Category: Insurance

The legal industry has officially entered its AI era. In just one year, AI in legal practice skyrocketed from 22% to 80%, marking the most dramatic technology shift the profession has witnessed in decades.

This isn’t just about numbers: it’s about an entire industry embracing innovation with strategic confidence. Legal professionals have finally gotten their “AI sea legs,” and the implications for AI in legal practice are profound.

The great awakening: AI in legal practice

The legal profession’s relationship with artificial intelligence has evolved rapidly over the past year. Like many industries, legal professionals have moved from initial evaluation to strategic implementation as AI tools have matured and proven their value in professional settings.

This shift seemingly came from a pressing concern in 2024, that law firms were struggling to keep pace with the rapid growth of AI and other disruptive technologies:

The data from our 2025 Legal Risk Index reveals a profession that has embraced AI with remarkable speed. The 80% adoption rate represents a fundamental shift from experimentation to implementation, from curiosity to commitment in how AI in legal practice is being integrated.

But, what does that 80% look like in practice? 

Beyond basic applications: Strategic integration

What’s striking about this transformation is how sophisticated legal AI applications have become. The industry has moved far beyond basic content generation that made up most of their use in 2024.

Enhancing professional services has emerged as the top application at 46%, representing a mature understanding that AI isn’t replacing legal expertise—it’s amplifying it. For law firms, AI augments research capabilities, identifies relevant precedents more quickly, and ensures comprehensive case preparation.

Automating client support interactions ranks second at 45%, showing how firms are improving client experiences while freeing up human resources for higher-value work. One specific circumstance would be improving accessibility and responsiveness without sacrificing the personal touch clients expect.

Strengthening cybersecurity measures rounds out the top three at 40%, reflecting awareness that AI can be both a risk and a solution in digital security. For example, AI tools have been used by organizations to detect phishing attacks, as the number of these breaches have increased substantially, and law firms remain high-value targets for threat-actors.

The finding that utilization has evolved from basic “developing or drafting content” (which dominated 2024 usage at 48%) to these strategic applications demonstrates that legal professionals have moved beyond the experimental phase of AI adoption.

The Cconfidence transformation

The most significant shift isn’t in what legal professionals are doing with AI, but in how they feel about it. The profession’s comfort level with AI-driven tools has increased substantially, with more legal professionals expressing confidence in their ability to implement and manage AI effectively.

According to Reuters’ 2024 Future of Professionals Report, “Over the past few years, legal professionals have become less wary of artificial intelligence (AI). Indeed, they are increasingly embracing AI as a transformative force, becoming more and more optimistic about the positive impact it can have on their practices.”

This confidence shift happened as practical experience replaced theoretical concerns. Real-world implementation has shown AI as a powerful complement to legal expertise, leading to broader acceptance across the profession.

While risks and misuse are still a concern, the benefits of AI in law practices seem to outweigh the consequences for lawyers and law firms, and this substantial one-year shift could be the result of that awareness.

Best practices for implementation of AI in legal practice 

As legal professionals have gained experience with AI tools, several best practices have emerged for successful implementation. Establishing clear governance frameworks is essential—firms should develop written policies that define acceptable AI use cases, required human oversight protocols, and client disclosure requirements. Data security remains paramount, with successful firms implementing strict controls over what information can be processed through AI systems and ensuring compliance with client confidentiality obligations.

Quality control measures are equally critical. Leading firms establish review processes where AI-generated work undergoes thorough human verification, particularly for client-facing documents or strategic recommendations. Training programs help staff understand both AI capabilities and limitations, while regular audits ensure policies are being followed consistently.

The most successful implementations also include client communication strategies, with firms proactively discussing their AI use with clients and obtaining appropriate consents. This transparency builds trust while protecting against potential professional liability issues down the line.

Navigating implementation risks

As with any significant technology adoption, legal professionals continue to thoughtfully address AI’s potential challenges:

• Over-reliance leading to professional liability risks tops concerns at 43%, showing lawyers understand the importance of maintaining human oversight when implementing AI in legal practice.
• Data privacy breaches concern 38% of respondents, reflecting acute awareness of client confidentiality requirements.
• Legal and ethical issues due to misuse worry 37%, demonstrating proactive thinking about compliance and ethical obligations, as well as legal malpractice.

These considerations haven’t disappeared with increased adoption—but, what is clear is that AI must be integrated into comprehensive risk management strategies. Legal professionals that are implementing AI will need to employ appropriate governance frameworks and internal policies to mitigate the risks they’re still exposed to.

Helpful tools for AI-workflow implementation

The legal profession’s thoughtful approach to AI in legal practice has yielded significant advantages. By taking time to evaluate options and develop implementation strategies, legal professionals have been able to select mature, reliable AI tools that align with their specific professional needs.

The amount of tools built specifically for law firms is growing. As our Chief Insurance Officer, Andy Lea, listed in an article for Law.com:

• WestLaw: An online legal research service and database provided by Thomson Reuters.
• Harvey: A generative AI platform designed specifically for the legal industry.
• Bloomberg Law: Utilizes AI to enhance legal research and practice.
• Clio: Integrated AI into their practice management software to enhance efficiency and client experiences.
• Lex Machina: Employs AI to analyze litigation data and provide strategic insights for legal professionals.

These tools have allowed firms to avoid common pitfalls while maximizing the benefits of AI integration. The result is an industry that’s now positioned at the forefront of professional AI implementation.

For more information on these tools and how law firms are actually using them, check out this recent webinar with Reminger Law and Everest:

Does your law firm use AI?

In this webinar with Reminger Law Firm and Everest, we explore the use-cases of AI in legal practice, the best tools for the job, the risks, and the benefits for lawyers.

Watch On-Demand

The new normal

What we’re witnessing isn’t just a temporary surge—it’s the establishment of a new baseline for legal practice. AI tools are set to become as fundamental as legal research databases and case management systems.

The legal professionals who successfully navigated this transformation share common characteristics: they approached AI implementation strategically, maintained focus on client service and professional obligations, and used their professional expertise to assess and manage risks associated with new technology.

The professionals thriving in this landscape are the strategic implementers who understand that successful AI integration requires the same careful planning and professional judgment that defines effective legal practice.

As Jordan Furlong, a lawyer and legal sector analyst recently told Fortune Magazine, “Lawyers are not big R&D people. They’re not hackers and experimenters. They are ‘tell me what this thing can do. Tell me it is safe to use it, and I’ll use it… I find it incredibly exciting. Terrifying for sure. Risky, no question. But really exciting.”

As the legal industry continues to evolve, the professionals who develop their “AI sea legs” while maintaining their professional standards will be best positioned to thrive in an increasingly competitive and technologically sophisticated marketplace.

What’s next for AI in legal practice?

The rapid adoption of AI in legal practice reflects broader technological trends affecting all professional services. The integration of AI in legal practice represents not just technological advancement, but strategic evolution in how legal professionals approach innovation and client service.

This transformation demonstrates that when implemented thoughtfully, AI tools can enhance rather than replace the core competencies that define quality legal work.

While this dramatic shift in AI adoption shows promise for the future of AI in legal practice, the complete picture reveals nuanced implementation strategies and opportunities that every legal professional needs to understand.

Get our full 2025 Legal Industry Risk Index to access all findings, implementation strategies, and risk management frameworks that can help position your practice for success in the AI-driven legal landscape.

Use of algorithmic underwriting is increasing across the insurance industry. With enhanced decision-making and improved risk assessments, an algorithmic approach to underwriting can optimize operations for insurers and experience for their customers.

