How Insurance Teams Can Get Better Claims Results with Less Manual Work

Insurance professionals are expected to handle claims quickly and accurately. Doing so manually has become inefficient: rushing increases the risk of mistakes, while thorough reviews slow processing.

Incorporating automation into their workflows means claims teams no longer need to prioritize one over the other. The following are some of the most effective ways to improve claims accuracy and turnaround while cutting repetitive manual work.

Automate the First Notice of Loss

Inefficiencies that start at FNOL continue to accumulate downstream. Addressing it early on reduces the need for later corrections. The idea is to digitize and automate the intake to minimize mistakes and avoid the need to chase missing information.

Ideally, information should be captured automatically when interacting with emails or web forms, while OCR software can be used to digitize physical files. Information obtained this way needs to be validated against existing records. It’s crucial to also identify and retrieve any missing information at this stage.

Automate the Admin Work Surrounding Each Claim

The repetitive work insurance professionals perform when interacting with claim-related documents is among the most impactful manual time sinks. The process of going over various types of evidence and then manually extracting, categorizing, and transferring relevant information is an excellent candidate for automation.

The process can involve automation tools with different levels of sophistication and autonomy. Trigger-based automation can be used to route incoming emails, name files and attach them to correct claims, and update their statuses.

All in one AI platforms are helpful here as they can then identify and extract data like claim numbers, invoice totals, or claimants’ personal info. Then, templates and workflow triggers can send requests for unreceived documents or missing data that couldn’t be extracted.

Intelligently Triage Claims

Different claims need to be approached with different levels of attention and handled through appropriate workflows. This is exactly the type of complex, multi-step process that AI agents excel at automating.

An AI agent can gather necessary information and assess whether to send straightforward claims directly to processing, request missing information, flag suspicious claims for fraud investigation, and send complex claims to specialist adjusters.

Humans still make the final decision, and AI agents need both access to predefined criteria and proper guardrails to help safely and effectively.

Support Adjusters with Decision-Making Insights

Not every aspect of insurance claims needs to be automated. Merely ensuring that adjusters’ work is faster and more consistent improves efficiency.

You can achieve this by giving adjusters access to tools that automatically surface relevant clauses, provide summaries, compare similar claims, explain why claims were flagged or routed their way, and recommend next steps.

Add Consistency through Fraud and Accuracy Checks

Another way of improving work quality is making sure that money isn’t mispent on payouts for fraudulent claims. To that end, it makes sense to augment workflows with fraud and accuracy checks that spot and alert insurance professionals to anomalous behavior.

AI systems are useful here for comparing current information with previous claims, identifying redundancies or documentation conflicts, cross-referencing information, and surfacing claims that warrant an intervention from the Special Investigations Unit.

Automate Back-Office Work and Communications

While not technically part of claims assessment, reducing the work surrounding inquiries, follow-ups, inspection scheduling, or performing payment-related admin considerably speeds up turnaround times.

Automation does a lot of heavy lifting here. You can automatically notify customers if a claim’s status changes or if they need to take specific actions. It also makes sense to automate payments once conditions are met and update internal systems as claims get processed.

Conclusion

It’s worth reiterating that removing human agency from claims processing is not and should not be the goal of automation. Even sophisticated systems like AI agents aren’t a replacement for the experience-based judgment seasoned professionals contribute when handling complex cases or weighing consequential decisions.

Therefore, the best approach is a balanced one. Automate predictable and repetitive work and leverage AI when it adds genuine value. But most importantly, have people be responsible for and in charge of the most impactful decisions. By finding the right balance between the two, you can get better claims results with less rote work at hand.

insurance teams, results, automation