Over the past decade, technology has revolutionized nearly every aspect of the claims process, from initial inspections to final resolutions. Drone technology, in particular, has emerged as a powerful tool for addressing some of the industry's most persistent challenges, including the need for increased accuracy, faster speed, and more cost-effectiveness.

As insurers seek ways to enhance their operations, the integration of drones with artificial intelligence (AI) and machine learning (ML) offers an unprecedented opportunity to rethink how property inspections and claims evaluations are conducted.

How Drone Technology Enhances Claims Processing

Traditionally, property inspections have required significant time and labor, often leading to delays in claims resolution and the potential for human error. Drone-based inspections address these issues directly. Equipped with high-resolution imaging capabilities, drones can capture comprehensive visual data of a property's exterior in a fraction of the time required for manual inspections.

This data is then analyzed using AI and ML to detect roof abnormalities, structural damage, and other potential issues with a high degree of precision. These technologies eliminate much of the subjectivity that has long characterized claims assessments, providing insurers with reliable, consistent insights.

Introducing Repair Estimates for a Seamless Workflow

While drone technology has become increasingly common for property inspections, recent advancements have expanded its applications to include repair estimation. This is a critical step forward, as it allows insurers to move seamlessly from damage analysis to actionable solutions.

For example, drone-based property inspection platforms are now being enhanced to include repair estimates. By integrating these capabilities, insurers can streamline the entire claims process—from initial inspection to final resolution—saving time and reducing operational costs while improving the experience for policyholders.

Why This Matters for Insurers and Policyholders

The benefits of these advancements are significant for all stakeholders. Insurers gain a faster, more efficient workflow that enables them to process claims with greater accuracy and consistency. For policyholders, the impact is equally profound. Faster claims processing means quicker access to the funds they need to recover from property damage, while the transparency offered by drone and AI technology builds trust in the claims process.

The Broader Context: Technology's Role in Insurance Innovation

Drone technology is not an isolated advancement; it is part of a broader wave of innovation sweeping the insurance industry. According to a recent Deloitte report, insurers are increasingly leveraging AI, blockchain, and IoT to modernize their operations and better respond to the needs of their customers. These technologies are helping insurers enhance risk assessment, reduce fraud, and improve customer satisfaction.

By adopting tools like drone-based inspections and repair estimation, insurers position themselves at the forefront of this transformation, meeting the demand for smarter, faster, and more responsive claims solutions.

Looking Ahead

As the insurance industry continues to evolve, the integration of advanced technologies like drones, AI, and ML will become increasingly essential. These tools not only enhance operational efficiency but also have the potential to reshape the relationship between insurers and their customers, fostering a new level of transparency, trust, and collaboration.

For insurers looking to stay ahead of the curve, embracing these innovations is no longer optional—it's imperative. By leveraging the capabilities of drone technology, the industry can move closer to a future where claims processing is not just faster and more accurate but also more equitable and customer-centric.

In today's rapidly evolving digital landscape, insurers stand at a juncture. The integration of advanced technologies such as artificial intelligence (AI) and the rise of insurtech innovations promise to revolutionize traditional insurance operations. However, the key to unlocking these advancements lies in one foundational shift: robust data modernization.

High-quality, integrated data systems are now essential to an insurer's adaptability and long-term success. Data not only underpins effective AI applications but also forms the backbone of the integration or promise of most insurtech solutions. Without a modern data infrastructure, insurers risk falling behind in a market that increasingly values speed, accuracy, and personalized experiences.

Understanding Data Modernization

What do we mean by data modernization? It is a comprehensive and strategic approach to improving an organization's data architecture. Often, this means moving from outdated legacy systems to advanced, scalable platforms. It involves migrating data storage and processing to cloud-based solutions, integrating disparate data sources across the organization, processes, and third-party providers, and implementing real-time analytics capabilities. The goal is to create a unified, agile data environment that supports informed decision-making and enhances operational efficiency.

The Imperative for Insurers

For the insurance sector, data is the cornerstone of virtually every function—from underwriting and risk assessment to claims processing and customer engagement. Traditionally, insurers have relied on data silos, inconsistent formats, and inefficient processes, which lead to delays and hinder their ability to respond swiftly to market changes and customer demands. Modernizing data systems resolves these issues by ensuring data is accurate, accessible, and actionable.

Enhancing Regulatory Compliance

One of the primary drivers of data modernization is regulatory compliance. The insurance industry operates within a complex regulatory framework that varies across jurisdictions. Maintaining compliance requires meticulous data management and strong reporting capabilities. Modern data platforms facilitate this by providing secure, transparent, and easily auditable data trails. Automated compliance monitoring and reporting tools can be integrated, reducing the risk of non-compliance and associated penalties. Data modernization is essential for insurers navigating the intricate web of local, national, and international regulations.

Operational Efficiency and Cost Reduction

Another major driver is operational efficiency and cost reduction. Outdated data systems often lead to redundant processes and prolonged cycle times. By adopting modern data architectures, insurers can automate routine tasks, streamline workflows, and reduce operational costs. For example, AI-powered analytics can process vast datasets in seconds, providing insights that would take humans significantly longer to derive. This efficiency lowers operational expenses while enabling employees to focus on more strategic activities.