In this post we delve into the evolution and advantages of algorithmic underwriting and share our insights on building and scaling an algorithmic underwriting platform.

The evolution…

Algorithms have always been part of the underwriting process, but they have generally been restricted to rating. For example, in determining risk factors for car insurance, algorithms, or mathematical formulas, would be used to set rates based on vehicle make, model, driver age, location and previous history. Whether simple or complex, algorithms have long been our core rating tool.

The use of algorithms in other areas of the underwriting process has been limited due to fear of overlapping these factors with rate making, or simply the lack of data and analytical capabilities at other parts of the underwriting process to make these decisions. Instead, the insurance industry has typically depended on complex rules engines for decisions on risk acceptance, risk tiers and report ordering.

With advancements in data access and analytics tools, carriers are now rethinking the use of algorithms, using them either alone or alongside traditional rules engines, to enhance decision-making throughout the underwriting process.

How it works…

Algorithmic underwriting employs analytical models to automate decision-making in the underwriting process or to provide insights to assist underwriters. For more homogeneous risks, it can fully or partially automate underwriting.

Key decisions made using algorithmic underwriting:

• Determining if a submission fits the carrier’s risk appetite
• Identifying key risk characteristics such as the correct SIC/NAIC code
• Prioritizing accounts based on desirability and winnability
• Making risk determinations on portions or the entirety of risk

Through this approach, carriers can achieve faster risk acceptance or rejection and reduce underwriting workloads. It also helps in providing customers more personalized risk assessments, real-time risk management and a seamless experience.

5 advantages of algorithmic underwriting

Algorithmic underwriting significantly benefits the insurance industry across 5 key areas:

1. Process efficiency: By automating the underwriting process, we are seeing algorithmic underwriting reduce processing times by up to 50%, streamline operations, increase testing speed and simplify the maintenance of complex decision-making systems. In addition, the automated processes of algorithmic underwriting can help handle an increase in applications reviewed by up to 25%, enabling insurers to increase premium without additional operating costs.
2. Accuracy: The accuracy of risk assessments can be improved through analysis of more extensive data sets. These analyses help identify patterns and correlations that might be missed by human underwriters alone. With this augmentation of the underwriter’s insight and judgement, errors in risk assessments can be minimized and fraud can more easily be detected. We estimate fraud losses may be reduced by up to 30% for some insurance companies.
3. Price: Pricing decisions can be more accurate by enhancing risk assessments. Algorithmic underwriting helps tailor premiums to individual risk profiles, enhance customer satisfaction and competitiveness. Additionally, it supports dynamic pricing, adjusting premiums in real-time based on changing risk factors, which we see improving underwriting profitability by up to 20%.
4. Proactive risk management: Algorithms can help insurers proactively identify emerging risks and adjust their underwriting and risk management strategies. This can help to mitigate potential losses, reduce loss ratio and improve overall portfolio performance.
5. Customer experience: Algorithmic underwriting allows for instant or near-instant decisions on coverage eligibility, pricing and personalized offers. With predictive and prescriptive analytics, insurers can make real-time, contextualized offers, making insurance more accessible and relevant to the individual customer’s needs. It also makes insurance more attainable to customers or segments that may have been marginalized by underwriting methods of the past.

Building an algorithmic underwriting platform at scale

An algorithmic underwriting platform requires a multi-layered approach that takes future scalability into consideration. Advanced features needed when considering an algorithmic underwriting platform include machine learning models, real-time risk assessment, and dynamic pricing models.

 

Challenges to consider as you optimize your data and algorithmic underwriting platform:

• Data quality and availability: Data may be fragmented, incomplete or outdated.
• Model interoperability: Complex machine learning algorithms used for underwriting may lack transparency and interoperability making outcomes difficult to explain.
• Compliance: As regulation of algorithmic models and AI increases, insurers must stay ahead of the guidance and adjust models as needed.
• Fairness and bias: If not proactively addressed, algorithmic underwriting presents the risk of perpetuating unfair practices and historic biases.
• Data privacy and security: Algorithmic underwriting involves collecting, processing and storing large volumes of personal and sensitive data. Securing customer data is vital for compliance and maintaining customer trust.

Success stories…

We see examples of success with algorithmic underwriting across the industry. In P&C for example, Ki Insurance leverages AI and algorithms for instant commercial insurance quotes and automated policy issuance. Hiscox collaborated with Google Cloud to develop and AI model that automates underwriting for specific products. Meanwhile, on the life insurance side, ethos employs machine learning to asses risk and to offer simplified insurance applications.

Conclusion

While algorithmic underwriting is not a novel concept in insurance, it is revolutionary in its enhancement of access to new data sources, improved data quality and better analytics tools. These enhancements allow underwriters insight from other areas of the value chain and extend their capability beyond archaic models or knockout rules.

Despite their sophistication, insurers will need to be aware of the potential for bias and a lack of transparency in algorithmic underwriting models. Ethics and compliance, including data privacy, consumer protection and fair lending laws will pose challenges for insurers to address from the outset.

As technology continues to evolve and data analytics capabilities expand, we bear witness to how algorithmic underwriting will revolutionize the insurance industry, drive innovation and empower financial institutions to make more informed, data-driven decisions.

Yesterday’s 8.8 magnitude earthquake near Russia’s Kamchatka Peninsula sent tsunami waves across the Pacific, placing Hawaii under evacuation orders, triggering advisories along the U.S. West Coast, and emphasizing a critical truth about natural catastrophes: They don’t respect borders and tend not to give warnings.

While the immediate impacts were relatively contained—with waves reaching up to 4 meters in Russia’s coastal towns and smaller surges affecting Japan, Hawaii, and Alaska—the event offers a potent and timely reminder about the importance of preparation and investment in resilience.

Coverage Confusion That Could Cost

Standard homeowners insurance policies don’t cover tsunami damage. Neither do earthquake policies, despite the seismic trigger. Tsunami damage falls under flood coverage—a separate policy that many coastal property owners don’t carry.

Flood insurance purchase rates nationally are low – even in coastal communities. This creates a potential perfect storm of financial vulnerability. Communities that experienced evacuation orders yesterday, from Oahu to the Oregon coast might well have been saddled with massive, largely uninsured losses had the tsunami played out differently.

Low Frequency, High Consequence

Tsunami risk represents the most challenging category of natural disasters: extremely rare but potentially catastrophic. Unlike hurricanes or earthquakes that occur with some regularity, major tsunamis affecting U.S. coastlines are generational events. This rarity can breed complacency.

Yesterday’s event, while not causing major damage to U.S. properties, provided invaluable data for catastrophe modelers. The wave propagation patterns, arrival times, and coastal impacts across Hawaii, Alaska, and the West Coast offer fresh insights into how a more severe event might unfold. Insurers and reinsurers are likely already incorporating this data into their risk models.

Building Resilience Through Partnership

The beauty of a “predict and prevent” model of risk management is that it can address a multiplicity of perils. While tsunamis are rare, flooding is not. Recent years have witnessed a rise in inland flooding related to tropical storms, atmospheric rivers, and severe convective storms. The communities affected by catastrophic flood events like the recent ones in Texas and New Mexico and the devastating 2024 floods related to Hurricane Helene tend to have even lower flood insurance “take-up” rates than coastal communities.

The most effective risk management will require unprecedented collaboration between public and private sectors. The NFIP, state insurance departments, and private insurers need to work together on pricing models that accurately reflect risk while remaining accessible to coastal communities. At the same time, communities and businesses must plan and invest together to prepare not just one but many potential climate-related risks.

