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.

The answer lies not in the existence of digital tools, but in how intelligently and efficiently they’re being used. Today, the conversation is no longer about simply digitizing manual processes—it’s about empowering insurers to innovate faster, smarter, and more affordably. This is where low-code/no-code (LCNC) platforms and artificial intelligence (AI) are becoming the real game changers.

Rethinking Digital Transformation: Beyond Just “Going Digital”

Digital transformation has often been loosely defined—ranging from replacing paper processes with software to overhauling core legacy systems. At its heart, it has always been about operational efficiency—streamlining workflows, cutting costs, and keeping pace with a rapidly evolving market.

However, many so-called “transformative” efforts have been largely incremental. Migrating from spreadsheets to web-based forms or deploying an off-the-shelf policy admin system isn’t transformation—it’s digitization.

What’s missing from many of these initiatives is agility—the ability to quickly roll out new products, adapt to regulatory changes, or respond to evolving customer behavior. That’s where LCNC platforms enter the picture.

Digital Evolution with Low-Code/No-Code

Low-code and no-code technologies mark the industry’s shift from digital transformation to digital evolution—where speed, flexibility, and configurability take center stage.

Unlike traditional software development, LCNC platforms enable business users, product teams, and IT to rapidly design, deploy, and modify applications with minimal coding effort. This evolution has redefined how insurers bring products to the market in many ways:

• New insurance products configured in weeks, not months
• Product launches driven by business teams instead of IT avoiding resource conflicts and backlogs
• Workflow automation and rule changes without full-scale deployments

In recent years, insurers have adopted LCNC platforms to build reinsurance admin systems, launch supplemental health plans, and even create agent compliance modules—all with a fraction of the time and cost of traditional development.

It’s no longer about replacing old systems; it’s about evolving them intelligently with scalable, modular components built for continuous innovation.

The Rise of AI: From Digital Evolution to Digital Intelligence

As insurers evolve their infrastructure with LCNC tools, the next logical leap is toward digital intelligence—powered by AI and real-time data.

AI is no longer just about chatbots or predictive models. It’s about creating systems that adapt, learn, and evolve on their own. In the insurance context, this means:

• Self-adjusting rating models based on real-time behavioral data
• Dynamic underwriting that adapts with every new data point
• Claims triage and fraud detection fueled by machine learning (ML)

While usage-based insurance (UBI) scratched the surface of this concept, it failed to make systems truly intelligent. The models were still static. True digital intelligence requires constant data loops, where AI doesn’t just observe behavior but learns from it and adjusts system logic in real time.

Imagine a platform that automatically recalibrates premiums, deductibles, or policy terms based on live behavioral insights—without human intervention. That’s the future AI enables.

The Fusion of LCNC and AI: A New Operating Model for Insurance

The real innovation happens when LCNC and AI converge. Together, they form a powerful combination:

• Low-code platforms offer speed, modularity, and democratization of development
• AI algorithms bring automation, personalization, and real-time decision-making

This fusion allows insurers to:

• Build AI-powered rating engines without writing complex code
• Train and deploy ML models inside workflow apps configured by business users
• Continuously optimize customer journeys, pricing, and claims processes—without costly development cycles

This isn’t theoretical. Leading insurers today are already deploying AI-infused, LCNC-driven systems to streamline product launches, manage agent compliance, and deliver personalized policyholder experiences on a scale.

Conclusion: Stop Talking About Transformation—Start Driving Intelligence

The term digital transformation has served its purpose. But it’s time to shift focus. Insurers must now embrace a new blueprint—one that starts with LCNC evolution and matures into digital intelligence through AI.

While the transformation journey may have begun years ago, its real momentum is just beginning. With LCNC and AI, the insurance industry is finally equipped to move beyond catch-up mode and into a future of continuous innovation, real-time agility, and intelligent automation.

The finish line isn’t just digitization. It’s self-optimizing, intelligent systems that learn, adapt, and grow with your business.

To learn more about InsurIQ’s transformative technology solutions specializing in policy administration, agent compliance management, and digital insurance sales and enrollment, visit insuriq.com.