Competitive Advantage: Meeting Evolving Customer Expectations

Today's consumers expect personalized, digital-first interactions. Modern data systems enable insurers to analyze customer behavior and preferences in real time, allowing for customized products and services. This personalization fosters customer loyalty and can be a significant competitive differentiator. Leveraging AI and modern data architectures enables insurers to create intelligent decision-making frameworks that enhance customer experiences.

AI Enablement Through Data Modernization

Artificial intelligence thrives on high-quality, well-structured data. Applications such as predictive analytics, automated underwriting, and fraud detection rely on seamless access to comprehensive datasets. Modern data infrastructures provide the necessary foundation for these AI applications to function effectively. Without such a foundation, AI initiatives may yield inaccurate results or fail to deliver actionable insights. Integrating AI into insurance operations can enhance risk estimation accuracy and drive better pricing strategies.

Building the Data Foundations for AI and Cloud-Native Insurance

As insurers adopt modern platforms like Guidewire Cloud, they're also rethinking how to manage data access and analytics in a more distributed, cloud-native environment. This shift presents an opportunity to streamline reporting and unlock greater agility—but it also requires retooling traditional approaches to data extraction and business intelligence. To accelerate this transition, some insurers are working with consulting partners who offer pre-built frameworks for accessing and organizing cloud-based data, ensuring continuity in analytics while laying the foundation for AI and compliance-ready data environments. Firms with deep expertise in insurance data architecture and governance can help insurers make this leap efficiently and strategically.

Driving Innovation Through Insurtech Partnerships

Data and analytics fuel innovation in insurance. The insurtech landscape is filled with startups offering solutions that can transform various aspects of insurance operations. However, integrating these solutions requires a modern data environment that supports interoperability and scalability. Collaborations between traditional insurers and insurtech firms can lead to the development of new products, improved customer engagement tools, and more efficient claims processing systems. For example, companies like Earnix or hyperexponential deliver AI-based solutions to insurers, enhancing their data analytics capabilities and enabling data-driven decision-making.

Making Quick Progress in Data Modernization

Data modernization is achievable, and insurers can make significant progress quickly with the right approach. By focusing on key areas and working with an experienced consulting partner, organizations can streamline their transformation and see real benefits faster. Here are a few key considerations:

1. Start With Strong Data Governance – Implementing clear policies and frameworks ensures data accuracy, security, and compliance from the start. A well-structured governance plan makes future enhancements easier.
2. Adopt Scalable, Cloud-Based Technologies – Modern cloud solutions allow insurers to expand their data capabilities as needed, reducing costs and improving flexibility.
3. Promote a Data-Driven Culture – Encouraging data literacy and empowering employees to use insights in their daily work helps organizations maximize the value of their data.
4. Leverage Expert Support – Partnering with experienced insurtech firms and technology providers can accelerate integration, helping insurers adopt innovative solutions with minimal disruption.

Data modernization is not merely a technological upgrade—it is a strategic imperative for insurers aiming to thrive in the digital age. By overhauling data infrastructures, insurers can enhance regulatory compliance, operational efficiency, and customer satisfaction. Moreover, a modern data foundation is essential for leveraging AI and fostering innovation through insurtech collaborations.

As the industry continues to evolve, those who prioritize data modernization will be well-positioned to lead in a more agile, customer-centric future. With the right strategy and expert support, insurers can unlock opportunities and remain at the forefront of the digital transformation of insurance.

Sunny Wadhwa, managing director/head of asset management sales at Conning, spoke with Andy Pace, managing director/portfolio manager at Conning, and Don Townswick, managing director/director equity strategies at Conning, about the current state of the equity market and why they think the firm's high-dividend equity strategy is ideal for insurance portfolios.

What is causing current market volatility?

DT: President Trump's April 2 "Liberation Day" introduction of new tariffs certainly led to a spike in volatility, but there has been a great deal of uncertainty gripping markets for some time now.

There are some outstanding questions about fiscal and regulatory policy that still need to be answered: Will tax cuts from Trump's first term be allowed to expire? Will the Trump administration bring forth a lighter regulatory environment, which would likely be helpful to businesses? Will the economy be slowed by federal budget deficits, and will immigration enforcement hamper labor markets? We also don't know how the U.S. Federal Reserve will respond to sticky inflation and economic growth concerns.

With this much uncertainty, it is no surprise that equities are volatile and that they may remain so for an extended period.

Will equity market conditions change? What do you think will happen?

DT: Markets are always changing, and this market will, as well. As we study the current dynamics, we actually see a silver lining in the outlook for dividend-equity stocks.

The stocks recently dominating S&P 500 Index performance have been in a narrow band known as the "Magnificent 7" stocks: Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. Most other stocks in the index have been performance laggards. The outstanding earnings (which are closely related to net income) performance of the "Magnificent 7" have begun to taper and are projected to settle into a lower range, while earnings for the rest of the stocks in the S&P 500 are projected to rise through the rest of 2025.