Learn More:

N.J. Quake a Wake-Up Call for Seismic Mitigation, Resilience Investment

Earthquakes:You Can’t Predict Them, But You Can Prepare

Dear California:As You Prep for Wildfire, Don’t Neglect Quake Risk

JIF 2025: Federal Cuts Imperil Resilience Efforts

BRIC Funding Loss Underscores Need for Collective Action on Climate Resilience

Louisiana Senator Seeks Resumption of Resilience Investment Program

Triple-I Brief Highlights Rising Inland Flood Risk

Hurricane Helene Highlights Inland Flood Protection Gap

Removing Incentives for Development From High-Risk Areas Boosts Flood Resilience

Executive Exchange: Using Advanced Tools to Drill Into Flood Risk

Accurately Writing Flood Coverage Hinges on Diverse Data Sources

Accurately Writing Flood Coverage Hinges on Diverse Data Sources

• Global insurtech funding surged 90.2 percent quarter over quarter, reaching US$1.31 billion, the highest level since late 2022 
  
   

• Three mega-rounds over US$100 million were recorded for P&C-focused firms: Quantexa (US$175 million), Openly (US$123 million), and Instabase (US$100 million) 
  
   

• AI-led insurtechs raised a combined US$710.86 million across 60 deals, with an average size of nearly US$ 14 million

For many insurers, the hype has outpaced practical understanding, but that’s changing. As George Shelton, head of venturing at Alchemy Crew Ventures, explains, “AI, and especially generative AI, has raised the bar in terms of what we expect from insurance software.” 

He describes the sector as deeply complex and data-dependent, having historically lagged behind other industries in innovation. That slow pace now leaves room to move.  

“There is plenty of low-hanging fruit,” Shelton says. “But we’re a lot less forgiving of AI than we are of our human counterparts, especially given the wide variety of so-called solutions flooding the market.” 

And he also explains that the top insurtechs don’t lose sight of the end goal. “Insurers are grappling with a perfect storm of significant challenges, many of which are increasingly complex and potentially very disruptive,” Shelton says. “The goal is to help insurers become more agile, resilient, and customer-centric.” 

 

AI has become the defining talking point of the tech space, but insurance leaders are wary of inflated promises and one-size-fits-all platforms. 

“Nearly every solution provider has ‘AI’ in their URL, somewhere on their websites and marketing collateral,” says Demers. “This makes it difficult to assess and distinguish among players, never mind attributing real cost-benefit analysis.” 

He warns that while generative and agentic AI are showing potential, many carriers are still experimenting and struggling to find solutions tailored to their business needs. 

Demers points to specific progress in “co-pilot or agent use cases,” such as claims reserving. Shelton reinforces the point: “AI is a game-changer, but only when implemented thoughtfully.” 

The value lies not in the tech itself but in how it’s trained and deployed. “The real value comes from tailored, insurance-specific AI models that are rigorously tested for fairness and compliance, and that are fully explainable and understood by those using them,” Shelton says. 

Real progress is being made with measurable improvements in: 

“Expectations have soared with the emergence of generative AI,” Demers adds. “The bar is raised high for new innovation, breakthroughs on efficiency and cost advantages, as well as better risk selection and pricing.” 

 

The global market is crowded with vendors offering transformation. However, separating value from industry noise requires operational fluency and a deep understanding of how insurance companies operate. 

Four key patterns emerged across the top insurtech companies based on brokers’ insight: 

• AI expectations are rising fast. Generative AI has become a strategic issue. But off-the-shelf models are losing ground to purpose-built, insurance-specific solutions. 
  
   

• Implementation is now a credibility test. If a system can’t integrate smoothly with legacy infrastructure or deliver value on day one, it doesn’t make it through procurement. 
  
   

• Customization is expected. Off-the-shelf software is being replaced by flexible platforms that adapt to niche product models and market-specific strategies. 
  
   

• Outcomes are everything. Buyers are watching for real impact, reduced loss ratios, faster processing, and better CX. Features alone no longer close the deal. 

For Demers, who previously led major claims operations, staying power, domain expertise, and measurable results remain the hallmarks of top-tier providers. 

“Top providers often bring attendant scale, reliability, and are mature enough to bring insurance acumen as an added dimension,” he says. “The best tends to provide rich benchmarking information as carriers constantly compare performance given the highly competitive market.” 

While established players dominate through stability and scale, newer entrants are also gaining ground. Demers adds, “New entrants often gain traction by offering the latest in technology and innovative influences to set themselves apart.” 

Innovation leader Shelton echoes this sentiment. “Great partners make working with them a no-brainer. As efficiency and profitability pressures mount for insurers, the industry is ripe with opportunity. However, prospective partners must be able to deliver measurable value, on insurer’s terms, from day one, in a flexible, responsive, and collaborative way.” 

 

The insurance industry is under pressure from aging tech stacks, new risk types, evolving customer expectations, and an increasingly complex regulatory environment. 

Technology partners must go well beyond implementation and are expected to bring solutions to systemic challenges while minimizing disruptions to core operations. 

Demers identifies three critical areas where the right tech makes a difference: 

• profitability pressures in stressed lines like homeowners and commercial auto 
  
   

• fragmented systems and expensive tech stacks that hinder efficiency
  
   

• the push to adopt AI responsibly, especially around data quality, privacy, and business relevance 

Shelton offers a complementary list of challenges that insurers expect their vendors to address: 

• growing complexity of risk, from cyber to climate 
  
   

• rising regulatory and data privacy requirements that demand more than box-checking 
  
   

• operational inefficiencies due to layered legacy infrastructure 
  
   

• consumers demanding personalization and digital ease, even as they cut back on spending 
  
   

• internal pressure to launch new products and distribution models without expanding overhead 

“From a strategic point of view, tech and software providers should recognize that their services can extend beyond solving a technological problem toward helping their clients to actively innovate, improve, and develop new products and services, based on smart feedback,” Shelton says. 

 

 

In a space crowded with demos and marketing noise, insurance leaders don’t want to buy promises. Efficiency gains are still table stakes, but they’re no longer the whole story, Demers remarks. 

“At present, revenue growth is probably No. 1, as P&C has restored profitability and underwriting appetites are growing quickly,” he says. “Loss ratios would be a close second. Decision-makers want to see benefits in all, including customer satisfaction.” 

Shelton agrees that evaluating ROI in insurance tech is crucial and must be a blend of quantitative and qualitative data. 

“The magic numbers of loss ratio and expense ratio will always be top of a conventional insurer’s mind,” Shelton says. 

 

Tools that work quickly, integrate seamlessly, and deliver measurable value under current business conditions are the top requirements. 

A comparison of IB’s global ratings from 2023 to 2025 also uncovers a series of trends: 

 

 

• 2024 dip: All criteria experienced a dip in 2024, suggesting either higher expectations or market challenges. 
  
   

• 2025 recovery: All criteria rebounded in 2025, with some reaching their highest levels, indicating improvements in technology offerings or better alignment with broker needs. 
  
   

• Ease of use dominance: This remains the most important factor, highlighting the necessity for intuitive, user-friendly technology. 
  
   

• Customization volatility: The sharp drop and recovery suggest that brokers’ needs for tailored solutions may fluctuate with market or regulatory changes.
  
   

• Consistency in value and support: Value for money and customer support are stable, underscoring their ongoing importance. 

IB’s historical data supports what Shelton and Demers flagged: buyers want platforms that align with their environment, not the other way around. 

“Implementation is not just a matter of speed,” Shelton says. “It’s a marker of whether a provider understands how insurance businesses operate.” 

