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AI holds promise for innovating the claims experience

By Sam Krishnamurthy | Chief Technology Officer, Turvi

Artificial intelligence has numerous applications for the insurance industry, and one area where AI is already showing promise for innovation is claims. The claims process is the moment of truth for policyholders, when they expect their insurer to fulfill the promise of paying for a covered loss. AI is being deployed in several ways that enhance the claims experience.

With the advent of GenAI, advanced AI capabilities have been democratized, enabling use cases like data analysis, generating content based on prompts, summarizing complex documents, and optimizing workflows. In insurance claims management, GenAI can transform processes by streamlining operations, providing actionable insights, and enhancing customer experiences. For example, GenAI can summarize lengthy claim-related documents or generate tailored responses to claimant queries, significantly boosting productivity and reducing response times.

Contrary to fears that AI might displace humans, in claims, this is not the case now or likely ever. AI serves as a productivity toolkit, complementing the expertise of claims professionals rather than replacing it. The nature of claims demands a human in the loop to provide the empathy and expert knowledge necessary to resolve claimant issues effectively.

However, implementing GenAI requires a cautious approach, prioritizing data privacy, security, and robust data governance practices. Ensuring the quality and diversity of training datasets is critical to minimizing bias and improving model reliability. Combined with observability metrics such as accuracy, bias detection, and explainability, these measures drive trustworthy and actionable insights. While GenAI can analyze claims data and cite trusted sources, human validation helps to achieve outputs that are reliable, ethical, and aligned with business goals. Taking this "trust but verify" approach helps to ensure that GenAI can serve as a powerful tool to empower claims professionals, maintain trust, and drive responsible innovation.

Forward-thinking claims organizations see AI’s potential in a number of elements that drive and deliver better outcomes for customers and policyholders.

Roles for AI

Over the last two decades, predictive models in claims management have evolved to anticipate trends and risks, improving decision-making and operational efficiency. Now, GenAI is driving a transformative shift, with AI embedded within claims management products to automate routine tasks, augment adjuster expertise, and personalize claimant experiences. By streamlining workflows and delivering innovative solutions, GenAI redefines how insurers create value and transform the claims process across the property and casualty sector.

Examples of AI that are already in use include:

• Triage claims to reduce cycle time and loss adjusting expense. Desk adjusters overseeing AI-directed claim triage and channel segmentations.

• Image recognition and classification of photographs.  AI helps detect inconsistencies in photos, uncovering fabricated claim evidence by bad actors. This empowers claims professionals with accurate insights to efficiently identify fraud and focus on legitimate claims.

• Ensuring the right resource is assigned faster. Simple claims generally do not require specialized adjusting expertise, unlike complex claims. AI assists in allocating adjusting resources where they are most effective.

• Claims coverage reviews. Understanding the language in a policy is critical in determining whether a claim is covered. AI simplifies and speeds up this process by analyzing large context of unstructured policy and claims data.

• Transform call centers for claims. Conversational AI revolutionizes call centers by enabling straight-through processing, where AI agents can efficiently handle up to 60% of calls, streamlining routine inquiries and resolutions. For complex cases, human agents are empowered with AI copilots and real-time language translation capabilities, to give personalized, empathetic support. This seamless integration transforms interactions, driving faster resolutions, personalized support, and improved satisfaction for both customers and agents.

Advantages of AI in claims

AI offers several key advantages in the claims experience. These include AI’s ability to:

• Reduce human errors. Minor mistakes, like clerical errors or misapplying data, can lead to rework, delays, and errors in claim reserving. GenAI minimizes these risks by automating data handling, improving accuracy in estimates, and flagging inconsistencies, to ensure more efficient workflows and reliable outcomes.

• Significantly shorten cycle time. By streamlining claims workflows, AI can reduce cycle time for adjusters. For example, using AI can reduce the claim-related coverage review process from one hour to 15 minutes. For an adjuster handling 80 to 100 claims, that adds up to substantial time savings that translates into better service across the adjuster’s caseload.  

• Enhancing customer experience:  Conversational AI reduces call abandonment, improves first-call resolution, lowers average handling time, and boosts NPS. By delivering an omnichannel experience, it drives faster, personalized, and seamless support across voice, chat, and digital platforms, enhancing customer satisfaction.

• Flatten the learning curve for junior adjusters. Experienced claims professionals possess a great deal of expertise, but the learning curve for inexperienced adjusters is steep. AI can assist junior adjusters in increasing their knowledge faster.

With any AI application, constant research and development is mission critical. Insurers and brokers have varying needs in claims operations, and solving industry challenges requires differentiating the extent to which AI technology can be leveraged to address complex problems through product innovation while keeping human expertise integral to the process. This approach not only maintains empathy and expertise as a central part of claims handling but also drives efficiencies, reducing loss adjustment expenses (LAE) and delivering better outcomes for customers.

Sam Krishnamurthy is the Chief Technology Officer of Turvi, a newly launched insurance technology company funded by Crawford & Company. Sam has more than 22 years of experience as an information technology professional, including 15 years at Crawford & Company. At Turvi, Sam is helping to transform the insurance ecosystem by developing innovative SaaS solutions that reduce LAE, enhance CX, and improve accuracy. By combining advanced technology with human expertise, Turvi empowers claims professionals and elevates the claims experience.

For more information on Turvi, please visit www.turvi.io.