AAIS hosted the webinar AI Exploitations: How P&C Insurers Can Protect Themselves, featuring insights from Joseph Petrelli, President of Demotech, and Todd Kozikowski, CEO of 4WARN, with Werner Kruck, President and CEO of AAIS, moderating. The session explored operational, legal, and reputational implications of AI-driven threats, giving insurers practical guidance to identify exposure, implement safeguards, and stay ahead of evolving fraud techniques.

Lessons From Insurance Market and Carrier Failures

Petrelli opened the conversation by examining recent trends in claims and litigation, pointing to Florida’s wave of insurer insolvencies in 2020. Several carriers collapsed despite strong financial ratings, adequate reinsurance protections, capital contributions, and unqualified audits. “The safeguards were in place, but the issue was claims, not solvency,” Petrelli explained.

He pointed out that litigation surged to unsustainable levels, overwhelming even well-managed insurers. New technologies accelerated solicitation and claim manipulation, allowing opportunistic actors to reach policyholders faster and at greater scale. What might once have been a localized or manageable challenge quickly cascaded into systemic risk for the market.

Petrelli emphasized that this historical perspective carries an urgent lesson: vulnerabilities in operations and claims handling can undermine carriers regardless of their balance sheet strength. As AI becomes more prevalent, he cautioned, insurers face similar dynamics—only now the risks are amplified by the speed, automation, and reach of digital manipulation.

The Evolution of Fraud with Digital Risk

Digital fraud in insurance has shifted from opportunistic scams to highly organized, scalable operations. Kozikowski explained that one of the most concerning developments is Ghost GPT—malicious, customized AI models sold on the dark web. These tools have effectively created a “fraud-as-a-service” market, enabling even non-technical actors to launch sophisticated attacks.

He noted that by flooding the internet with manipulated content, bad actors can influence multiple AI platforms simultaneously, producing consistent but false responses that shape consumer perception and behavior. “These tools are lowering the barrier to entry for fraud,” Kozikowski emphasized. “Insurers need to understand the external attack surface just as well as their internal systems.” As fraud becomes more organized, AI itself has emerged as a new attack surface for these coordinated campaigns.

AI as a New Attack Surface

AI has introduced entirely new vectors for exploitation. Fraudsters are no longer limited to internal systems—they can manipulate public data, SEO strategies, and digital channels to amplify attacks. From generating fake content to influencing search engine results, AI-enabled threats are faster, more sophisticated, and increasingly difficult to detect.

Kozikowski explained that coordinated fraud campaigns are rarely confined to a single tactic; instead, they operate as layered operations designed to overwhelm insurers from multiple angles at once. He pointed to black hat SEO campaigns as a growing threat, where fraud actors flood search engines with fake websites and keyword-optimized content that impersonate legitimate insurers or legal resources.

At the same time, Kozikowski said, these groups deploy AI-generated articles, reviews, and social posts to reinforce the false narrative, ensuring that consumers and even automated systems encounter consistent—but misleading—information across platforms.

He also noted the rise of coordinated litigation solicitation efforts, where fraud networks use AI-driven digital ads, text campaigns, and robocalls to push policyholders toward opportunistic lawsuits. By automating outreach and scaling rapidly, these campaigns can generate litigation volumes that overwhelm carriers, regardless of their financial strength.

“What we’re seeing is a lifecycle of propagation,” Kozikowski said, “where fraudsters create content, amplify it through multiple channels, and then reinforce it with claims or legal action. The digital ecosystem gives them a playbook to move faster than insurers can respond if we’re not paying attention.” Understanding these external and internal vulnerabilities is critical, and 4WARN has developed strategies to help insurers respond proactively.

Mitigation Strategies and Industry Collaboration

4WARN was founded to help insurers understand and defend against emerging digital threats, focusing on how fraud campaigns spread and take root across the internet. By tracking the propagation lifecycle of fraudulent content and analyzing claims and litigation patterns, 4WARN enables insurers to anticipate and address risks before they escalate. “Our goal is to see the threats early, understand how they’re evolving, and work with the industry to stop them before they cause real damage,” Kozikowski said. Through continuous monitoring, trend analysis, and close collaboration with industry partners, insurers can proactively strengthen their defenses rather than simply reacting after the fact.

Kozikowski also stressed the importance of education and awareness, equipping internal teams to recognize early signs of AI-driven manipulation—such as brand impersonation or black hat SEO tactics, where fraud actors deliberately game search engine algorithms to elevate misleading or malicious content. He pointed to the growing role of third-party litigation funding networks, which can magnify the reach and financial impact of AI-enabled fraud. According to Kozikowski, this evolving threat landscape underscores the need for insurers to adopt proactive, layered defenses and integrate AI risk monitoring into their core risk management frameworks.

Staying Ahead of AI-Driven Fraud

As AI technology continues to advance, so too will the methods of bad actors. Insurers are encouraged to build robust internal governance structures, invest in advanced monitoring tools, and foster industry collaboration. “Understanding the AI attack surface—inside and outside the organization—is essential to protecting operational integrity, compliance, and consumer trust,” Kozikowski concluded. By taking a proactive approach, insurers can safeguard their operations and maintain confidence in an increasingly complex digital environment.