Customization saw the biggest year-over-year gain, rising 0.22 percent illustrating that off-the-shelf solutions are losing ground to providers who help insurers tailor everything from workflows to product design. Ease of use, already near the ceiling, remains the single highest-rated factor. That reinforces a hard truth that if frontline teams can’t use a platform easily, they won’t. 

 

 

 

Vertafore, one of the industry’s most established insurtech firms, takes a practical approach to innovation. Its innovation strategy prioritizes foundational problem-solving over stacking on unnecessary features. That ethos drives breakthroughs in daily workflows, boosts relationships, and fuels scalable growth for customers. 

Vertafore serves agencies, wholesalers, MGAs, and carriers of all sizes. That reach gives the company a front-row seat to shifting needs across distribution, underwriting, and compliance. 

That insight pairs with an open feedback loop with customers and the NetVU user group, allowing the product team to turn top requests into reality. 

 

One flagship initiative, Project Impact, cuts the time agencies spend on repetitive, high-volume tasks. Vertafore staff shadowed more than 100 servicers across AMS360, Sagitta, and WorkSmart to identify pain points in real workflows. 

The result was dozens of enhancements that have already saved nearly an hour per day for many users. “Innovation is essential for our industry to thrive, but to make a lasting impact, it has to be about more than simply chasing what’s new,” chief project officer James Thom explains. 

“Our innovation process starts with a focus on what’s going to propel our customers’ long-term success. That ensures innovations deliver measurable value, such as quantifiable time savings, improved client retention, faster processes, and business growth.” 

 

 

Launched in December 2024, AgencyOne is Vertafore’s integrated platform built on AMS360 and Sagitta, which brings together everything agencies need to run and grow their business. 

Designed to simplify how agencies operate, AgencyOne includes: 

• sales automation that optimizes day-to-day activity 
  
   

• real-time, competitive quoting and binding 
  
   

• modern digital experiences for today’s insurance clients 
  
   

• streamlined agency management workflows 
  
   

• Data and analytics for smarter decision-making 

Faster navigation and improved search functions alone can free up two weeks per employee per year. “AgencyOne gives a 360-degree view of client information with personalized dashboards and global navigation, making an agent’s work easier every day,” Thom says. “That kind of unified experience translates into real time savings and lets agents spend more time on business growth and client engagement.” 

 

Underpinning Vertafore’s technology is an open-architecture strategy built on APIs and microservices, as well as its Orange Partner program. 

This ecosystem enables agencies, MGAs, and carrier partners to plug in best-in-class tools, extend workflows, and maintain a seamless experience across its suite and complementary technologies. 

In 2020, Vertafore found a permanent home through its acquisition by Roper Technologies. That long-term backing allows Vertafore to reinvest nearly a quarter of its revenue in product development, UX/UI enhancements, and continuous platform modernization. 

Recent design updates emphasize: 

• inclusive principles 
  
   

• improving accessibility 
  
   

• reducing clicks 
  
   

• overcoming situational barriers that slow agents down 

“Our goal is to simplify the entire insurance lifecycle so customers can focus on what matters most to their unique business needs,” he adds. “We’re delivering tools that work today and evolve to meet tomorrow’s challenges.” 

Vertafore will extend the Project Impact approach to new workflows and surface AI-driven recommendations across its platform. Its focus remains on uniting the distribution chain, empowering agencies, MGAs, and carriers with customer-centric solutions that drive real business outcomes. 

 

 

In a market where speed, accuracy, and experience set the minimum bar for competition, automation has become more than a cost-cutting tool. TCG’s flagship platform, DocProStar, combines AI, legacy integration, and no-code process design to deliver speed without adding technical complexity. 

“Initially, clients were primarily focused on cost savings by automating repetitive administrative tasks such as data extraction and email triage,” says managing director Frank Volckmar. “These early-stage implementations delivered a strong return on investment, often achieving payback in under 12 months.” 

Development now sees clients using automation to enhance both employee and customer experiences. “While cost reduction remains important, the focus has expanded to include broader strategic goals; namely, improving employee and customer experiences,” Volckmar says. 

DocProStar stands out for its no-code, BPMN-based interface, which enables claims managers, underwriters, and operations staff to map, test, and refine workflows without writing a single line of code.

“This inclusive approach accelerates automation rollouts while ensuring the people closest to the business challenges can actively contribute to process innovation,” Volckmar says. “The result is faster time-to-value, broader alignment across teams, and more resilient, business-driven automation initiatives.” 

 

TCG designed DocProStar to act as an orchestration layer, connecting legacy platforms to modern AI tools and third-party systems. For many insurers, this ability to bridge old and new is crucial. 

For example, one client now uses DocProStar to ingest claims documents, extract key data, classify inputs, and automate decisions using AI, all while syncing with its core insurance platform for validation. 

“In some implementations, clients also ‘scrape’ data from legacy platforms and merge it with AI outputs within DocProStar, turning fragmented tasks into measurable, end-to-end processes,” Volckmar adds. 

 

 

Despite strong adoption, Volckmar states that many insurers still underestimate what it takes to get automation right: 

• lack of standardization across teams or departments 
  
   

• distrust in AI outputs due to fears of hallucination or inaccuracy 
  
   

• weak evaluation frameworks that fail to weigh privacy, security, and performance 

“With so many services in the market, it’s vitally important to work with specialized consultants who can align technology with actual business needs.” 

 

TCG is focused on expanding AI across high-volume use cases, such as claims and underwriting, through OCTO, a new orchestration module embedded in DocProStar. 

“Use cases already emerging include the integration of AI into legacy applications, validation of incoming data against business rules to enhance data integrity, and AI-powered support for knowledge workers embedded directly in their workflows,” Volckmar says. 

 

In Australia’s motor insurance market, total loss valuation has long been a sticking point. Clunky workflows, inconsistent data, and drawn-out disputes have frustrated assessors and claimants alike. 

AutoGrab has stepped into that gap with its Pre-Accident Valuation (PAV) platform, which combines real-time market data with human-guided decision-making to streamline the process and improve trust. 

“It was fraught with errors,” recalls Denis Flora, national customer manager for insurance. “If they weren’t selecting the right vehicle, it meant they weren’t producing the right value on a total loss.” 

 

During the height of the pandemic, as car prices surged and supply chains crumbled, AutoGrab launched its solution to reduce manual steps and improve consistency. 

By automating the grunt work, matching vehicle identification and description, and drawing on a deep catalogue of advertised listings, the platform reduces the average time per case to seven to 10 minutes, a 60 percent time saving with improved accuracy. 

“The pain was acute during COVID,” Flora says. 

Users are guided through an easy-to-navigate interface and receive a transparent, customer-ready PDF report. 

“Our anecdotal feedback is that nine out of 10 customers agree with the outcome of the report because they’ve got the evidence there,” Flora adds. 

 

 

Settlement value complaints remain among the most frequent insurance disputes in Australia, according to AFCA. To support transparency, AutoGrab’s reports include comparable listings, price history, and state-specific market dynamics. 

“If a customer is dissatisfied with a total loss claim’s value, the insurer can provide the AutoGrab PAV PDF report to show how the value was calculated,” he explains. 

 

AutoGrab’s proprietary catalogue covers 99.3 percent of vehicles under 4.5 tons, dating back to 1983. It’s updated regularly through its global partnerships. 

The coverage is expanding faster than that of other tools on the market, thanks to those partnerships and exclusive access to new models, making it the quickest on the market to grow. 

Advertisements are matched to the catalogue and monitored throughout the sales cycle, including pricing movements, days to sell, and supply and demand dynamics. This data is analyzed to produce an accurate market-reflective price, supported by actual listings and sales data. 