We think this implies that a correction in the "Magnificent 7" stocks could happen along with a broadening market in which the rest of the market goes down less than the "Magnificent 7," while providing competitive returns when the market turns up again. The first implication already seems underway, as high-quality stocks have dropped far less than the "Magnificent 7" stocks. It remains to be seen whether the second part of that hypothesis will come to pass.

How are Conning clients reacting to the recent equity volatility?

DT: As most of our clients are insurance companies and tend to be fairly risk-averse equity investors, they are holding their allocations; we are not seeing wholesale buying or selling.

However, in many client conversations we've noted that a large number see this "tariff induced" selloff as a buying opportunity, once the acute uncertainty abates. Our clients have a very long horizon for their equity investments, and equities are usually the longest-duration asset they own. They often look to add during market dips or in situations like we are currently in, and like us, many clients believe the current selloff is overdone. The broadening of the market away from the "Magnificent 7" stocks has certainly been welcomed by our clients after two years of a small number of stocks driving the majority of the market's returns.

Given the volatility, why do insurers include equity in their portfolios at all?

AP: NAIC and state regulatory requirements limit insurance portfolio allocations to equity, and while most insurers don't like surplus volatility, they do understand the need to have an equity allocation to grow surplus. Conning's recommended approach in recent years has been an allocation to our lower-volatility, higher-dividend strategy.

Why do you support an equity strategy focused on dividend-paying stocks?

AP: Initially, what led us to develop this strategy was the period of historically low interest rates post-Great Financial Crisis: We saw the equities of many high-quality companies offering dividend yields that exceeded the yields of their long-term debt. The dividend income, plus the potential for growth, as well as the lower beta (historical beta of 0.82 to the S&P 500) and higher quality approach (average NRSRO credit rating of the holdings of A), made a strong case for insurers to consider an allocation to this strategy, either solely or as a complement to their existing equity allocations.

Lastly, dividends have contributed a meaningful share of the total return of equities over long time horizons and, in periods of uncertainty or volatility, provide a stabilizing element to performance.

Tell us about the process: How do you build the portfolio?

AP: Our goal is to create a diversified portfolio of companies with strong balance sheets and free cash flow, that have higher dividend yields than the S&P 500, a history of stable payouts and dividend growth, and potential for capital appreciation.

Our rules-based method of building the portfolio has been the same since inception, repeated in the last month of each quarter and based on a disciplined three-step process (quantitative screening, qualitative review, and finally name selection) designed to filter the universe of potential investment candidates from the S&P 500. So not only is this a low-volatility, high-quality, value-oriented approach, it is also a low-turnover/cost approach, as we only trade on a quarterly basis.

How do insurance portfolios benefit from this dividend-focused equity strategy?

AP: In addition to the higher dividend income, insurers have also benefited from the strategy's strong historical risk-adjusted return, which since inception has provided upside market capture of 90% of the S&P 500's gains; the downside protection has been evident with a downside market capture of only 82% of the index's declines.

Historically, the strategy has performed best when equity markets are experiencing volatility, such as we've seen this spring. Our clients have found having a higher-quality, larger-capitalization, lower-volatility portfolio quite valuable during periods of market uncertainty.

Are there other benefits?

AP: We've talked about many benefits already, but we can't stress enough the importance of the dividend income -- insurance companies can never have enough income! While we do not view equity dividends as a substitute for fixed-income coupons, we believe that an equity component offering a higher dividend than the broad market is of value to income-focused insurers. Lastly, I want to add that our portfolio approach is equal-weighted rather than market-weighted. This strategy was built with insurance companies in mind, and we firmly believe that an equal-weighted approach offers better diversification, reducing concentration risk and potentially leading to better risk-adjusted returns.

The insurance-linked securities (ILS) market represents a major evolution in how risks are transferred, managed and financed globally. Insurance, among the world's oldest commercial activities, offers institutional investors participation opportunities through ILS and reinsurance via capital markets.

The risk transfer market, traditionally dominated by insurers and reinsurers, attracts institutional investors seeking alternative assets that provide both portfolio diversification and stability during market turbulence.

The ILS market has evolved significantly, reaching $50 billion in catastrophe bonds for the first time as of March 2025, according to Artemis reports. This growth represents a 9.7% compound annual growth rate over the past five years as investors increasingly seek alternative assets offering both diversification and resilience to market volatility.

Through instruments like catastrophe bonds and collateralized reinsurance, ILS allow investors to assume insurance risks for competitive returns that remain largely uncorrelated with traditional financial markets. This bridges capital markets and the insurance industry while enhancing the sector's capacity to absorb major risks, particularly from natural disasters.

How ILS Work

In the traditional insurance model, companies sell policies to customers in exchange for premiums, providing coverage for potential future losses. When catastrophes occur and too many policyholders file claims simultaneously, insurers face significant financial strain. To manage this, they often turn to reinsurers.