To view the full webinar, click on the video above.

Questions? Please reach out to any of the featured speakers through the contact information below.

Werner Kruck
President & CEO, AAIS
wernerk@aaisonline.com

Joseph Petrelli
President, Demotech
jpetrelli@demotech.com

Todd Kozikowski
CEO, 4WARN
todd@4warn.com

The post Webinar: AI Exploitations: How P&C Insurers Can Protect Themselves first appeared on AAIS.

If you’ve been in the industry long enough, the current AI conversation may feel reminiscent of the Agile revolution that swept through IT departments in the early 2000s. Back then, Agile was the hot topic. Today, AI has taken its place. But the parallels are more than superficial. The missteps many insurers made in their Agile transformations offer cautionary lessons—and opportunities—for how we approach AI implementation now.

Agile: A Cautionary Tale of Incomplete Transformation

Agile methodology was born around the turn of the century out of a desire to overhaul the pre-existing Waterfall methodology known for rigid, documentation-heavy development processes. It promised more alignment with the customer, faster delivery, higher quality, continuous feedback, and more customer-centric outcomes. The Agile Manifesto, published in 2001, was a rallying cry for a better way to develop software—one rooted in iteration, collaboration, and adaptability.

Fast-forward to today: ask any insurer if they’ve adopted Agile, and most will say yes. But peel back the label, and the reality is more nuanced. What many organizations call Agile is, in practice, Hybrid Agile—an undefined blend of Agile and traditional Waterfall practices.

Why Did This Happen?

Because most companies didn’t fully commit. They adopted Agile ceremonies—standups, sprints, backlogs—without embracing the cultural and operational changes required to make Agile truly work. Agile wasn’t just a process shift; it demanded new ways of thinking about leadership, accountability, team structure, and value delivery. But many insurance organizations never invested in the change management necessary to drive that deeper transformation.

The result? Agile became a buzzword. A checkbox. And many of the benefits it promised—greater speed, higher quality, better alignment with customer needs—were never fully realized. Project failures, delayed implementations, and disappointing outcomes became common, despite “Agile” being the official methodology.

Human Resistance to Change

To understand why Agile adoption fell short, we need to acknowledge a simple truth: change is hard. Humans are wired for comfort and predictability. Even when change is necessary—or desirable—it can be deeply uncomfortable. As anyone who’s ever tried (and failed) to stick with a new diet or exercise routine knows, sustaining change is exponentially more difficult than starting it.

Now multiply that resistance across an enterprise. You’re not just asking individuals to change; you’re asking teams, departments, and entire business units to work differently. And if only some adopt the new approach while others resist, the result is friction and dysfunction.

This is why true transformation requires more than just new tools or processes—it requires a deliberate, strategic approach to people and culture. In other words: change management.

Change Management: The Missing Link

Change management isn’t about IT, or even methodology. It’s about people. It’s about psychology, motivation, leadership, and learning. It’s a discipline in its own right—just like finance, operations, or claims.

Agile transformations that succeeded had one thing in common: they were supported by formal change management strategies, often led by dedicated teams that reported directly to the C-suite. These teams didn’t just roll out new software practices; they enabled deep organizational change. They aligned HR, finance, operations, and leadership to a shared vision. They provided training, coaching, communication, and cultural reinforcement. In short, they treated transformation as a human endeavor.

AI: A New Era, Same Story?

Today, we’re on the brink of another transformation—this time driven by AI. And once again, the signs are familiar. AI is everywhere in the headlines. Executives are eager to say their company is “doing AI.” Vendors are marketing AI-powered solutions for every pain point. But in many cases, the implementation is superficial. AI, like Agile, is not a plug-and-play solution. It’s a capability that must be aligned with real business problems. It requires not just technical infrastructure, but organizational readiness. It requires oversight, governance, ethical considerations, and cultural adaptation. And, most critically, it requires humans—skilled, empowered, and change-ready humans. Without that, AI risks becoming yet another buzzword. Another checkbox. Another opportunity squandered.

Learning from the Past to Succeed in the Future

If the insurance industry is to harness the full power of AI, we must treat its implementation not as a technical rollout, but as a business transformation. We must invest in the people side of change—just as we should have with Agile.

That means:

• Appointing change leaders who report into the C-suite and have the authority to drive cross-functional alignment.
• Training managers and teams not just on AI tools, but on new ways of working, decision-making, and collaboration.
• Defining success criteria that go beyond technical deployment to include adoption, impact, and cultural fit.
• Creating space for learning and iteration, understanding that transformation is a journey, not a sprint.

At INFORCE, we’ve seen firsthand how critical the human element is to technology implementation success. Effective systems integration implementations require more than IT know-how; they need seasoned leadership, effective change management, and client-centric people. That’s why we created our INFORCE Academy: to train our team on systems integration and to develop the cultural, technical, and behavioral skills needed for transformation. We specialize in building high-performance teams that can lead and sustain change, from Agile to AI and beyond.