While the platform uses machine learning to suggest an estimated retail value, human expertise remains central to the process, especially in insurance. 

“We present all of the data, insights, and listings to the customer, and they make the call on which vehicles to use in the valuation,” Flora explains. “Every vehicle is unique. It may have different accessories, modifications, or pre-existing damage. That’s where the human interaction comes in.” 

What’s changed is the quality of information behind those decisions. In addition to presenting comparable listings, AutoGrab includes state-based supply and demand stats, odometer averages, and national pricing trends. Flora calls it a holistic picture. 

“That price may be different on the last day of the month compared to the first day of the month because listings may have changed,” he says. “We present all of that to our users to make that call.” 

Since its launch in 2020, AutoGrab now serves insurers and underwriting partners in Australia, New Zealand, the UK, and Asia. While its foundation lies in insurance, the company is well established in other verticals, including dealership platforms, fleet management, finance, and government. 

“Holistically, the automotive industry is our oyster,” Flora says. “But we see really good benefits for insurers, not only to drive their claims performance and policy portfolio performance better, but to improve their customer engagement and transparency, which drives loyalty and retention.” 

AutoGrab is now expanding deeper into the claims lifecycle, from lodgment and repair assessment to underwriting and quote generation. 

Internationally, it already provides fully automated valuations for insurers. In Australia, the hybrid model, combining machine intelligence with human discretion, remains the optimal fit. But the technology is designed to scale. 

 

 

Insurtech is no longer a sandbox for theories. AI may be in the spotlight, but insurers and brokers are focused on what works. They want tools that deliver results. Tech that cuts the noise, fixes the headaches, and helps teams perform more efficiently. 

IB’s 5-Star Technology and Software Providers 2025 have earned their reputation by remaining focused on execution. They’re not selling software; they’re solving problems for brokers and insurers in demanding, complex environments globally. 

 

• AgencyBloc
• Alert Labs
• Applied Systems
• Bentek
• Curium
• Decerto
• EcoClaim
• Folio.insure
• Foxquilt
• InsuredHQ
• Life Design Analysis
• ProNavigator
• Quandri
• QuickFacts
• Quotey.io
• RedBook New Zealand
• SambaSafety
• TCG Process
• Trufla Technology

Personal lines insurance is very price-sensitive. As discussed previously, maintaining a 20+% expense ratio is not feasible for insurers. Beyond pricing, what truly fosters customer loyalty, and how can insurers compete to increase their market share? 

In this blog, I explore strategies for enhancing customer loyalty and retention, provide forecasts on the evolving risk landscape for auto and home insurance, and discuss Accenture’s predictions for how personal lines insurance buying behaviors might shift over the next decade. 

The changing landscape of personal lines risk

Personal lines insurance has evolved from a specialty product to a digital commodity. Initially traded manually, it has now become a globally traded digital product. With around 4 billion vehicles and homes worldwide, personal lines insurance is both a global commodity and a constantly evolving risk. 

The risk landscape varies significantly between auto and home insurance. Auto insurance covers a homogenous risk profile with approximately 600 common vehicle models globally. The rise of electric and autonomous vehicles is reshaping road regulations and vehicle repair processes and introduces new risks requiring product liability and cyber coverages. 

Conversely, home insurance covers a heterogeneous risk profile with countless types of homes and building standards. The underlying home risk is significantly impacted by extreme weather that affects both frequency and severity of the damages. It’s fair to predict that extreme weather will not only impact ratings, but also building codes which would provide additional variables to price on. 

While home and auto insurance represent key areas for personal lines insurance, consumers are also coping with the impacts of large-scale disruption – a volatile economic environment, residual impacts of the COVID-19 pandemic and the ongoing technology revolution have all shifted global dynamics significantly. Today, a consumer’s felt need for insurance is high, and the areas of risk that have them most concerned are shifting. We found that the rising cost of living and climate change were two top areas where consumers felt concerned about the risks but also least protected. 

Generational shifts in insurance buying

The core consumers of insurance are changing. Millennials, the first generation of digital natives, are entering their peak insurance buying years. Insurers must cater to this demographic’s unique needs. Across all demographics, there is a demand for more, better, and faster services. Consumers want their unique needs met quickly and easily and are willing to share their data in exchange for a tangible better experience and product. 

Strategic areas for enhancing value proposition

1. Brand identity in customer interactions: Ensure that the brand identity is palpable in every customer interaction, creating a consistent and recognizable brand experience across all touchpoints. 
2. AI-augmented employees: Instead of focusing on implementing AI solutions, focus on augmenting employees with AI to provide more personalized and empathetic interactions, ensuring customers feel deeply understood. This is a fine, but critical nuance.  
3. Compelling digital experiences: Craft digital experiences that foster emotional connections. For instance, in travel insurance, offering dynamic updates on extreme weather, top tourist attractions, and local health advisories can significantly enhance customer engagement. Traditional risk mitigation notifications do not foster emotional connections with the customer.  
4. Real benefits for digital adoption: Ensure customers recognize tangible benefits from adopting digital channels, such as significantly faster resolution times and personalized digital interactions, making the digital shift worthwhile. 

Creating compelling digital experiences for customers is key for enhancing customer loyalty. Recently, we worked with an insurer to address low engagement between agents and customers, insufficient customer information, and a lack of visibility for managing leads. The insurer and Accenture deployed an AI-enabled app to their customers; the app was incredibly intuitive and built using a scalable design for market adoption across Asia. The solution offered automated customer relationship management, marketing content recommendations, next-best-action recommendations, customer insights, 360 degrees customer insights, and agent performance management.

The results? 424% premium growth and 671% pipeline generated, proving that compelling digital experiences are worth their weight in gold. 

Shifts in consumer buying channels

Traditional methods of purchasing insurance through brokers and agents are expected to decline in favor of direct sales and embedded insurance models. Munich RE have said that embedded insurance is projected to grow at a CAGR of 25% until 2030, potentially accounting for over US$ 500 billion in gross written premiums globally by 2030 for P&C lines. 

Consumers show increasing interest in embedded insurance offers, where relevant risk protection is integrated into their purchase. For example, the share of consumers likely to buy auto insurance from a car dealer has increased from 32% to 42% since 2018. Consumers also want solutions beyond traditional home and auto insurance bundling, such as complete house buying services and home monitoring services. 

Focus areas for insurers

1. Performance and efficiency: Develop the best features and products. 
2. Experience and convenience: Delight customers with exceptional service. 
3. Solving, not selling: Play a relevant role in customers’ lives while creating value for all. 

As the insurance landscape evolves, we must continue to harness the power of AI to turn challenges into opportunities. By empowering businesses with AI-driven solutions, we don’t just create tools – we transform possibilities into measurable success. In this journey of innovation, we redefine what’s possible, ensuring that the future of insurance isn’t just anticipated – it’s actively shaped. 

As property/casualty insurers increase their focus on predicting and preventing costly damage that drives up claims and premiums, telematics technology has come to play an increasing role.  From video doorbells that reduce theft and vandalism to “smart plumbing” solutions that detect leaks and shut off water before in-home flooding can occur, these technologies clearly offer value to homeowners and insurers.

But how much value?

Whisker Labs – maker of the Ting home fire prevention solution – has taken on the challenge of quantifying its product’s efficacy and return on investment. In a research partnership with Octagram Analytics for independent data analysis and modeling and Triple-I for its insurance industry expertise and insight, Whisker Labs found that Ting reduced fire claims within the study sample by an estimated 63 percent, resulting in 0.39 fewer electrical fire claims per 1,000 home years of experience, in the third year after installation. This translates into a fire claims reduction benefit of $81 per customer. 