Catastrophe bonds, a major ILS type, typically involve an insurer issuing bonds through a special purpose vehicle (SPV). Investors receive coupon payments but may forfeit principal if predefined events like earthquakes or hurricanes occur. Various trigger mechanisms determine payouts, including indemnity triggers based on actual losses, parametric triggers tied to objective measurements like wind speed, industry loss triggers based on total market losses, and modeled loss triggers calculated through predetermined models.

For example, a sample catastrophe bond for California earthquake risk might offer investors a 7% annual coupon rate for three years. If no triggering event occurs, investors receive their interest and principal. However, if an earthquake meeting specific parameters strikes, investors could lose part or all of their principal, which the insurer would use to cover policyholder claims.

Market Growth Driven by Climate Change

Weather-related disasters increasingly strain the traditional insurance model. Between 2019-2023, the U.S. averaged 20.4 catastrophic events annually causing over $1 billion in damages each, up from the historical average of 8.5 since 1980.

The distribution of damage from U.S. billion-dollar disasters shows tropical cyclones causing the most damage at $1,427.2 billion (inflation-adjusted), with an average cost of $22.3 billion per event. Drought ($361.9 billion), severe storms ($513.8 billion) and inland flooding ($201.9 billion) have also caused considerable damage.

Rising building values further strain insurers' capabilities, compounded by carriers exiting wildfire and wind-prone markets. This exacerbates coverage challenges in vulnerable areas. In 2023 alone, the U.S. experienced 28 confirmed weather and climate disaster events exceeding $1 billion in losses, resulting in 492 deaths and significant economic repercussions.

Expanding Beyond Natural Catastrophes

While catastrophe-linked products dominate the market, the ILS sector is expanding beyond natural disasters to include other high-impact risks:

Cyber Risk: Catastrophic cyber events such as ransomware attacks and widespread outages share many traits with natural catastrophes—they're hard to model, potentially devastating, and increasingly systemic. In 2023, Beazley issued "Cairney," the first cyber catastrophe bond, transferring tail cyber risk to capital markets.

Terrorism Risk: These systemic and infrequent risks fit the ILS model well. France's terrorism risk pool GAREAT issued a $105 million terrorism risk cat bond in 2024, marking an important expansion into man-made perils.

Pandemic Risk: COVID-19 catalyzed interest in pandemic-related securities, although these face complex modeling and trigger challenges. Nevertheless, pandemic-related ILS like mortality bonds are drawing attention from reinsurers and health insurers.

Technological Evolution

Technology plays a crucial role in the ILS sector's development, particularly in risk assessment, modeling, transparency, and operational efficiency. Leading companies in the risk modeling space include Verisk AIR Worldwide, RMS (Moody's), and CoreLogic (EQECAT), which are used in approximately 99% of ILS contracts. Emerging players like CyberCube, Synthetik, Parametrix and Katrisk are also making significant contributions.

Blockchain technology and decentralized finance (DeFi) present new opportunities to enhance efficiency and accessibility. In 2024, Schroders Capital conducted a successful tokenization pilot that enabled reinsurance contracts to be tokenized and traded on a public blockchain platform using smart contracts. This initiative demonstrated potential for automating time-consuming processes like subscriptions and settlements.

The regulatory environment for crypto assets remains uncertain, raising questions about how tokenized ILS should be classified and regulated across jurisdictions. Consumer protection concerns exist, particularly regarding potential retail investor exposure to complex insurance risks. Additionally, the current ILS investor base, primarily pension funds and specialized ILS funds, may adopt crypto-based platforms slowly.

Future Vision

The long-term vision for ILS could include tokenized catastrophe bonds with rapid settlement times, global insurance pools funded by stablecoins, and catastrophe swaps traded on decentralized exchanges. According to Fitch, blockchain-driven applications in ILS are expected to grow as the technology becomes more integrated into the reinsurance sector.

This could eventually enable an insurer to seamlessly transfer specific risks to global investors through smart contracts. These investors would contribute digital stablecoins in a transparent, regulated process. When triggering events occur, payouts would happen automatically, allowing same-day relief through parametric solutions. This combination of speed, automation and trust could redefine how capital is deployed for disaster response and risk management.

Despite challenges, the convergence of digital finance and ILS represents a significant opportunity to create a more efficient, transparent and inclusive risk transfer market. As climate-related events increase in frequency and severity, innovative financial instruments that expand risk-bearing capacity will become increasingly important to global financial resilience.

Only tax evasion exceeds insurance fraud on the list of most costly white-collar crimes in the U.S. In fact, 10% of insurance claims are fraudulent, and the problem is only growing. 

TransUnion says suspected digital fraud attempts surged 80% globally from 2019 to 2022, and generative AI heightens the problem. It lets bad actors manipulate or even make up evidence such as photos and lets them create synthetic identities (combining real and fake personal information).

But generative AI is turning out to be much more of a blessing than a curse, mostly because it so greatly expands the amount of information an insurer can evaluate for signs of fraud, according to a recent report by Deloitte. Unstructured information such as handwritten notes, photos (including their metadata), videos, phone calls and sensor data can all be scanned for inconsistencies and key words or patterns that suggest fraud. 

By 2032, Deloitte says, P&C insurers could save between $80 billion and $160 billion a year on fraudulent claims — if they take the right approach. 