Final Thoughts

As we enter the AI era, the stakes are high. This technology has the potential to redefine how we serve customers, manage risk, and create value. But it won’t succeed on its own.

To unlock its promise, we must lead with intention. Let’s learn from our past. Let’s prioritize people, process, and purpose. Let’s approach AI not just as a tool, but as a transformation. That’s how we’ll turn AI from a buzzword into a breakthrough.

The post Digital Transformation in Insurance: From Agile to AI first appeared on AAIS.

Why Insurance Still Relies on Paper and the Challenges It Creates

“I think one of the primary reasons insurance carriers have been so reliant on paper for so long is due to the industry being so deeply rooted in everything from regulatory requirements and compliance to legacy systems,” Eubank explained. Processes like claims handling, underwriting, and policy issuance involve multiple parties, signatures, and compliance checks—many of which have historically required physical documentation for legal or audit purposes.

In addition, customer preferences play a role. “A significant portion of the customer base—especially in commercial and life insurance—is older and still prefers or expects paper-based communication,” Eubank said. But the cost of staying on paper is high. Eubank highlighted several major challenges for carriers:

• Operational inefficiency: Manual processes are slow and prone to error.
• High costs: Storing, mailing, and managing paper adds up quickly.
• Data fragmentation: Paper documents are unstructured and hard to integrate into digital systems.
• Poor customer experience: Clients expect digital-first interactions, and paper often falls short.

Practical Steps Toward Paper-Free Workflows for Insurers

While a full transformation may seem daunting, insurers don’t need to overhaul everything at once. “Start with high-impact areas where paper slows down operations—like claims intake or third-party notifications,” Eubank advised. From there, build momentum by introducing simple digital solutions including:

• Replace paper forms with online applications.
• Adopt secure electronic signature tools like DocuSign.
• Use OCR (optical character recognition) to digitize incoming documents.
• Train staff and customers to support the transition away from paper.

How Carriers Can View Automation as an Ecosystem for Future-Proof Operations

To truly future-proof operations, Eubank encourages insurers to think of automation as a long-term ecosystem—not a one-time project. “Start by promoting cross-functional collaboration—get operations and business leaders working together to prioritize automation that serves shared goals,” he said.

He also recommends a modular approach, where carriers implement flexible, plug-and-play components—like for claims triage or fraud detection—without disrupting their core systems. Artificial intelligence (AI) and machine learning can also help automate decision-making in areas like risk scoring, customer service, and document classification—particularly when integrated into modern systems. “Lastly, it’s about leveraging APIs and web services within a cloud environment,” Eubank said. “That kind of architecture ensures any future tools can integrate easily and support a land-and-expand strategy.”

Visit LenderDock.com to explore how insurers can streamline workflows and reduce paper dependency with digital verification and automation solutions.

The post Modernizing Automation in Insurance Toward a Paper-Free Future first appeared on AAIS.

Practical First Steps for Integrating AI Without Disrupting Operations

“AI is definitely frontier-level stuff that’s changing rapidly, so it’s natural to be cautious about its adoption,” Villa explained. A practical first step is to focus on data hygiene, ensuring that AI has access to accurate and structured data. He recommends insurers take key steps, including:

• Establishing clear data standards for formatting, naming conventions, and storage.
• Enhancing data security and privacy by anonymizing or adapting personal data for AI model training.
• Extracting, integrating, and consolidating data from various systems.

“Having limited data sets that are thoroughly cleaned and vetted will create a strong data foundation and position AI initiatives for success,” Villa added.

Using AI to Enhance Teams, Improve Decision-Making, and Drive Efficiency

Most insurers start their AI journey with chatbots or automated document processing to improve data access and decision-making. AI streamlines manual tasks, such as summarizing home inspection reports, which typically take underwriters about 30 minutes to review. AI can ingest data, redact personally identifiable information (PII), and generate a summary in seconds, making it immediately actionable. “This level of AI precision reduces cycle time, but does not replace the underwriter,” said Villa. “Instead, it’s a collaborative process that combines human expertise with machine learning a ‘human-in-the-loop’ approach.”

Overcoming Key Challenges in the AI Journey to Deliver Measurable Value

“I think the biggest challenge we face is thinking differently about the work we’ve been doing for the past 20 years,” said Villa. “Using ChatGPT to help enhance the quality of and reduce the time it takes to put things in writing or researching topics feels natural. Who wouldn’t want to spend less time writing emails or researching topics?” However, the challenge arises when AI begins to automate tasks professionals feel they have mastered. “What if I’m a senior underwriter and I am an expert at inspection report reviews?” Villa posed. “I may not be as open to using AI, even if it gives me back time in my day. Helping our team understand that AI isn’t going to replace the work we do, but rather augment it, will be key to successful adoption.”