“This study provides concrete evidence of the value that telematics technology can deliver,” said Patrick Schmid, chief insurance officer at Triple-I. “While IoT solutions are gaining traction with many success stories, rigorous analysis of claims reduction has been harder to find until now.  This analysis clearly shows Ting reduces claims and provides a positive return on investment for insurers.”

The research can be read here.

How Ting works

Ting helps protect homes from electrical fires by using advanced AI to detect arcing, the precursor to most electrical fires. Once connected to a single outlet, Ting analyzes 30 million measurements per second, analyzing voltage at high frequencies to detect tiny electrical anomalies and power quality problems. These hazards can originate from wiring in the home, connected devices and appliances, or even the power coming in from the utility. On average, Ting detects and mitigates fire hazards in 1 out of every 60 homes it protects.

“Ting is about saving lives and homes – that’s always been our mission,” said Bob Marshall, CEO and cofounder of Whisker Labs. “By analyzing verified claims data over time, this analysis shows that what’s best for families also delivers a strong financial return for insurers. Prevention is better for everyone.”

Whisker Labs works with a growing community of 30 insurers who provide Ting to their customers for free.  More than one million Tings are deployed in the United States, and approximately 50,000 new Tings are installed each month.

In addition to monitoring voltage and features of voltage at high frequencies to detect arcing that is indicative of fire hazards, Ting has a temperature sensor that monitors the temperature within the home. 

“When the temperature drops below 42 degrees, an alert is issued,” Marshall said. “Thus, Ting detects and warns about conditions that can result in frozen and burst pipes and alerts the homeowner to correct the situation before damage occurs.  Over the past three years, we have issued low-temperature warnings to about 1 in 560 customers per year.”

Measuring the value

Like Ting, other peril-based IoT solutions issue alerts and warnings when a hazard is detected.  Thousands of hazards are detected and alerts sent, but how do you know that this reduces claims?  How do you estimate the return on investment for these devices?  How can you prove that the bad thing, a loss and a claim, didn’t occur? 

“We developed a methodology to do this in the real world with existing customers and experience data,” said Whisker Labs Chief Scientist Stan Heckman.

Whisker Labs and Octagram had to overcome challenges related to limited data and sampling bias. To address these, a self-controlled study was developed that assesses claims over time in homes with Ting in place.  (See paper for a fuller explanation of the methodology).

The chart below shows how the number of fire claims in Ting-equipped homes declines over time. The claims frequencies observed and associated percent reduction in claims are highly dependent on the definition of the sample of non-cat fire claims provided by carriers that participated in the analysis.  However, this does not affect the observed absolute reduction.

Using data from Triple-I and Verisk, Whisker Labs determined that Ting provides a loss-prevention benefit of $81 per home per year. (See paper for details).

“Add in benefits associated with reduction in water-related losses from frozen pipes and failing sump pumps and water heaters,” and the benefits are likely substantially higher, Marshall said. Insurers who provide Ting to their policyholders also may enjoy improvements in customer retention.

Learn More:

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JIF 2024: What Resilience Success Looks Like

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Triple-I Town Hall Amplified Calls to Attack Climate Risk

For the legal profession, 2024 marked a dramatic shift for lawyers, as legal professionals embraced transformation at an unprecedented pace across technology adoption, risk management, and business strategy.

Our newly released 2025 Legal Industry Risk Index, based on a comprehensive survey of 245 full-time legal professionals across the United States, reveals an industry that has found its footing in our new AI and technology-driven landscape and is confidently charting a bold new course forward.

The AI Revolution Finally Arrived

Perhaps the most striking finding is the legal industry’s complete about-face on artificial intelligence. After years of cautious skepticism, AI adoption exploded from a mere 22% in 2024 to an impressive 80% in 2025. Legal professionals didn’t just dip their toes in the water—they dove headfirst into strategic AI applications.

This isn’t just about basic content generation anymore. Today’s legal professionals are using AI to enhance professional services, automate client support interactions, and more. The profession has officially gotten its “AI sea legs,” with confidence levels rising dramatically as practical experience seemed to take slight precedence over theoretical concerns.

Risk Priorities Get a Complete Makeover

The shifting risk landscape tells an equally compelling story. For the first time, financial pressures—which dominated legal professionals’ concerns for the last two years—have been dethroned. Reputational challenges and employment-related claims now tie for the top internal risk, reflecting the complex realities of managing modern law firms in an increasingly polarized social and political environment.

External threats have evolved too. While inflation concerns that once kept 52% of legal professionals awake at night have reduced to 28%, new challenges around disruptive technology adaptation and professional liability threats have taken center stage.

The Great Insurance Awakening

Perhaps most telling is how legal professionals are responding to these shifts. Rather than retreating into defensive positions, they’re proactively strengthening their safety nets while simultaneously becoming more willing to take calculated risks.

The insurance landscape transformation is remarkable: 45% of legal professionals are upgrading their coverage—a staggering jump from just 14% who had such plans the previous year. This isn’t panic buying; it’s strategic preparation. An impressive 77% now express confidence that their current insurance policies cover their greatest business risks.

Confidence Meets Calculated Risk-Taking

This newfound insurance confidence appears to be enabling bolder business strategies. Legal professionals are increasingly viewing risk through an opportunistic lens, with 37% now seeing risk as a pathway to growth—more than double the 18% who held this view just one year prior.

The data reveals a profession that has moved beyond uncertainty paralysis. Where 41% of respondents were “unsure” about their risk response approach after facing challenges in 2023, that figure plummeted to just 4% in 2024. Legal professionals know what they’re doing and why they’re doing it.

What This Transformation Means

The legal industry appears to have reached a critical inflection point where technological adoption, strategic risk management, and protective planning are working in concert rather than competing for attention.

The legal professionals who are thriving aren’t avoiding change—they’re anticipating it, preparing for it, and positioning themselves to capitalize on the opportunities it creates.

The Complete Picture

While these headline findings paint a picture of an industry in confident transition, they represent just the surface of our comprehensive analysis. The full 2025 Legal Industry Risk Index dives deeper into the specific applications driving AI adoption success, the nuanced factors behind the reputational risk surge, and more.

Ready to see how your firm compares to these industry-wide trends? Get the complete Legal Industry’s 2025 Risk Index to access all findings, detailed analysis, and strategic insights that can help position your practice for success in this rapidly evolving landscape.

In the context of fractious global trade dynamics, businesses have no choice but to adapt their strategies for planning, pricing and protection. The interconnected nature of the global economy means that instability in one sector often has ripple effects across others.  

Insurers are no exception to this with recent trade developments having introduced a more volatile environment also impacting both the demand for and the cost of providing insurance. US inflation is set for a potential increase of 0.8-2.8% while we might face a potential decrease in global Gross Domestic Product (GDP) of 0.3-3.9%. In addition, resulting higher US Treasury Yields mean the risk for a liability-asset portfolio mismatch can intensify for life insurers and shrinking reinvestment yields pressurize earnings. According to our calculations, just US households face potential additional yearly costs of $4900. 

Life and P&C segments are particularly affected, with likely reductions in demand due to lower disposable incomes and reduced consumer spending. As insurers navigate these challenges, they are also grappling with reduced risk pools and lower premium appetites. Additionally, higher claims severity is leading to increased indemnity costs, and the volatility of financial results is adding another layer of complexity.  