Here are Deloitte's key recommendations for how to save loads of money on fraud. 

The Deloitte report says soft fraud — when a claimant exaggerates a loss — accounts for 60% of fraud and is only caught 20% to 40% of the time. Hard fraud — when someone stages a loss or simply makes it up — accounts for the remaining 40% of fraud and is caught more often, between 40% and 80% of the time.

Improving on detection won't come cheap. Deloitte expects insurers to be spending $32 billion on fraud detection technology by 2032 — but says they could then reduce fraud by between 20% and 40%, more than making up for the technology's hefty expense.

Deloitte lists these techniques as key to fraud detection, while emphasizing the need to combine multiple approaches: 

• "Text analytics. Natural language processing analyzes textual data of claims forms, emails, and social media posts to identify keywords and entities....
• Audio-image-video analysis. Speech recognition and sentiment analysis can examine customer calls for signs of duress.... Photo analytics can uncover irregularities in metadata, manipulation, and repeated use. Causation analytics can identify if alleged injuries were likely consistent with the experienced accident. Video analytics can verify the occurrence and extent of damage, identify authenticity of images, and highlight signs of tampering or staging.
• Geospatial analysis. Satellite images and comprehensive 3D drone footage can verify the extent and location of damage that may not be clearly visible in physical inspections....
• Internet of Things data. Real-time surveillance devices like vehicle telematics can reconstruct accidents and verify the legitimacy of claims. Smart home sensors like water leak detectors and security cameras can help gather evidence that can be used to verify claims and detect fraudulent or staged activities.
• Simulation models. Replicating the behavior of medical providers, repair shops, and others that individuals may work with under different scenarios in a controlled virtual environment can identify patterns and deviations from standard industry practices and detect instances such as overbilling, unnecessary services, and coordinated activities or probable collision rings between entities."

Every honest customer hates fraud, because we all know it's raising prices for the rest of us. Customers are surely even more sensitive about the issue now, given that premiums have risen sharply for a couple of years and that Trump's tariffs are starting to reignite inflation for cars, car parts and materials that insurers use to repair or replace homes. 

So insurers will not only cut costs but be applauded by customers for doing so. Let's do it.

Cheers,

Paul 

In today's fast-paced digital landscape, insurance carriers stand at a crossroads. Traditional operations—burdened by siloed systems and manual workflows—are no longer sustainable. Outdated models not only slow decision-making but also erode customer trust and inflate operational costs. The path forward is clear: Embrace intelligent, AI-driven operations that cut through complexity, deliver real-time insights, and elevate both efficiency and experience.

Intelligent Operations: The Strategic Advantage

Intelligent operations are not just a tech trend— they are the new foundation for competitive advantage. By leveraging agentic AI, machine learning, and real-time analytics, insurers can automate decision-making, streamline processes, and hyper-personalize customer interactions. Agentic AI, in particular, represents a breakthrough: autonomous, purpose-driven agents that learn, adapt, and act independently to deliver outcomes at scale. According to McKinsey, insurers implementing AI are achieving up to a 25% reduction in operational costs and a 25% boost in customer satisfaction—a leap in both efficiency and impact.

The Time for Transformation Is Now

The urgency to act has never been greater. Customer expectations have shifted—demanding instant, seamless, and personalized service across every channel. Legacy systems and fragmented processes simply can't keep up. Meanwhile, insurtech disruptors and digital-native competitors are setting a new bar for agility and innovation. To stay relevant, traditional carriers must reimagine their operations through the lens of intelligent automation. Those that move now will lead the future of insurance. Those that don't risk being left behind.

Taking the First Step: Initiating the Transformation

Embarking on this journey requires a structured approach:

1. Assess Current Operations: Identify areas where inefficiencies exist and where AI can have the most impact.
2. Set Clear Objectives: Define what success looks like—reduced processing times, improved customer satisfaction, or cost savings.
3. Collaborate With Experts: Partner with technology providers specializing in insurance digital transformation.
4. Pilot and Scale: Start with pilot projects, gather insights, and then scale successful initiatives across the organization.
5. Foster a Digital Culture: Encourage continuous learning and adaptability among employees to embrace new technologies and processes.

The Cost of Inaction: Risks of Not Embracing Intelligent Operations

Insurers that delay modernization face mounting risks. Without embracing AI and digital-first solutions, organizations fall behind more agile competitors, struggle with inefficient legacy systems, and expose themselves to regulatory challenges. Operational inefficiencies lead to increased costs, delays, and errors, while outdated systems make compliance more difficult. Most critically, customer dissatisfaction grows as digital expectations rise—leading to churn and a decline in brand trust. The absence of AI-driven insights also means missed opportunities to identify emerging trends and evolving customer needs.

Enhancing Job Satisfaction Through Intelligent Operations

Intelligent operations don't just transform systems—they elevate people. By automating routine tasks, employees are freed to focus on higher-value, strategic work. Upskilling becomes part of the journey, as staff gain new digital competencies that enhance their career prospects and value in a rapidly evolving industry. Streamlined processes also improve work-life balance by reducing burnout and enabling more meaningful contributions. The result: a more engaged, capable, and future-ready workforce.