How OneShield Helps AAIS Members Navigate the Evolving AI Landscape

OneShield is at the forefront of AI-driven transformation, offering two modern core systems: OMS and Enterprise. “Both solutions can be delivered as enterprise suites to automate policy, billing, claims, workflow, and reporting, or they can be implemented as a modular solution to address any one particular aspect of the insurance value chain,” Villa explained. For AAIS Members, OneShield’s expertise in AAIS lines of business makes adoption even smoother. “Across our two products, we can support all AAIS lines. We have particularly strong experience with unique AAIS lines such as COP and Artisans,” Villa noted. “Leveraging this experience to deliver pre-built AAIS content within our core solutions can accelerate core transformation projects at a significantly reduced cost to the insurer.”

Learn more at OneShield.com.

To view the full interview with Tony Villa, click on the video above.

The post AI in Insurance: Streamlining Underwriting Without Disruption first appeared on AAIS.

Why AI Is a Hot Topic Across the Insurance Industry
While predictive modeling has long been a part of insurance operations, the rise of advanced AI technologies, including generative models such as GPT, has created new possibilities. Habayeb shared, “Once we got into the world where GPT and generative happen, you now had non-technical people, non-actuaries, and business leaders, saying, ‘I want to build a model to do this thing.'” This democratization of AI technology has sparked growing interest in how AI can solve insurance’s unique challenges, especially in a low-margin, often manual environment. Aufenthie further emphasized AI’s mainstream rise, noting that as AI becomes more accessible, it signals a significant shift in its potential across the industry.

Regulatory Perspective of AI in the Insurance Industry
The growing role of AI in insurance has caught the attention of regulators. This can be proven by the NAIC Innovation Cybersecurity and Technology (H) Committee, which was created to address AI and its potential to transform the industry, Block explained. “Insurance is an industry that is sort of perfect for the use of technology,” she noted. Regulators are focused on ensuring AI is applied within existing frameworks, though the complexity of integrating emerging technologies with traditional regulations remains a key challenge.

Consumer-Facing Applications of AI in the Insurance Industry
Regulators are particularly concerned with AI’s consumer-facing applications, such as in underwriting, fraud detection, and claims processing. Block referenced surveys in the auto insurance sector, highlighting a significant gap between the intention to use AI and its actual implementation. “The numbers went from… 80-90% are thinking about using it… to 20% are actually using it,” she revealed. Despite this, areas like claims, fraud detection, and marketing are seeing more widespread AI adoption.

Biggest Hurdles That Insurers Face in Advancing Their AI Journeys
One of the largest obstacles for insurers, especially smaller carriers, is the reliance on third-party vendors for AI solutions. While large insurers may have the resources to build and tailor their own AI systems, smaller companies often lack the infrastructure to do so. Habayeb advised smaller carriers to manage relationships with external vendors to implement AI solutions effectively.

The AI Bulletin: Its Purpose and How It Hopes to Protect the Consumer
The AI Bulletin, passed about a year ago, serves as a crucial step toward regulating AI in the insurance industry. Block explained that the bulletin is not a statute but provides clarity on regulators’ expectations for AI use within the context of existing laws. “It aims to ensure that AI is used responsibly and transparently, focusing on protecting consumers,” she explained. The bulletin addresses concerns such as AI-driven pricing, ensuring fairness, and avoiding discriminatory practices in line with established regulations. However, Block noted that this is only the beginning. Future legislative efforts may further refine AI governance, particularly around third-party data and models.

Managing State-by-State Differences With AI Compliance
Habayeb explained that navigating AI regulations is complicated by the different approaches taken by individual states. “If a state establishes their AI risk management program in 2025, the degree to which you have robust testing, validation, and continuous monitoring of the high-risk things… might take a little bit more time,” he said. States like New York, Colorado, and California have already implemented their own policies that differ from the AI Bulletin’s guidelines, creating additional challenges for insurers trying to maintain compliance. Habayeb advised insurers to develop a consistent, repeatable structure for managing AI compliance, with a focus on the highest-risk use cases in 2025. “Have some consistent structure for knowing that it’s happening, proving that you evaluated its appropriateness, and that you’re keeping an eye on it,” he said.

NIST: Finding a Framework and Importance of Investing in AI Now for the Future
The NIST AI Risk Management Framework (AI RMF) offers a critical tool for companies seeking to ensure responsible AI use. While Habayeb noted that the framework is still evolving, he praised its structure as a valuable guide. He emphasized that insurance companies should start aligning AI governance with existing industry standards, such as actuarial practices.

Steps for Insurers to Align With the Bulletin’s Goals
To align with the AI Bulletin’s guidelines, Block emphasized that insurers must assemble the right team to build a practical governance structure. “You need all the people in the room to build a practical governance structure so that it makes sense,” she said. After the team is in place, insurers should focus on defining clear internal policies that outline the roles, responsibilities, and risk management strategies related to AI. Habayeb added that insurers should be ready to explain how their AI systems align with corporate policies and regulatory expectations. “You want to see those connected, right? How have you affected that policy?” he asked, reinforcing the need for transparency and clear communication with regulators.