The post How Low-Code/No-Code and AI Are Digitally Transforming Insurance first appeared on AAIS.

Today, change in insurance is not only necessary but inevitable. As customer expectations grow and technology advances, insurers must rethink how they handle policy verification, lienholder updates, and compliance notification processes. Automating policy information in real time can reduce administrative burdens and enhance efficiency across the industry.

The Industry Challenge — Inefficiencies in Lienholder Communications

The Burden on Insurers

For decades, insurance carriers have been overwhelmed with thousands of daily policy verification requests. Banks, credit unions, and mortgage lenders continuously seek confirmation of policy details, creating a relentless administrative burden in the form of unnecessary phone calls, emails, faxes, and postal mail. Without automation, insurers must rely on human capital to manually handle these inquiries, leading to wasted time, excessive costs, and the potential for compliance risks. Conservative estimates claim that the insurance industry handles over 500 million phone calls annually. The sheer volume of requests diverts attention from more critical business functions, making it difficult for insurers to focus on their primary objective—providing high-quality service to policyholders.

The Cost of Existing Solutions

Many traditional industry solutions, such as Interactive Voice Response (IVR) systems, outsourced call centers, and Electronic Data Interchange (EDI) data sharing, require significant resources to maintain. Despite their widespread use, these approaches still contribute to operational inefficiencies. One of the largest burdens that both the insurance and banking communities face is managing millions of daily tasks, processes, and deliverables via paper documents and spreadsheets. The costs associated with printing, postage, and processing physical paper disrupt the ability to adopt more cost-effective, agile, and scalable digital solutions. Insurers relying on legacy systems often find them inflexible, unable to support real-time updates, and ineffective at addressing the growing demand for seamless communication between financial institutions and insurance providers. Without an efficient digital solution, insurers remain stuck in a cycle of administrative burden, missed opportunities for growth, and declining customer satisfaction.

The Roadblocks to Digital Transformation

Breaking into a modernized approach to lienholder communications comes with challenges. The sector operates on deeply entrenched legacy systems, and insurers have historically been hesitant to deviate from familiar technologies. Concerns about workflow disruptions, outdated IT infrastructures, and the complexity of integrating new solutions have made digital transformation a slow and cautious process. Additionally, regulatory and compliance considerations add another layer of complexity, making insurers wary of adopting new technologies without proven security and efficiency measures. But, these challenges, while significant, should not deter insurers from embracing automation – especially when the right solutions can seamlessly integrate with existing workflows.

A Digital Solution for Lienholder Process Automation

As the demand for efficiency and automation increases, insurers must rethink how they handle policy verification, lienholder updates, and compliance notifications. Implementing a fully digital, real-time system can significantly reduce administrative burdens, improve response times, and enhance operational efficiency across the industry.

LenderDock addresses this issue by providing a SaaS platform that automates lienholder communication and the exchange of policy data. By eliminating manual processes, LenderDock streamlines policy verification and ensures real-time updates for financial institutions. Their key features include:

• VERiFi™ – Allows banks, lenders, and financial third parties to self-serve online policy verification requests in real-time, eliminating the need for phone calls, emails, and faxes.
• LIENSure™ – Provides digital updates and correction requests for mortgagee clauses and loss-payee information, ensuring process efficiency and data integrity.
• LENDERDocs™ – Enables mortgagees and lenders to access policy documentation instantly, including proof of insurance and paid receipts, fast-tracking information sharing.

The shift toward automated lienholder communications isn’t just an operational upgrade—it’s a strategic necessity. By reducing administrative overhead, insurers can lower costs, ensure compliance, and reallocate valuable resources to higher-value initiatives that drive growth and innovation.

As technology continues to advance, solutions like LenderDock will play a critical role in shaping the future of insurance operations. The industry is at a turning point—those who embrace digital transformation will lead the way, while those who resist may struggle to keep up.

Learn more at LenderDock.com.

The post Automating Lienholder Communications to Boost Efficiency 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.

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.