From Chaos to Clarity: A Strategic Imperative

The transition from fragmented, traditional operations to intelligent, AI-enabled clarity is more than a technology upgrade—it's a strategic imperative. Insurers that embrace agentic, AI-powered, and digital-first operations position themselves to deliver faster, smarter, and more personalized experiences. In doing so, they unlock greater agility, customer satisfaction, and sustainable growth in a competitive landscape that favors innovation and responsiveness.

When people talk about AI in insurance, they usually imagine global giants, shiny dashboards, and Silicon Valley pilot programs. But the reality is far broader—and in some ways, more grounded. Even in emerging markets like Ukraine, artificial intelligence is becoming a silent partner in day-to-day decision-making, risk management, and claims processing.

From Curiosity to Daily Tool: Where We Use AI

I wouldn't call myself an AI veteran, but over the past year, these tools have become a quiet backbone in my work. I use them to analyze market trends, structure internal reports, and systematize competitive data that used to take hours to compile. In short, AI is like having an analyst who never sleeps and never needs a coffee break. (Though if it learns to bring coffee, I'm in trouble.)

Beyond personal use, we're gradually integrating AI into our operational workflows. Some real examples from inside our company:

• Automated underwriting that speeds up policy issuance and improves consistency.
• Remote claims adjustment using computer vision tools to assess damage from user-submitted photos.
• Medical AI integration in health insurance products to provide early diagnostics and smarter pricing models.

Where AI Shines in Insurance (and Where It Still Struggles)

The areas where AI truly adds value are well known:

• Underwriting based on historical and behavioral data
• Fast-track claims resolution
• Actuarial calculations at scale
• Fraud detection through pattern recognition

But the challenge isn't always in the algorithm—it's in the environment. In Ukraine, we lack clear regulation on AI, so companies are hesitant to fully automate sensitive decisions. There are also concerns about customer trust and data ethics. Without clear legal frameworks, some executives prefer to play it safe.

That said, this cautious phase is normal. We've seen it before with online banking. It started slowly—and now no one can imagine life without it.

People First: Culture Matters More Than Code

One of the biggest misconceptions is that AI will replace people. In practice, it empowers them. But that message needs constant reinforcement.

In our company, we've started internal workshops to help teams understand how AI supports—not replaces—their work. Once employees see how tools help them save time or reduce routine, resistance melts away.

Still, change management is essential. Some team members fear the unknown, others are simply overwhelmed by "yet another tool." That's why leadership has to be transparent and patient and lead by example.

East vs. West: What's Different—and What's Not

Compared with Western markets, Ukraine is behind in AI penetration—but not in ambition. While U.S. and E.U. insurers boast automated five-second claims approvals, we're still scaling those capabilities. But the bright side? We get to learn from others and leapfrog past failed models.

In some ways, being late to the party is a strategic advantage.

Final Thought: Start Small, Think Bold

AI is not a threat. It's a lever. A multiplier. An amplifier of human capability. It helps us do what we do—only faster and more intelligently.

My message to industry colleagues: Don't wait for the perfect regulation or the perfect tool. Start where you are. Use what you have. Explore. Adapt. And most of all—bring your teams along for the journey.

The future isn't about man versus machine. It's about partnership.

In an evolving healthcare ecosystem, insurance companies are uniquely positioned to lead innovation and influence the adoption of technology-driven care models. Among the most transformative advancements in recent years are telemedicine and remote patient monitoring (RPM). These solutions are not just short-term responses to healthcare access challenges, they are enduring strategies that can enhance care quality, reduce costs, and improve patient engagement. For insurance companies, particularly those managing Medicare Advantage plans, the question is no longer if telemedicine and RPM should be prioritized, but instead how quickly and effectively they can be scaled.

Telemedicine: Expanding Access While Controlling Costs

Telemedicine refers to the use of electronic communications and software to provide clinical services to patients without an in-person visit. This includes video consultations, telephone appointments, and asynchronous (store-and-forward) communication.

For payers, the value proposition of telemedicine lies in cost avoidance, member satisfaction, and access to care. Studies consistently show that virtual visits are more cost-effective than emergency room or urgent care visits for non-emergency conditions. Moreover, they help insurers engage hard-to-reach populations, including rural residents and mobility-challenged seniors.

A Medicare Agent from Medicare Agents Hub outlines how strongly Medicare Advantage plays a role here, "if you're living in a rural area, a Medicare advantage plan may offer you more options for telehealth that you would otherwise not have access to if you were simply on original Medicare and Medigap."

Insurance executives should view telemedicine as a lever to support value-based care models. By enabling more frequent touchpoints with providers, plans can manage chronic conditions, reduce hospital readmissions, and identify gaps in care.

Remote Patient Monitoring: Continuous Care Beyond the Clinic

Remote patient monitoring (RPM) involves the use of connected devices—such as blood pressure cuffs, glucose monitors, and wearable sensors—that transmit health data from the patient's home to clinicians in real time. RPM is particularly valuable in the management of chronic diseases like diabetes, hypertension, heart failure, and COPD.