To view the full webinar, click on the video above.

Questions? Please reach out to any of the featured speakers through the contact information below.

Chris Aufenthie
Director of Regulatory Filings, AAIS
chrisa@aaisonline.com

Anthony Habayeb
Co-Founder & CEO, Monitaur
anthony@monitaur.ai

Mary Block
Director of Insurance Regulation, Vermont Department of Financial Regulation
mary.block@vermont.gov

The post Webinar: Advancing AI in Insurance: Navigating Regulatory Trends first appeared on AAIS.

Lisle, IL, January 13, 2025 — The American Association of Insurance Services (AAIS) is excited to welcome Monitaur to the AAIS Partner Program.

“We are thrilled to join the AAIS Partner Program. This collaboration ensures that AAIS and its Members have access to the robust governance solutions they need to comply with insurance regulations while optimizing their AI investments,” said Anthony Habayeb, Chief Executive Officer and Co-Founder of Monitaur. “We’re committed to driving innovation and excellence while helping insurers navigate the complexities of AI risks.”

Since 2019, Monitaur has committed to being an AI Governance partner across the insurance ecosystem. Its solution helps carriers build and scale governance frameworks that improves business outcomes while aligning with key standards and regulations, including NIST, ASOP, and the NAIC AI Bulletin – now adopted in 25 states nationwide.

“We are excited to welcome Monitaur to our AAIS Partner Program, providing our Members with expertise and solutions that deliver responsible and trustworthy AI for the insurance industry,” said Werner Kruck, President and Chief Executive Officer of AAIS. “Through their customers and regulatory interactions, Monitaur has clearly demonstrated their commitment to being the best AI Governance solution for our industry. We look forward to seeing how our Members leverage Monitaur to establish an approach to AI Governance that fuels innovation and achieves regulatory expectations.”

The AAIS Partner Program provides AAIS Members with unique access to quality products and services that help them streamline processes, achieve operational efficiency, and support business growth. To find out how AAIS Partners like Monitaur can help innovate your business, please visit AAISonline.com or contact the AAIS Member Engagement Team at membership@aaisonline.com.

About Monitaur

Monitaur is the premier AI Governance solution for the insurance industry, helping companies use AI that businesses, regulators, and consumers can trust. The company delivers software and expertise to help insurers and their partners define, manage, and automate fundamental best practices throughout the modeling project lifecycle. With Monitaur, companies can accelerate innovation with clarity and confidence, ensuring transparency, performance, fairness, safety, and compliance across AI systems. Find out more at monitaur.ai.

About AAIS
Established in 1936, AAIS serves the property & casualty insurance industry as the only national not-for-profit advisory organization governed by its Member insurance carriers. AAIS delivers high-quality advisory solutions, including best-in-class policy forms, rating guidelines, and data management capabilities for commercial lines, inland marine, farm & agriculture, auto, and personal lines insurers. Their consultative and unbiased approach, unrivaled customer service, and innovative technical capabilities underscore a focused commitment to the success of their Members. Together with Member carriers, insurance regulators, Partners, MGAs, and other key stakeholders, the AAIS Community is working to build a more cost-effective and sustainable industry. For more information about joining the AAIS Community, visit AAISonline.com.

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Media Contacts

Monitaur
Susan Peich 
Head of Marketing
s.peich@monitaur.ai

AAIS
Wen Tilghman
Director, Marketing & Communications
went@aaisonline.com

Source: GlobeNewswire

The post Monitaur Joins AAIS Partner Program, Helping Members Mitigate AI Risk and Remain Compliant with Adaptable Industry Solutions first appeared on AAIS.

How Insurers Can Leverage New, Unconventional Technologies and Insights to Improve Loss Ratio

Ham believes that new behavioral insights offer insurers a critical tool to enhance risk assessment and loss ratios. “Insurers can leverage new and unconventional behavioral insights by performing better, more thorough risk assessment,” he explained. These insights provide an additional layer of understanding that complements traditional factors used in risk evaluation. With the inclusion of behavioral insights, carriers get “a factor that to date they haven’t had access to,” offering a fuller picture of the risk profile. This allows them to make more informed and profitable decisions.

How Carriers Can Integrate Behavioral Intelligence Into Existing Risk Mitigation Strategy

Carriers can integrate behavioral intelligence into their risk mitigation strategies at multiple points in the insurance value chain, according to Ham. By using behavioral insights, they can target individuals whose profiles align with their risk appetite, tailoring risk selection from the outset. “It goes down the insurance value chain, where they can dictate the buying journeys based on these new insights,” Ham explained. Additionally, carriers can use behavioral intelligence to develop renewal strategies, allowing for a more dynamic approach to risk management.