Defining Speed to Market

White defined “speed to market” as an insurer’s ability to introduce new products or services or make updates to products that already exist as quickly and efficiently as possible. Speed to market covers the entire product development lifecycle, beginning with product ideation, regulatory approvals, marketing and distribution, and finally, the ever-important need to deliver on customer engagement. “GhostDraft finds it critical for our customers and carriers to be first to market with product innovation by making sure that those products address emerging customer needs, especially when you look at the overriding context of being in a fast-paced environment and the need to have a significant competitive advantage,” White shared. “So, we work with insurers so that they can quickly adapt to those changing demands, but also position themselves to retain existing [customers] and attract new customers.” He clarified that speed to market is a continuous journey. “We like to work with our customers to ensure that they’re fostering an innovative culture, making sure that they can easily collaborate around their organizations, and continuously improving, adapting, and evolving so that they can stay ahead of the competition,” he said.

Speed to Market Challenges

One challenge White has noticed with carriers achieving speed to market is the use of legacy systems and legacy processes. “The ability to be adaptive and to try and integrate new and responsive technologies within those legacy environments is pretty important,” said White. “But it can be very complex and time-consuming.”

There are also challenges with streamlining the different processes that relate to collaboration within the product and product development environment. “There are lots of stakeholders involved when you think about how an insurance product is created and moved through its lifecycle,” White stated. “The ability to accurately and effectively collaborate and communicate amongst all of the different departments within a carrier organization is a really critical part of the process.”

In addition, White has seen a lot of organizations struggling to remain compliant with regulators. “We have so many new requirements that are being established within the customer base and the policyholder base, which makes things more complicated and makes remaining compliant a little tougher,” White explained. He touched upon competitive pressures being a challenge to carriers as well. “Once you realize that somebody else has put something into market and you decide it’s a business that you want to be in, you’ve got to compete both with those traditional competitors and the big increase in insurtech startups that we’re seeing in the marketplace today,” he said.

Balancing Speed and Compliance in Product Development

White acknowledged that speed is essential, but compliance is equally, if not more, critical. “There is no sense implementing the fastest technology if you can’t ensure that you can remain compliant,” he advised. “That means reviewing and updating processes that exist to ensure that you’re aligning the processes with new and emerging regulations that are coming from the industry.” To be able to quickly adapt and make changes rapidly, White suggested standardizing. “If you are standardizing, for example, with an AAIS product group, then that means you can take some of those decision points out of your processes,” he explained. “If you leverage something that’s already compliant, then all you’ve got to do after that is ensure that you’re staying on top of it and continuing to meet all of the different obligations you have from a compliance and a regulatory perspective.”

How GhostDraft Helps Drive Speed to Market

GhostDraft offers a few unique ways to drive speed to market. One way is what White refers to as “unburdening.” “We’re taking the burden away by making all of the changes that are required to remain compliant and remain consistent and remain competitive,” he shared. “I had a customer who, essentially, after implementing our solution, was able to move from the design phase to the development phase and through to the production process in just a couple of days, which would historically have taken them about three months to do.”

GhostDraft also utilizes migration to address speed to market. “We certainly see the inclusion of AI when it comes to being able to migrate a large body of content from one environment to another body of content,” White began. “At GhostDraft, we call it our document domain model. All of the data reference points and all of the business logic that is required to produce this form live in one area within the platform that’s managed and owned by businesspeople.”

A significant amount of data mapping needs to happen with a library of documents, according to White, and GhostDraft can help with managing that. GhostDraft allows a carrier to develop those documents only once while having the ability to move the entire domain to a new administrative system without changing any of the business rules or logic that is employed to generate that form.

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.

Laurence White

Executive Vice President of Sales – GhostDraft

laurence.white@ghostdraft.com

The post Webinar: From Concept to Customer: The Need for Speed to Market in Insurance first appeared on AAIS.

