaged in international trade and mergers and acquisitions (M&A) against these uncertainties. It provides protection against non-payment risks, ensuring financial stability during uncertain times. This article delves into how trade credit insurance mitigates risks from tariffs and fluctuating supply prices and the strategic role it plays in M&A transactions.

Managing Tariffs and Supply Price Fluctuations

Protection Against Non-Payment

When tariffs are imposed, not only does the cost of importing goods rise, but so does the cost of those goods themselves. This makes it significantly harder for buyers to pay the agreed-upon amounts and to meet their payment terms. Many businesses face delayed or non-payment for goods from companies unable to afford the tariffs. Trade credit insurance can cover the seller if the buyer is unable to pay due to these price increases and can help businesses maintain their cash flow and financial stability despite economic challenges.

Assessing Buyer Risk

Trade credit insurers assess buyers' financial stability before transactions occur, helping businesses understand the risk involved. This is particularly important when tariffs raise the cost of doing business with foreign customers or suppliers and in industries with volatile commodity prices. These risk assessments provide peace of mind, allowing businesses to maintain their cash flow even if customers face payment delays or defaults.

Enhancing Financing and Cash Flow

Trade credit insurance helps businesses secure better financing options, as lenders view it as a risk mitigation tool. This can be particularly valuable when dealing with international trade where tariff and supply price volatility can affect cash flow. It ensures that, even if a customer defaults on a payment due to financial strain caused by tariffs or rising supply costs, the business can recover a significant portion of the amount owed.

Role in M&A Transactions

Trade credit insurance can play a vital role in M&A by mitigating risks associated with the buyer's or seller's receivables and improving the financial stability of the parties involved.

Mitigating Credit Risk

In M&A, trade credit insurance protects against the risk of uncollected receivables for both buyers and sellers.

If the company being acquired has significant accounts receivable, trade credit insurance can protect the buyer against the risk that those receivables may not be collected. For example, if the target company has customers who owe large sums, and those customers default or face financial difficulty, the insurer covers the losses. This reduces the buyer's concern about the quality of the receivables when evaluating the value of the target company, giving them confidence that these risks are covered, ensuring smoother financial integration after the acquisition.

Enhancing Valuation and Financing

While insurance can lead to higher valuations, it also eases financing for buyers, as lenders are more willing to provide funds knowing the risk of default is mitigated. This stability is crucial for securing working capital post-transaction.

Having trade credit insurance can increase the valuation of the target company by ensuring that a certain portion of receivables is protected against non-payment. It helps the buyer assess the true value of the target company's financial assets, making the target more attractive by reducing the perceived financial risk.

Ensuring Continuity and Reducing Disputes

Trade credit insurance supports business continuity post-acquisition by ensuring the customer base remains stable and reducing disputes over the quality of receivables.

Trade credit insurance ensures business continuity post-acquisition by stabilizing customer relationships and covering future payment defaults. It also reduces disputes, providing protection if there are concerns about outstanding payments or the quality of the target company's receivables. This facilitates smoother negotiations and integration. It also ensures both parties are covered if there is a default post-acquisition. For example, the buyer may demand that the seller take on the risk of bad debts from the receivables, and trade credit insurance can help facilitate this process.

In addition, trade credit insurance can ensure that the seller's customer base remains stable post-acquisition. If the target company has long-standing relationships with customers, the buyer may be worried that any disruption in those relationships could affect future revenue streams. Trade credit insurance provides the buyer reassurance by covering potential future customer payment defaults.

Reducing Escrow Needs

In M&A deals, escrow accounts are often set up for contingencies like bad debts. Trade credit insurance can reduce the need for escrow by assuring that receivables are covered in case of non-payment, simplifying the transaction process.

Trade credit insurance provides a safety net that mitigates risks from tariffs and volatile supply prices, enhances the value of target companies in M&A transactions, and improves the financial stability of both buyers and sellers. By fostering smoother transactions, reducing post-acquisition risks, and enabling more favorable financing terms, trade credit insurance plays a vital role in ensuring business continuity and growth in an unpredictable economic landscape.

In the complex world of insurance underwriting, mental health presents a growing challenge. The stigma surrounding mental health may or may not be slowly dissipating, but insurers continue to face a critical question: How can they accurately assess mental health risks while providing a positive customer experience?

A study by Reinsurance Group of America (RGA) offers compelling answers, leveraging behavioral science to transform the disclosure process.

The mental health disclosure dilemma

Certain mental health conditions can affect mortality and morbidity outcomes, making accurate disclosures crucial for risk assessment. However, the persistent stigma and confusion surrounding mental health often leads to reluctance in sharing this information. RGA's 2023 Mental Health Survey highlighted this challenge, with 55% of insurers reporting difficulties in underwriting and managing mental health-related claims.