Using Behavioral Insights to Help Carriers Achieve Goals of Equity and Fairness

Behavioral insights can play a pivotal role in helping carriers meet goals of equity and fairness. “By getting that complete picture, we have to recognize the uniqueness of individuals, and behavioral insights are exactly that they’re telling the carrier unique insights about that individual, so they don’t have to bucket them or ban them, ” said Ham. He explained that by understanding individuals on a more personal level, carriers can avoid the unintended exclusion of certain groups, ensuring a more inclusive approach to underwriting and risk management. “It’s not based on banking, so you’re getting insights that are more inclusive of individuals, as opposed to those that may unintentionally exclude some.”

About Pinpoint Predictive, Inc.

Ham described Pinpoint Predictive as “the ultimate risk selection platform.” He elaborated, “Pinpoint Predictive leverages machine learning and these new unconventional behavioral insights to deliver unparalleled precision in underwriting and actuarial decisions. The company’s platform addresses not only profitability for insurers but also improves the overall customer experience and provides agents with better tools to represent carriers effectively. “For me, Pinpoint is that ultimate risk selection platform that allows everybody to win.”

Learn more at pinpoint.ai.

To view the full interview with Scott Ham, click on the video above.

The post Enhancing Risk Mitigation with Behavioral Intelligence first appeared on AAIS.

In 2024, a P&C insurer study conducted by Capgemini suggested that 41% of the underwriters’ time is spent on “administrative and operational activities, constraining their capacity and triggering value chain challenges in pricing and broker/customer experience.”

Improving underwriter efficiency has always been a key driving force behind selecting an insurance platform. However, merely adopting a modern insurance platform is insufficient to address some of the current inefficiencies. To truly enhance underwriting efficiency, insurers now have the opportunity to select an insurance platform with built-in advanced AI-based automation and process optimization solutions. Furthermore, selecting a platform equipped with AI capabilities and partnering with a solution provider that is actively investing in AI technologies will not only meet current underwriting demands but also drive future productivity and innovation requirements.

With built-in AI-driven solutions, insurers can streamline operations, reduce manual workloads, and enhance overall efficiency, positioning themselves for long-term success in a rapidly evolving market. A modern platform working in cohesion with its own AI solution is the only way to achieve maximum efficiency and success.

Key areas where AI can bring substantial benefits include:

• Improving User Experience and Automation: AI-powered platforms can streamline and automate repetitive tasks, such as data entry and analysis, thereby reducing the administrative burden on underwriters. For example, Cogitate’s DigitalEdge platform has UW Assist, powered by CogitateLabs, which includes data ingestion capabilities. The AI reviews the input submission forms, automatically identifies the inputs for the submission through its powerful LLM models, and inserts data automatically into the application. This drastically reduces the manual administrative work for the underwriters and improves their user experience.
• Reducing Premium Leakage and Adverse Selection: AI can play a crucial role in minimizing premium leakage by identifying discrepancies and ensuring that premiums accurately reflect the risk associated with each policy. Moreover, AI-driven analytics can detect patterns indicative of adverse selection, where higher-risk individuals might be disproportionately represented. By addressing these issues, insurers can better align premiums with actual risk profiles and improve the financial stability of their portfolios.
• Prioritizing Work: AI can assist underwriters in prioritizing their workload by analyzing and sorting tasks based on urgency and impact. Intelligent systems can assess cases that require immediate attention and those that can be deferred, optimizing the allocation of resources and improving workflow efficiency. This prioritization ensures that critical tasks are addressed promptly, leading to better risk management and decision-making.
• Identifying Demands: Attorney demand letters are one of the biggest challenges facing the insurance industry. Any bad faith claim can have a significant impact, with settlements running into millions of dollars. Insurance companies have to deploy the manual process of reviewing thousands of documents daily to identify demand letters from attorneys. This is a time-consuming and error-prone process. With solutions like Cogitate’s DemandAssist, an AI/ML-based product, significant operational efficiency with an error-free process can be achieved.

Conclusion

AI-based tools are becoming a part of the work process, and proper adoption is key for an organization’s success and sustainability. To effectively leverage innovative tools, particularly AI-assisted solutions, it is essential to first build trust within your team. This involves gradually introducing these tools to address specific issues, consistently using and testing them, and measuring the improvements they bring. By demonstrating tangible benefits and success, you foster confidence in the technology and cultivate advocates for innovation within your organization.

Equally important is finding the right partner, like Cogitate, to support your transformation journey. Selecting the right solution provider who not only offers advanced tools as part of their insurance platform but also invests in ongoing innovation and support ensures that you have a reliable ally in navigating the complexities of modern insurance technology needs. This partnership is crucial for maximizing the potential of AI solutions and achieving long-term success in underwriting and beyond. Learn more about Cogitate at cogitate.com.

The post AI-Powered Insurance Platforms Boost Underwriting Efficiency first appeared on AAIS.

The Evolving Landscape of Homeowners Insurance

The homeowners insurance market is under intense pressure due to a combination of factors:

• Population Shifts and Real Estate Development: Growing populations and new developments in high-risk regions exacerbate underwriting difficulties.
• Unpredictable Weather: Increased frequency and severity of weather-related events make risk prediction more complex.
• Market Disruptions: Factors like social inflation, macroeconomic pressures, rapid innovation demands, and heightened competition are intensifying the strain on insurers. Litigation management costs surged 19% from 2018 to 2023 for the combined P&C sector, reflecting an approximate $24 billion loss adjustment expense (LAE).