For insurers, RPM translates into real-time insight into member health, early intervention, and better utilization management. Instead of reactive care driven by acute events, plans can support predictive care models where risks are flagged before they escalate. This not only enhances patient outcomes but also reduces the need for high-cost interventions such as ER visits and hospitalizations.

Medicare Advantage: A Catalyst for Adoption

The Centers for Medicare & Medicaid Services (CMS) has played a pivotal role in legitimizing and providing incentives for telemedicine and RPM. Medicare Advantage (MA) plans, in particular, are at the forefront of this transformation due to their flexibility in offering supplemental benefits and their emphasis on care coordination.

Since 2020, CMS has allowed MA plans to offer telehealth services as part of their basic benefit structure. This includes virtual primary care, behavioral health services, and even specialty consultations. The CHRONIC Care Act and other CMS regulatory updates have further enabled the use of remote monitoring for chronic disease management, providing reimbursement pathways for services that were previously out-of-pocket expenses.

Moreover, under Medicare Advantage, plans can use telehealth to meet network adequacy requirements in underserved areas. This creates an opportunity to expand provider networks without significant investment in brick-and-mortar infrastructure.

Strategic Considerations for Insurance Executives

1. Align Telehealth With Risk Adjustment and Quality Metrics:

Telemedicine and RPM generate valuable data that can support HEDIS measures, Star Ratings, and risk adjustment coding. Executives should ensure interoperability with electronic health records and build data analytics strategies to capture and leverage this information effectively.

2. Invest in Member Education and Technology Access:

Even with broad reimbursement support, telehealth and RPM adoption hinges on member trust and usability. Executives should consider programs that provide devices, offer digital literacy training, or partner with community organizations to bridge the digital divide.

3. Strengthen Provider and Agent Partnerships:

Providing incentives to providers and agents to adopt telehealth and RPM requires more than reimbursement, it requires workflow integration and clinical alignment. Collaborative models that offer training, shared savings, and decision-support tools will accelerate participation.

4. Embrace Hybrid Care Models:

Rather than replacing in-person care, telehealth and RPM should be integrated into a hybrid model that blends virtual and physical interactions. This ensures continuity of care and supports patient preference.

Looking Ahead: A Competitive Differentiator

As CMS continues to encourage digital innovation and as consumer expectations evolve, telemedicine and remote monitoring will become table stakes for insurance companies, not differentiators. The window of competitive advantage is narrowing. Insurance executives who invest now in infrastructure, partnerships, and member engagement strategies will not only improve outcomes and control costs, they will position their organizations as leaders in the next generation of care delivery.

For Medicare Advantage plans, in particular, this represents a unique opportunity to leverage regulatory flexibility to pilot, scale, and refine technology-enabled care solutions. The imperative is clear: Telemedicine and remote monitoring are not optional, they are foundational pillars of a modern, resilient, and member-centered insurance model.

Today's unconventional solopreneur may be tomorrow's regional success story — that's why we need more inclusive underwriting.

Insurance is a safety net many take for granted—until they realize they've been excluded from it.

For countless small businesses across the U.S., securing coverage isn't just a bureaucratic hurdle. Instead, it's a barrier to entry. Without insurance, a budding business can't bid on contracts, rent space, or even get off the ground. Yet, many are shut out because their business models don't fit neatly into a traditional underwriting box.

As an industry, we have a duty and an opportunity to do better.

Having spent much of my career in insurance product development and underwriting, I've seen the mechanics of risk evaluation up close. I've also seen how legacy approaches can leave unconventional businesses out in the cold. From part-time side hustles to gig-driven enterprises, the insurance industry often struggles to keep pace with the changing nature of entrepreneurship. This is where innovation and inclusivity must intersect.

We're often likely to insure individuals' passions that happen to develop into businesses. For instance, we insured a young man's lawn mowing business that evolved into a thriving business. He started the business before even entering high school, and most insurance carriers would have rejected him for not having enough years of experience. If we had relied on conventional underwriting rules that required three-plus years of experience to get a policy, we would have extinguished his passion before it even began.

At Simply Business, we encounter entrepreneurs every day who have been turned away by traditional channels—not because they're high risk, but because they're misunderstood.

Microbusinesses, particularly those owned by first-time founders or individuals in non-traditional trades, often face either excessive premiums or complete exclusion, with 20-30% of small businesses struggling to obtain insurance. In fact, nearly one-third of uninsured business owners in one of our recent surveys reported relying on Google or peers for insurance recommendations because they've been unable to access professional guidance or fair pricing.

That's not a sustainable future for our industry—or our economy. Small businesses generate 44% of U.S. economic activity. If we're not willing to protect them, we're failing to protect the very foundation of American enterprise.

Meeting Customers Where They Are

Expanding access starts with rethinking how we define risk. A thoughtful underwriter doesn't immediately reject a policy because it's unfamiliar. They look deeper. Our insurance carriers have stepped up to cover everything from pet waste removal professionals to holiday light installers—trades most carriers wouldn't bother pricing. But by leveraging digital platforms and informed risk frameworks, we've been able to meet these customers where they are—and help them get to where they're going.