However, while the rising risks of inflation, GDP decline, and market confidence erosion may lead to softer demand, higher cost of claims, and increased volatility in the long term, these challenges also present opportunities for innovation. But above all, boosting their overall resilience will be critical for insurance companies as they navigate a shifting economic landscape and markets in flux. 

Resilience as a gateway to opportunity 

Resilience can be defined as a company’s ability to withstand and adapt to uncertainty and volatility, and to emerge stronger by building the capabilities needed for long-term, profitable growth. As the meaning of the word evolves, too many companies might remain anchored to outdated playbooks. We are witnessing a fracturing as a result, with the divide between strong and weak organizations widening. Resilience actually delivers its greatest value in times of disruption, with our research showing that the most resilient organizations outperform their peers during high-stress periods with faster revenue growth and higher profit margins.  

There are four key areas that insurance executives will need to focus on to become more resilient: 

1. Operational resilience: Operational efficiency is impacted by increasing competition, rising operating costs, evolving customer expectations and buying patterns, as well as the changing nature of risk. To maintain a competitive edge and improve overall business health, insurers should consider long-term, structural cost reductions by equipping their organizations with future-ready technology and operations. Embracing human and machine collaboration – through the integration of automation, data and AI with human insight – can elevate business outcomes and employee performance. 

Building operational resilience also requires reinforcing supply chain resilience by implementing strategic changes in sourcing, procurement and network strategy, followed by a focus on reinventing cost and productivity through spend optimization. To optimize costs, improve efficiency and expand market reach, insurers could consider adopting strategies that leverage resources, services and capabilities from various geographic locations. This includes utilizing Global Capability Centers (GCCs) to access specialized expertise and drive cost-effective operations. Additionally, exploring innovative distribution models can streamline how insurance products and services are delivered to customers. For example, embedded insurance integrating policy offerings directly from e-commerce or travel platforms enables customers to purchase coverage without visiting an insurer’s website. 

2. Commercial resilience: Develop a pricing and commercial strategy that can help navigate trade uncertainties by addressing cost absorption, price adjustments and the commercial structures that can support these changes, while exploring growth and M&A opportunities in a slower economic environment. Insurers are being forced to make quick, strategic decisions about which costs to absorb and which to pass on to customers. This comes against a backdrop of already rising claims costs and premiums for many insurance customers, particularly in auto and home insurance. By moving beyond transactional interactions and one-size-fits-all solutions to understanding customer preferences and offering innovative, behavior-based products and services, insurers can create new opportunities for sustained, profitable growth. 

3. Technology resilience: The strongest performing businesses in this area have a focus on cybersecurity, AI and data capabilities. Insurers can accelerate their AI efforts to drive enterprise productivity, which should be accompanied by implementing a system to deploy autonomous agents to monitor real-time data and identify potential risks. Insurers should also introduce stronger safeguards and secure processes to account for geopolitical risks and cyber threats. AI and data analytics can transform customer engagement by processing large volumes of data to identify patterns and trends in customer interactions. To realize the full potential of AI, insurers will need to build a secure digital core supported by a simplified cloud infrastructure and powered by a robust data and model ecosystem.  

4. People resilience: Last, but certainly not least, is the talent component. Insurers can make all the technology investments they want but without employees to interpret, apply and scale these tools, they could find themselves at a competitive disadvantage. To build an agile workforce, insurance leaders should implement a talent and recruitment strategy that offers and prioritizes continuous growth and diverse career paths to attract and retain highly skilled talent. With the industry facing a retirement crisis, reinforcing an employee value proposition that moves away from the perception of ‘tenured’ positions and manual task-oriented stagnant jobs to one that emphasizes the purpose-driven nature of the industry becomes critical. They can lean on AI to identify skills gaps and encourage their workforce to upskill and improve their digital dexterity. For example, AI can help underwriters work more efficiently by reducing the time dedicated to routine activities. As AI redefines the historical apprenticeship-based career path, insurers will be prompted to adopt new talent sourcing strategies that tap into external expertise across the spectrum of domain knowledge.  

Resilience will be the key differentiator of the future 

In a world of uncertainty, adaptive resilience is the most valuable corporate asset. While many would liken resilience to a mattress, using it to soften the landing or cushion the blow, it should act more like a trampoline, absorbing the impact and propelling the company forward, creating new value. Resilience is the key differentiator in any future scenario. It should be built as a cohesive, company-wide strategy, not in isolated silos. Companies that adapt and enhance their responses to policy changes would be better equipped to handle uncertainty.  

For those looking to implement transformation programs to build more resilient businesses, it might be worth having a look at our latest insurance thought leadership that analyzed a variety of change programs across the industry. One key observation is that transformation needs to be precisely defined, tightly aligned to business outcomes and supported by decisive action. Small gaps in clarity, consistency and execution—compounded over time—could lead to large gaps over time. I am interested in your views on this topic – feel free to contact me on Linked in.  

 

By Lewis Nibbelin, Contributing Writer, Triple-I

Identifying key risk trends amid an increasingly complex risk landscape was a dominant theme throughout Triple-I’s 2025 Joint Industry Forum – particularly during the panel spotlighting some of the insurance industry’s C-suite leaders.

Moderated by CNBC correspondent Contessa Brewer, the panel consisted of:

• J. Powell Brown, president and CEO of Brown & Brown Inc.;
• John J. Marchioni, chairman, president, and CEO of Selective Insurance Group;
• Susan Rivera, CEO of Tokio Marine HCC (TMHCC); and
• Rohit Verma, president and CEO of Crawford & Co.

Their discussion provided insight into how insurers can transform these uncertainties into opportunities for business development and for cultivating deeper connections with consumers.

Recouping policyholder trust

Given the volatility of the current risk environment – exacerbated by various ongoing geopolitical conflicts and the rising frequency and severity of natural catastrophes – it is more imperative than ever to reaffirm the intrinsic human element of insurance, the panelists agreed.

“That’s one of the most underappreciated aspects of our industry,” Marchioni said. “We make communities safer and put people’s lives and businesses back together after an unexpected loss. Being the calming force when you have unsettling events like this happen around the world is a big part of what we do.”

Yet prevailing public perception continues to indicate otherwise, even as insurers report repeated losses or nominal profits compared to other industries.

“The insurance industry may be the only industry where record profits are a problem,” CNBC’s Brewer added, because consumers tend to “not care whether it’s coming from your investments, or whether it’s coming from your underwriting business or your reinsurance. They just hear that you’re making record profits.”

Brown noted that consumer mistrust derives, in part, from “a very active plaintiffs’ bar,” which the American Tort Reform Association estimates spent over $2.5 billion for nearly 27 million ads across the United States last year. He further discussed how, though the average homeowners’ insurance premium rate in Florida will increase this year, his home state has enjoyed far more stable rates after tort reforms eased litigation costs on insurers.

Previous research by the Insurance Research Council (IRC) – like Triple-I, an affiliate of the Institutes – showed that most consumers perceive the link between attorney advertising and higher insurance costs. Crawford’s Verma, however, emphasized that this awareness does not necessarily translate into consumers understanding their own agency.

“It’s easier for homeowners to understand how the weather impacts potential losses and the fact that weather patterns have changed,” Verma said. “But when it comes to [legal system abuse], I don’t think that connection is as well understood.”

Reflecting on a record high in nuclear verdicts last year, Rivera suggested insurers must reconfigure how they communicate legal system abuse to consumers.

“Where are those hospital professional liability verdicts going to go?” he said. “They’re going to go back into the cost of health care at the end of the day.”