These issues are compounded by a surge in consumer insurance shopping, a rise in higher-risk policies, and an increase in long-time policyholders switching carriers. Insurers are forced to make tough choices, such as raising premiums, exiting markets, or discontinuing certain coverage lines. These pressures are preventing the industry from achieving necessary positive outcomes critical for future profitability.

The Burden on Underwriters

Amid the ongoing market uncertainty, underwriters particularly are facing significant challenges:

• Overwhelming Submission Volume: An influx of submissions strains underwriting resources.
• Inaccurate Risk Prediction: Traditional methods based on demographic data and zip codes are proving to be inadequate, necessitating more precise risk assessment tools.
• Data Quality Issues: Poor-quality or unstructured data and manual processes further complicate risk assessment.

Underwriters are questioning why the process is so burdensome and how it can be alleviated. The crux of the issue is underwriting profitability, crucial for maintaining healthy bottom-line results. Fortunately, there are modern solutions to address these goals.

Modernize Risk Assessments with Behavioral Predictions

Traditional underwriting relies heavily on demographic data and location. Enhanced risk assessment goes beyond traditional methods such as ZIP Codes and credit scores by incorporating individual behavior and decision-making patterns.

Underwriters today can access a wealth of data outside traditional risk variables to deepen the understanding of their policyholder’s risk profile. By utilizing AI-powered behavioral predictions, which incorporate information about consumer activity, interests, buying choices, etc., underwriters can more accurately predict outcomes relevant to insurance underwriting performance.

To remain competitive, insurers must invest in this digital transformation and reduce reliance on complex, manual processes. In fact, a McKinsey analysis found that the most successful carriers are those leveraging the latest technologies to optimize underwriting capabilities. Enhanced approaches for success involve adding:

• Comprehensive Risk Profiles: A detailed view of prospective and existing policyholders to start transforming underwriting workflow.
• AI and Person-Level Insights: Using AI to access powerful person-level insights about customers and their individual risk propensities, which directly impact underwriting profitability.

Leveraging Behavioral Predictions Across the Insurance Value Chain

Using behavioral intelligence represents a transformative shift in insurance underwriting. By incorporating policyholder behaviors into risk evaluation, insurers gain a deeper understanding of risk profiles and individual customer nuances, leading to a more customer-centric approach to coverage. This intelligence offers specific predictions that enhance risk assessment:

• Identifying policyholders with a high propensity to seek an attorney at first notice of loss (FNOL) or a likelihood to litigate.

• Predicting claims frequency and severity for current policyholders and prospective customers.

• Assessing the likelihood of non-payment or early cancellation.
• Determining which prospects are most likely to convert to new customers and predicting their lifetime value.

When insurers identify policyholders with a higher propensity for risk, they can proactively manage these policies more precisely using unique identifiers. Meanwhile, they can handle other policies based on different qualifiers that indicate varying levels of risk. This becomes a game-changer for insurers’ ability to predict and review for underwriting.

Empowering Underwriters

Underwriters are tasked with building profitable books with targeted risk profiles. To be successful, they need to make quick, effective, and accurate assessments of the profitability of each policyholder. However, they are often working with limited or convoluted information and are under considerable time constraints.

Utilizing person-level intelligence in underwriting allows underwriters to focus their craft and expertise on the most complex risks. By integrating person-level intelligence, insurers can:

• Identify High-Risk Insureds Early: Early identification of high-risk individuals allows underwriters to focus on the most complex cases, improving resource allocation.
• Improve Efficiency: With simply using a name and address, significant risk insights can be obtained in seconds.
• Enhance Risk Handling: Focus on complex cases while automating the handling of low-risk applications, improving overall workflow efficiency.
• Provide Personalized Service: Offer coverage tailored to individual risk profiles, moving beyond traditional factors like location and credit scores.

Future-Proofing Insurance Underwriting

For P&C insurers, integrating person-level intelligence into underwriting processes offers a more precise and complete view of the policyholder risk profile. This approach helps insurers better prepare for uncertainty, respond to market volatility, avoid adverse selection, and achieve profitable, sustainable growth. These AI-powered behavioral predictions empower insurers to:

• Predict and Manage Risks More Accurately: Identify high-risk individuals earlier and adjust policies accordingly.
• Enhance Customer Understanding: Gain insights into customer behavior, such as propensity to litigate or likelihood of early cancellation, improving risk management strategies.
• Improve Underwriting Profitability: Achieve more accurate risk assessment and better manage underwriting resources, contributing to healthier bottom-line profitability and sustainable growth.

Using Advanced AI Risk Assessment with Pinpoint Predictive

A more comprehensive and inclusive risk assessment requires a deep understanding of the individual behind the policy, as well as incorporating insights into an insurer’s decision-making processes as part of risk analysis.

