When it comes to claims processing, commercial insurance companies historically have been forced to choose between speed and accuracy.

Choosing speed means increased risk of errors and non-compliance, making hasty adjudication decisions that can affect profitability, and negatively impacting the customer experience if things go awry.

But choosing accuracy means risk of losing out to more nimble competitors that offer a faster customer experience and frustrating customers with long settlement times. That, in turn, negatively impacts your net promoter score (NPS), ultimately leading to customers jumping ship.

“Claims dissatisfaction is a major factor in driving policyholders to switch to another company, with 74% of dissatisfied customers either saying they did change providers (26%) or are considering it (48%),” according to a 2022 Accenture study.


Learn how a F50 Insurance company achieves 300% return on investment with Indico Data.

Part of the reason intelligent intake delivers a 70% reduction in manual document handling is integration with downstream insurance claims automation platforms such as Guidewire ClaimCenter. Today that’s a familiar swivel chair process, where a claims handler reads a claims email and attachments, looking for data to enter into Guidewire, including case owner, case status number, cause and date of loss, estimates for extent of loss, and the like.

With an intelligent intake solution such as Indico’s, AI models can “read” claim emails and attachments and pre-populate some 80% of the required fields in Guidewire ClaimCenter. This kind of automated claims handling not only dramatically speeds processing time but increases accuracy - because computers don’t get tired and make mistakes like people do. In fact, intelligent intake solutions that support staggered loop machine learning become more accurate over time by learning from when users accept or correct a model’s predictions and classifications.


View Episode 9 of Unstructured Unlocked, where Indico Data’s Christopher Wells talks with Steven Weiss, former Senior Vice President and Chief Underwriting Officer at Munich Re Specialty Group Insurance Service.

A key concern in a highly regulated industry like insurance is the ability to explain why an automated, AI-based solution makes the decisions it does. If a claim is rejected, the insurance company must be able to explain in simple terms the reason behind that decision. A sound intelligent intake tool will make that easy, with an audit trail that makes clear – in plain English – the rationale behind each claim decision. Additionally, given insurance claims handlers create the automated models, the AI models naturally reflect the way these professionals think during the claims assessment process.

Read our blog: How intelligent automation speeds up insurance underwriting and claims processing.