Unstructured data is essential, but often challenging to use
Insurers rely heavily on structured data—policy dates, claim amounts, customer demographics—to assess risk and detect fraud. But some of the most valuable information is hidden in unstructured data, like adjuster notes, free-text fields, and intake documents. The challenge is that this information is lengthy, inconsistent, and difficult for humans to parse. Shift’s AI solves this problem by analyzing unstructured text at scale, uncovering suspicious details that would otherwise go unnoticed and helping insurers make faster, more accurate decisions.
Shift's AI detects fraud hidden in claim notes, preventing major losses
An insurer received what appeared to be a routine property claim for fire damage. At face value, the claim looked legitimate, and the structured data revealed nothing unusual.
Shift’s AI went beyond the structured claim data and analyzed the extensive free-text notes collected during intake and throughout the life of the claim. By processing this unstructured data, the AI surfaced critical red flags, triggering the insurer to conduct a deeper investigation.
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Claim denied, saving the insurer potential losses
- Fraud detected in unstructured notes that would have been hard to find manually
- Accelerated decision-making
How AI turns unstructured text from insurance documents into actionable insights
In this case, Shift’s AI demonstrated its ability to unlock hidden value in unstructured data. Claims are filled with free-text notes from adjusters, call centers, and investigators, providing information that is vital but often too lengthy and complex for human reviewers to analyze thoroughly. By applying advanced natural language processing, Shift’s AI was able to read through all of the notes, identify suspicious elements, and connect them with other claim data to reveal a clear fraud risk.
In this case, AI surfaced the following critical red flags:
- Mentions of potential arson
- Notes indicating that the claimant was not home at the time of the fire
- Additional contextual details inconsistent with the reported story
This level of insight simply wouldn’t have been possible manually. The insurer gained the ability to see beyond structured data fields and use all available information to make better decisions. Ultimately, Shift’s AI not only prevented a costly fraudulent payout but also proved how unstructured data can be transformed into a powerful asset for fighting fraud.
Learn more from our team of 200+ data scientists
This video is part of a series of interesting cases presented by our insurance-focused team of data scientists. For more examples of Shift Technology's AI-driven results, browse the AI in Action library
