AI is strengthening (not replacing) claims expertise. Claims has historically been slow to digitise. But it’s now an area where AI can drive real gains in efficiency and customer satisfaction.
Claims management is one of the costliest parts of the insurance lifecycle. It carries high administrative overheads, claims inflation, inefficient manual processes, and high levels of fraud.
Claims is also where customer satisfaction matters most. Customers expect their insurer to handle claims quickly, efficiently, and empathetically. If that doesn’t happen, trust and loyalty disappear fast.
MGAs and insurers also need to remember that many customers are still wary of AI and automation. Research by KPMG found that 90% of insurance customers say human interaction matters in claims handling. Two-thirds (64%) believe claims should primarily be handled by humans.
AI can speed up decision-making, improve fraud detection, and streamline admin. But insurers must balance this against the need to keep the personal touch. The key is giving claims handlers the right tools to do what they do best, not replacing them.
Balancing AI and a human-in-the-loop throughout the claims journey
FNOL (First Notification of Loss)
FNOL can drain claims handlers’ time if they don’t manage it effectively. Customers now expect to log claims however suits them, whether that’s a self-service portal, a phone call, or an email. Claims handlers often lose valuable time populating claims systems and prioritising claims as a result. AI tools can now handle most of this work. Insly’s Nora, for example, automatically extracts data from claims forms and documents, identifies and requests missing information, and triages claims. This frees claims handlers to focus on decision-making, customer queries, and complex cases.
Document review and policy interpretation
Sifting through dense insurance documents is another area ripe for AI automation. Natural language processing (NLP) and large language models (LLMs) are well suited to this kind of work. These tools save claims handlers time. They locate relevant policy wording, summarise coverage, and identify exclusions. They also compare documents against reported losses and surface similar past claims. Claims handlers can then spend more time assessing evidence and less time drowning in documentation.
Decision support
Claims vary enormously in complexity, so it makes sense for claims handlers to focus on the hardest cases. Insurers can now fully automate the most straightforward claims using rules-based automation. For more complex cases, AI helps by providing recommendations.
Insly’s Nora does this by drawing on policy wording, historical claims, similar outcomes, internal guidelines, and regulatory requirements. Claims handlers can accept, reject, or modify those recommendations based on their own analysis. The final decision stays theirs, but AI handles much of the legwork.
Fraud detection
Insurance claims fraud remains a major issue. Insurers uncovered over 98,400 fraud-related claims in 2024. That’s a 12% rise on the previous year, according to the Association of British Insurers. AI helps combat this by spotting unusual patterns that humans might miss, including inconsistent information, duplicate claims, suspicious behaviour, network relationships, and other anomalies. Flagging suspicious activity isn’t the same as proving fraud. It gives claims handlers a head start on a full investigation. The final judgement still rests with them.
Why human expertise matters more, not less
AI versus manual processing doesn’t have to be all-or-nothing. In fact, it works better when it isn’t. Insurance customers like the speed and convenience of automation. But they also value having a real person on the phone or email when they need one. Claims handlers still bring a layer of human expertise and judgement that AI can’t replicate.
AI takes away the routine work. Claims professionals become responsible for interpreting unusual situations, balancing conflicting evidence, and exercising discretion. They also negotiate settlements and support customers directly. Routine work becomes automated. Judgement becomes more valuable. Claims handlers shift from finding information to evaluating it, the ideal balance between automation and the human touch.
See how Nora supports your claims team, without replacing them
If your claims handlers are still buried in FNOL admin, document review, and manual fraud checks, that’s time they’re not spending on judgement calls that actually need a human. Insly’s Nora handles the routine work so your team can focus on the complex cases, faster decisions, and better customer outcomes.
Book a demo to see Nora in action.