Technology plays a key role here. Digital buying experiences can offer clarity, transparency, and ease to entrepreneurs navigating insurance for the first time. Much like the shift from paper tax forms to TurboTax, online insurance tools demystify an opaque system. But digital tools alone aren't enough—we must also rewire our risk models to accommodate the range of business owners knocking on our doors.

I remember speaking with a sweet tea vendor—formerly an airline mechanic—who traveled from fair to fair trying to grow her new business. She couldn't find anyone willing to insure her, and this prevented her from selling at the local food festival. She wasn't asking for a handout. She just wanted a chance to build the business that was her passion. And that's what insurance is really about: giving people the opportunity to achieve their dreams.

If we want to remain relevant and responsible stewards of risk, insurers must reevaluate how we define insurability. We must develop products that flex to fit emerging business models, not the other way around. This isn't charity—it's smart, future-focused business.

Now is the time to take a hard look at our models and expectations. Are we broadening our understanding of risk? Are we designing products that reflect the real world of entrepreneurship today? If not—why not? The businesses we overlook today are the ones that will define tomorrow.

Let's build an industry that makes room for all of them.

AI is reshaping insurance with high-resolution modeling that allows for more tailored, risk-appropriate solutions—even in high-risk geographies.

Climate change is no longer a future threat—it's a present-day crisis. Across the globe, extreme weather events tell a devastating story of this new reality. In the U.S. alone, more than 52,477 wildfires burned through 8.4 million acres of land, while 27 climate disasters each caused more than $1 billion in damages in 2024.

This pattern of destruction isn't isolated—from bushfires in Australia to floods in Europe and typhoons in Asia, communities worldwide are feeling the impact, with 2024 data showing that 97% of all insured losses stemmed from weather-related catastrophes. And with NASA reporting an uptick in carbon dioxide, global temperature and methane levels (and that 2024 was the warmest year on record) it's no surprise insurance companies are becoming increasingly concerned about protecting their policyholders and preserving their own business legacies.

As traditional approaches prove inadequate in the face of this escalating crisis, the insurance industry finds itself at a crossroads. So how can insurers move forward when traditional risk assessment models lag behind the changing climate reality?

The Rising Challenge: Market Retreat Amid Climate Volatility

As climate risk becomes more localized and unpredictable, certain regions are being deemed "uninsurable," even if they were previously profitable, causing an insurance exodus that leads to lost revenue, erodes trust in the industry and leaves vulnerable communities without coverage. In some cases, brokers can no longer offer relevant products, and customers are left underinsured or uninsured, with no one to turn to.

Without the right tools to assess and visualize climate impacts, insurers can struggle with inaccurate premium pricing and coverage gaps, inefficient underwriting with elevated exposure risk, overburdened claims operations during extreme events, delayed disaster response and customer dissatisfaction.

Artificial Intelligence is bringing clarity to what was once chaos and helping insurance enterprises respond to climate events—and more adequately prepare for them, with speed, accuracy and foresight.

How AI Is Transforming Climate Risk Management

AI isn't just a tool—it's a game-changer. Advanced climate risk modeling solutions marry cutting-edge AI, climate science and insurtech excellence to provide an accurate classification of extreme weather events using adaptive models to enhance response with early warning systems, hazard monitoring and data-driven insights for insurance enterprises. When combined with geospatial intelligence, environmental data simulation technology, continuous portfolio risk assessment and dynamic price adjustments based on evolving risks, AI is helping the insurance industry move from reactive to proactive decision-making across the entire insurance value chain.

Post-event recovery can be the most chaotic phase of all. AI simplifies and speeds this process with automated damage detection via satellite or drone imagery. AI-powered fraud detection during claim reviews easily prioritizes claims based on real-time impact modeling and can assist with resource prioritization and allocation. The result? Faster claims processing, reduced fraud, and improved customer experience.

Who Benefits From AI in Climate Risk Modeling?

The adoption of AI-powered climate risk solutions doesn't just enhance operations—it delivers tangible benefits across the insurance ecosystem, from insurers to brokers to the policyholder.

Insurers see smarter risk segmentation for more targeted products, faster claims handling and reduced fraud, and the ability to re-enter high-risk or previously uninsurable markets with data-backed confidence.

Brokers are finding enhanced risk insight, which helps them provide more personalized advisory services, confidence in offering relevant products in vulnerable geographies, and stronger client relationships through value-driven engagement.

Policyholders are seeing clearer, more transparent coverage terms and more affordable, tailored coverage—even in risk-prone areas. AI also provides them peace of mind with real-time risk alerts and better, faster claims support.

The Powerful Way Forward

The climate is changing faster than traditional insurance models can adapt. But AI-driven climate risk modeling offers a powerful way forward. This isn't just about better data—it's about redefining how insurance enterprises anticipate, adapt to and respond to risk. With artificial intelligence in insurance, we are building a more resilient, responsive future—one where technology empowers the insurance industry, and their policyholders, to thrive in the face of climate uncertainty.