The crux of the problem lies not only in applicants' hesitancy about disclosing but also in the very design of the questions they face. Traditional approaches often fall short, creating ambiguity and emotional discomfort that hinder accurate responses.

Five key behavioral science findings

RGA's behavioral science team conducted an extensive experiment involving 4,049 participants from the U.S. and Australia. The study tested various techniques to improve how customers interpret, process, and ultimately answer mental health questions. The results were striking, offering a new paradigm for insurance underwriting.

The study revealed five key findings:

1. Specificity encourages disclosure

Providing a specific list of mental health conditions increased disclosure rates 17%. For example, instead of asking, "Have you ever been diagnosed with, suffered from, sought medical advice for, or received treatments for any mental health condition? Some examples include anxiety, post-traumatic stress, depression, or schizophrenia," an altered question that asks "Have you ever been diagnosed with, suffered from, sought medical advice for, or received treatments for any of these mental health conditions," followed by a list of 12 possibilities, yielded a more accurate yes/no response.

This approach reduced cognitive load, making it easier for applicants to recall and process information. Surprisingly, this more detailed question only took an average of six seconds longer to complete, with no negative impact on customer experience.

2. Normalizing mental health issues increases openness

Adding a de-stigmatizing statement that normalizes reporting mental health challenges boosted disclosure rates by an additional 10%.

This statement reads, "It is increasingly accepted by people everywhere that recognizing and taking care of our mental health is important. In fact, a recent study showed that the number of people reporting mental health conditions has increased by 20% since 2014, and many adults now take active steps to manage their mental health."

This simple addition increased openness and did not hurt overall user experience.

Better still, pairing this statement with a list of specific conditions noted in the first key finding added only 12 seconds to completion time.

3. Segmenting stigma enhances detailed disclosures

Separating mental health conditions into distinct questions based on associated stigma levels increased the likelihood of participants disclosing multiple conditions. This approach improved disclosure rates for both highly stigmatized conditions, such as schizophrenia, and less stigmatized ones, such as stress and sleep disorders.

4. Balancing detail and emotional comfort helps

While detailed disclosures are valuable for underwriters, they can be emotionally challenging for customers. The study found no difference in disclosure rates between asking about "any conditions" vs. specific conditions. However, participants reported feeling more embarrassed when asked about specific conditions, highlighting the importance of emotional context in question design.

5. AI is an unexpected ally

Intriguingly, half of participants self-reported that an automated chatbot would be their most comfortable channel for disclosing mental health conditions. This preference aligns with psychological distance theory, suggesting that non-human interfaces may provide a more comfortable environment for sharing sensitive information.

Implications for the insurance industry

These findings have far-reaching implications for insurance underwriting and beyond. By incorporating behavioral science principles into question design, insurers can:

• Improve the accuracy of risk assessments
• Enhance the customer experience during the application process
• Potentially increase uptake of insurance products by making the process less daunting

Moreover, these insights can be applied to other sensitive areas of the insurance journey, such as claims forms and personalized claims conversations.

The future: A human-centered approach

As the insurance industry evolves, embracing a human-centered approach to underwriting becomes increasingly crucial. By understanding the cognitive and emotional factors that influence disclosure, insurers can create more effective, empathetic processes that benefit both the company and the customer.

The possibility of future integration of AI and chatbots presents exciting opportunities but would also create challenges requiring more detailed exploration. As these technologies advance toward reality, finding the right balance between psychological comfort and honest disclosure will be key.

By embracing these behavioral science insights, the insurance industry can take a significant step forward in addressing the mental health underwriting challenge.

Read the full report, "Improving Mental Health Disclosure for Insurance Underwriting."

References

• https://www.psychiatry.org/patients-families/stigma-and-discrimination

• https://www.cambridge.org/core/journals/bjpsych-open/article/creating-a-hierarchy-of-mental-healthstigma-testing-the-effect-of-psychiatric-diagnosis-on-stigma/3F7F87E0D4F50412B2A90072CFD8B995

• https://www.rgare.com/knowledge-center/article/how-can-life-insurers-improve-the-dtc-applicationprocess-a-behavioral-science-analysis

• Giesbrecht, G. F., Müller, U., & Miller, M. (2010). Psychological distancing in the development of executive function and emotion regulation. In B. W. Sokol, U. Müller, J. I. M. Carpendale, A. R. Young, & G. Iarocci (Eds), Self and social regulation: Social interaction and the development of social understanding and executive functions (p. 337–357). Oxford University Press.

• https://www.abi.org.uk/products-and-issues/choosing-the-right-insurance/health-insurance/mental-healthstandards/

• https://www.rgare.com/knowledge-center/article/searching-for-simplicity--improving-customercomprehension-in-life-insurance-through-behavioral-science

• https://www.rgare.com/knowledge-center/article/bringing-order-to-complexity-in-claim-forms-an-rgabehavioral-science-study