Pinpoint Predictive empowers underwriters by enabling them to make smarter, more equitable assessments of risk, accurately identifying high-risk and low-risk individuals. This enhanced accuracy in underwriting workflows helps insurers better serve their customers by identifying and quantifying individual risk earlier and more accurately.

By bridging the gap between the most powerful behavioral predictions made by the world’s leading tech companies and the specialized requirements of the insurance industry, Pinpoint is delivering unmatched risk-selection capabilities at various points along the insurance value chain.

Conclusion

The homeowners insurance sector faces unprecedented challenges. Behavioral intelligence, centered on individuals, represents the next generation of technology, transforming policyholder risk assessments and offering insights into future customer risks. As the industry adapts to these new technologies, the focus will shift toward more informed, efficient, and customer-centric underwriting practices, paving the way for a more resilient and profitable insurance market. Insurers that integrate these advanced risk assessment tools and insights will ultimately be the most successful in enhancing their underwriting processes, addressing the evolving risks associated with new developments and weather events, and ultimately improving financial outcomes.

Improve your Underwriting Outcomes with Pinpoint

With predictions available earlier and more accurately than any other risk solution on the market, Pinpoint is transforming the P&C insurance industry and helping underwriters drive better outcomes with an AI-powered, real-time solution for precise risk selection. For more information about how Pinpoint can help you, visit www.pinpoint.ai or contact info@pinpoint.ai.

The post Addressing Homeowners Underwriting with Behavioral Risk Predictions first appeared on AAIS.

LISLE, IL, July 29, 2024 — The American Association of Insurance Services (AAIS) is excited to welcome Pinpoint Predictive, Inc. to the AAIS Partner Program.

“We are proud to join the AAIS Partner Program and are thrilled to align with such a reputable organization that is providing the value and support it does for the insurance sector,” said Scott Ham, Chief Executive Officer of Pinpoint Predictive. “Working with AAIS to support U.S. insurance carriers offers Pinpoint a great opportunity to further our mission of promoting sustainable, profitable growth and fairness for insurers.”

Pinpoint Predictive’s innovative risk selection platform utilizes deep learning and individual-level behavioral intelligence to provide P&C insurers the ability to augment how they can assess and predict risk. Pinpoint’s predictions help insurers make informed risk decisions, improving loss ratios and accelerating profitability.

“We are excited to welcome Pinpoint Predictive to our AAIS Partner Program, providing our Members the opportunity to leverage their platform to improve loss ratios and accelerate their business,” said Werner Kruck, President and Chief Executive Officer of AAIS. “Pinpoint offers innovative technologies, like individual behavioral predictors and advanced AI, which is becoming crucial now more than ever in this ever-changing insurance marketplace.”

The AAIS Partner Program provides AAIS Members with unique access to quality products and services that help them streamline processes, achieve operational efficiency, and grow their business. To find out how AAIS Partners like Pinpoint Predictive can help create better customer experiences and increase speed to market, please visit AAISonline.com or contact the AAIS Member Engagement Team at membership@aaisonline.com.

About Pinpoint Predictive, Inc.

Pinpoint Predictive provides property & casualty insurers with the earliest and most accurate loss predictions and risk scores to fast-track profitable growth and improve loss ratios. Unlike traditional methods, Pinpoint’s platform leverages deep learning, proprietary behavioral economics data, and trillions of individual behavioral predictors to help insurers identify the risk costs associated with customers and prospects. Pinpoint Predictive has been recognized by several notable organizations including the 2022 Insurtech 100 Award, Insurtech Vanguard, AI Breakthrough Awards 2023, Global Tech Awards 2023 (Category winner for AI), AnalyticsTech and Insurtech, and the Insurance Awards 2023 (Category winner for Insurtech in World Finance Magazine). Find out more at pinpoint.ai.

About AAIS

Established in 1936, AAIS serves the property & casualty insurance industry as the only national not-for-profit advisory organization governed by its Member insurance carriers. AAIS delivers high-quality advisory solutions, including best-in-class policy forms, rating guidelines, and data management capabilities for commercial lines, inland marine, farm & agriculture, auto, and personal lines insurers. Their consultative and unbiased approach, unrivaled customer service, and innovative technical capabilities underscore a focused commitment to the success of their Members. Together with Member carriers, insurance regulators, Partners, MGAs, and other key stakeholders, the AAIS Community is working to build a more cost-effective and sustainable industry. For more information about joining the AAIS Community, visit AAISonline.com.

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Media Contacts

Pinpoint Predictive, Inc.
Shannon Minger
Product Marketing Manager/Media Relations
shannon.minger@pinpoint.ai

AAIS
Wen Tilghman
Director, Marketing & Communications
went@aaisonline.com

Source: Globe Newswire

The post Pinpoint Predictive, Inc. Joins AAIS Partner Program, Empowering AAIS Members with Strategic Risk Selection for Enhanced Profitability first appeared on AAIS.