Overview of Orion180 & Chrp Technologies

Orion180 is a technology-based insurance company that utilizes cutting-edge technology paired with outstanding customer service to simplify the insurance experience and enhance the customer experience. They are primarily HO3 in six southeast states but are beginning to roll out other products in more states. Chrp Technologies helps home insurance companies build great relationships with their insureds through proprietary AI products that deliver loss prevention and an enhanced customer experience. Chrp has seen tremendous success with clients like Orion180.

Finding Solutions by Utilizing AI Tools

Orion180 as a company focuses on three areas: efficiency, accuracy, and customer experience. “Our challenge was timely identification of risk and issues,” Wyrick shared. “Specifically, having inspections completed, allowing us time to review them, and giving the insured time to repair anything that we found had adverse conditions. So, we really needed to streamline that process to make it more efficient.” Accuracy is also extremely important to Orion180 because they base their outcome on the data that’s provided back to them from inspections. And, overall, the inspection process is a customer experience. What attracted Orion180 to Chrp Technologies was the ease of use and that it hit all three of the company’s focal points. “From an efficiency standpoint, it’s an automatic process,” said Wyrick. “You don’t have to manually order inspections, follow up, track, and keep all that data together. [The] AI built into the platform is accurate. We’ve gone from months of training time down to weeks. And if we have an issue, I know Chin and his team will be there on the customer experience side.”

Impact on Retention Rate & Policy Holder Engagement

Since partnering with Chrp, Orion180 has been able to retain its policies. “When we launched Chrp, our average date of a completed inspection returned was around 16 days,” Wyrick reported. “With all of the updates, we went from 16 days to now nine days completed and it’s still dropping. We’ve got drastically increased policy retention because we’re able to review those risks and provide those solutions and keep that policy.” Wyrick believes this process with Chrp has made policyholders more aware of their risk and its impact on insurance.

Overcoming Challenges

Being a company born out of Florida, Ma admits one of the biggest challenges for Chrp is that a lot of its customers are of an older demographic and do not feel they are tech-savvy enough to use the service. “So, one thing that we’ve put into place right away is a seven-day-a-week, 365 customer service model,” said Ma. “In our company, you go through a rite of passage called the legendary conversation.” This is essentially walking a customer through the inspection process and guiding them through the app. These conversations with customers influence the way that Chrp designed its application. “Those are the types of conversations and experiences that give us the opportunity to make improvements.”

Insight on How Chrp Works

Chrp complies with two mission statements: Eliminate Non-Cat Claims and Help People Have Healthy Homes. “Conducting inspections is [not] a new thing for the insurance industry,” Ma confessed. “But doing so the right way is incredibly important. Right now, the ‘right way’ also necessitates an economic model that works with an underwriting.” Being able to leverage self-inspections in concert with physical inspections, in a cost-effective way, is a huge plus in driving volume, according to Ma. Then, the correct symptoms that lead to claims need to be analyzed. “If you get those two things right, you should see a high inspection conversion, roughly between 75% to 85%, on the self-inspection side. Blended cost-wise, that can actually reduce your overall inspection cost,” he stated. Chrp delivers highly accurate AI to streamline what symptoms require underwriting action and also offer a solution to customers so they can prioritize their time. This leads to the end result, which is how to eliminate non-cat claims to ultimately improve profitability.

When the inspection report comes through to the customer, any adverse conditions that the AI has found are listed first. “We’re looking at those first before we even get through the rest of the inspection,” Wyrick shared. “That’s the efficiency aspect of [Chrp]; we can see right off the bat what’s wrong. If it’s bad enough, we’ll already know how this risk is going to end up.” But the best function of the Chrp platform in Wyrick’s opinion is the ability to escalate inspections. “If we have a reviewer that’s kind of guessing at something or if they have a question, they can escalate that inspection to a new cue, and myself or another senior member can go in to look and write our notes. Then it goes right back to that inspector.”

To view the webinar in its entirety, click on the video above.

Questions? Please don’t hesitate to reach out to any of the featured speakers through the contact information below.

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

Chin Ma
President – Chrp Technologies
cma@chrptech.com

Brandi Wyrick
AVP of Experience – Orion180

bwyrick@orion180.com

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