Leading the AI charge

Maintaining consumer centricity while implementing or experimenting with technological innovations – especially generative AI – was a unifying objective for all the panelists.

“We look at AI as an enabler,” Brown said, “so we can put teammates in a position to spend more time with customers, which is the most important thing.”

For Tokio Marine’s Rivera, AI “ultimately helps all of our insureds” by boosting operational efficiency while reducing operational costs, as well as facilitating more proactive risk management than ever before. A growing percentage of insurance executives appear to agree, as generative AI models continue to expedite data processing across the insurance value chain, reshaping underwriting, pricing, claims, and customer service.

Such efficiency, paired with the potential for improved decision-making, is crucial “in our dramatically changing environment,” Marchioni stressed.

“We have thousands of claims every day,” he said. “Thinking about lawsuit abuse as a backdrop – a claims adjuster, every day, has to make decisions regarding, ‘Do I settle this claim based on injuries or venue? What’s the value of the injury and of the claim? Who’s the plaintiffs’ attorney?’ These tools give more refined information so your knowledge workers can make better, more timely decisions.”

Generative AI fails, however, when base datasets are insufficient, outdated, or inaccurate, Brown pointed out. Training AI models uncritically can lead to outputs containing false and/or nonsensical information, commonly known as “hallucinations”.

At their current capacity, at least, AI models cannot draw the kinds of salient conclusions that adjustors and underwriters can, meaning AI could “change the way we work, but it’s not going to replace the jobs,” Verma said.

Though they do not currently exist in the United States at the federal level, AI regulations have already been introduced in some states, following a comprehensive AI Act enacted last year in Europe. With more legislation on the horizon, insurers must help lead these conversations to ensure that AI regulations suit the complex needs of insurance, without hindering the industry’s commitments to equity and security.

A 2024 report by Triple-I and SAS, a global leader in data and AI, centers the insurance industry’s role in guiding conversations around ethical AI implementation on a global, multi-sector scale, given insurers’ unique expertise in analyzing and preserving data integrity.

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Triple-I Issues Brief: Cyber Insurance (Members Only)

Triple-I Issues Brief: Legal System Abuse (Members Only)

Recently, many leading insurers have applied transformative solutions to enhance their cyber products. With the cyber insurance market projected to double to $29B by 2027, we explore what constitutes market-leading cyber claims management.  

In this blog we’ll delve into the complexities of responding to cyber claims, the essential skills required by claims adjusters, and the measures insurers must take to achieve excellence in cyber claims management. 

The complexity of cyber claims  

The most comprehensive cyber coverage encompasses a broader range of perils than most other insurance products: 

1. First-party coverages: This includes damage to devices, network damage, physical property damage, and damage to digital assets. It also covers damage to or theft of intangible assets, theft of funds, and costs associated with recovery, restoration, and remediation. Financial losses due to business interruption, lost business opportunities, reputational damage, ransomware, and extortion are also included. Additionally, expenses related to investigations, notifying affected third parties, and damage to intellectual property such as patents and trademarks are covered. 

1. Third-party coverages: These coverages include contractual and legal liability, regulatory proceedings, and multimedia liability. They also encompass civil damages, compensation, payment card loss, errors and omissions, technology professional liability, miscellaneous professional liability, and network security and privacy liability. 

When the policyholder of a comprehensive cyber product is a large multinational corporate business with both B2B and B2C customers, handling a potential large-scale claim becomes highly complex for claims adjusters. Cyber claims, akin to oil spillages, are catastrophic by nature, recognize no geographical boundaries, and are continuously evolving and unpredictable. Cyber breaches can critically impact businesses, societies, and essential national infrastructure, including hospitals, water and sewage systems, and airports. 

The complexity, however, extends further. Cyber claims pose unique challenges to today’s claims adjusters due to the intricate technical nature of the claims, which involve IT systems, both tangible and intangible assets, cybersecurity protocols, digital forensics, and the constantly changing regulatory and legislative landscape concerning data protection, AI protection, and privacy law across all affected jurisdictions. 

Furthermore, a cyber claims adjuster must be adept at instructing and managing a diverse group of specialists, ranging from IT forensic experts, data experts, and forensic accountants to credit monitoring experts, legal breach counsel, public relations experts, crisis management professionals, and ransomware attack experts. 

The skills of a cyber claims adjuster 

The skills of a cyber claims adjuster are multifaceted and require a detailed understanding of various aspects: 

Knowledge Requirements: A cyber claims adjuster must possess advanced, industry-recognized qualifications and typically have a background in Errors & Omissions (E&O), Trade Credit, Political Risk, and/or Crisis Management. They need practical knowledge of applying first and third-party cyber coverages, reserving, evaluations, and risk management processes, usually gained from previous roles in cyber claims or broker advocacy. 

Experience Requirements: The industry faces challenges due to a limited talent pool. It’s crucial for adjusters to understand the roles and responsibilities of various experts involved in cyber claims. Their practical experience is vital for effectively overseeing and managing these experts to ensure rapid response to claims, effective mitigation actions to prevent further losses, and complete resolution of claims. Cyber claims have grown in complexity and quantity, but many adjusters come from auxiliary lines of business. A key skill often missing is proficiency in IT systems, cybersecurity protocols, digital forensics, intangible assets, and a deep understanding of constantly evolving regulations and legislation across IT, AI, GDPR, and consumer privacy. This is particularly critical when insurance covers technology-based companies, where coverage is often bespoke and niche. 

Operational Responsibilities: Adjusters must effectively determine the existence, cause, and scope of a breach and manage key activities in cyber claims management. This includes selecting and managing the appropriate incident response team, assessing ongoing or concluded breaches, evaluating the impact on the customer’s business and assessing breaches of cybersecurity protocols. It also covers responding in compliance with current data protection and privacy regulations, identifying and responding to fraud triggers, and providing feedback into underwriting risk controls and actuarial tables. 

Customer Segment Knowledge: Proficient knowledge and experience with a range of customer segments, from SMEs to multinational and large corporate clients, are also essential for a cyber claims adjuster. Because Cyber is such a swiftly evolving product and still sub-scale to many other lines, insurers face the difficult question of whether to organize their Cyber claims team as a line of business CoE or whether to adhere to existing CoEs centred around SME, mid-market, multi-national clients etc. 

Emerging risks and challenges 

The task of determining the existence, cause, and scope of a breach is becoming increasingly complex due to the extensive coverage of cyber insurance, rapid technological and data platform evolution, the catastrophic and systemic risks associated with breaches, and the implications of Gen AI. Gen AI presents new opportunities and challenges, enhancing capabilities for both cyber attackers and defenders, leading to more sophisticated attacks almost daily.  

The strategic choices to become market-leading in cyber claims  

In conclusion, there are four key components to get right:  

1. Insurers need a claims application that supports the adjusters in effective management of the incident response team and experts. The application needs to be fit-for-purpose for cyber, which means a comprehensive master data management to orchestrate the 100+ relevant cyber claims data points as well as an expert-specific permission access to documents.
2. Insurers need a comprehensive and continuous development program to remain proficient in evolving cyber risk, technology changes and especially the opportunities and challenges that Gen AI represent. 
3. Insurers need a comprehensive cyber saferoom that provides a secure space for pre-incident advice and training, incident response planning, notification services, etc. The saferoom must have the right guardrails that support collaboration with the independent legal breach counsel.
4. Insurers need a continuous feedback-loop of claims master data that inform the actuarial tables and the risk controls in underwriting. Market-leading insurers achieve this with a scalable infrastructure and architecture, so that the technical pricing across all variables is informed in real-time based on loss history.