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Digital EditionRethinking Claims Intelligence with Early Intervention Tools
The A.I. conversation has matured. As anticipated, many sessions, demos, and discussions at the recent ITC Vegas conference focused on A.I.
But instead of simply calling out the use of A.I. tools, conversations shifted to use cases, deployments, and outcomes. The industry has invested in the use of various insurtech solutions, many of which now rely on A.I. in different ways, and this investment has led to measurable outcomes across the industry.
A session at ITC Vegas explored how carriers can connect both structured and unstructured data to reduce claims costs by identifying and managing emerging litigation exposure, growing severity, and medical complexity. Claims departments have always had access to vast amounts of information but have traditionally been limited by their ability to analyze and act on insights gleaned from the content.
Adjusters know there are early indicators of claims that may turn into large losses with litigation exposure or medical complexity, but often these flags are buried within medical records, legal packages, adjuster notes, evaluations, and expert reports. The historical challenge has been sorting through enormous amounts of information to find the right pieces of data early enough in the process to both meet compliance requirements and influence the claim outcome.
The case study examined in the session “Stop Leaving Claims Risk on the Table,” focused on a multiyear implementation within Nationwide’s claims department. The session was moderated by Heather Wilson, CEO of CLARA Analytics, and featured Maria Wood, senior consultant in business program management at Nationwide, and Mubbin Rabbani, chief product officer at CLARA Analytics. The speakers explored how carriers can use A.I. tools, including predictive analytics and document intelligence abilities, to give adjusters early insight into emerging risks and provided examples of how to make claims analytics actionable.
A.I.-Enabled Tools Identify Litigation and Severity Risks Earlier
The speakers discussed two specific tools that Nationwide has implemented. Litigation propensity alerts help identify claims that may need closer review before litigation develops. Adjusters who receive an alert can review the claim, assess emerging complexities, and seek guidance from their supervisor. There continues to be a distinction between identifying risk and making decisions, however, as the adjuster remains the decisionmaker on the claim. A litigation alert does not mean that litigation is inevitable, and it does not force any particular outcome or plan of action. Alerts are a way to channel an adjuster’s focus to the claims that may need more attention.
Severity analytics are the second tool the speakers discussed. Severity alerts help adjusters assess complexity and evaluate reserve adequacy. They can be used at the claim level and department level. Having early insight into severity issues can help carriers manage reserve deficiencies, prioritize workloads, and avoid under-reserving or making late-stage large reserve increases. This visibility allows leaders to shift claims management from reacting to adverse developments after they occur to predicting conditions that may require earlier intervention.
Conversational Claims Intelligence is the Next Evolution
The burgeoning role of agentic A.I. in claims management was another topic discussed during the session. While traditional predictive analytics were based on static, predefined models, newer approaches are more interactive, allowing adjusters to explore supporting details, ask questions about why a risk was highlighted, or look for alternative solutions. A.I. agents using multiple sources of information and tools can evaluate dynamic claims circumstances and help adjusters understand possible ways to respond and potential outcomes.
The speakers raised important transparency and governance issues. Adjusters who receive a severity alert or litigation propensity alert should be able to see what triggered the alert and which details contributed to the assessment. Supervisors and evaluators need visibility into the reasoning behind A.I.-generated insights and recommendations. The human-in-the-loop model remains critical throughout the insurance lifecycle. Increasing automation does not decrease accountability for claims decisions.
To measure success, the panel discussed tracking various operational and financial outcomes over time, like reserve adequacy, incurred losses, severity, and the progression of claims following early interventions. The takeaway is that financial outcomes and technology innovations must be considered together. It is not enough to simply count alerts or early interventions; those numbers must support better decisions and outcomes to show the program is successful.
With continued advances in claims analytics and technology, carriers will be better positioned to recognize developing risks. This opportunity for early intervention and more context for adjuster decisions requires carriers to have quality data, measurable outcomes, and human oversight. It is about connecting data, professional judgment, experience, and timely action. The goal is not simply to reduce cycle time or make claims handling faster. Rather, it is to ensure claims adjusters have access to insights that will help them make decisions while there is still an opportunity to influence outcomes.
With the right tools, the panelists showed how early intervention can result in better claims outcomes. &
