Case study
Automated Risk-Signal Detection for a Global Insurer
How SquareShift built a custom OCR and machine learning pipeline that spots emerging risk signals in journals and social media, replacing thousands of hours of manual review for a global insurer.
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Client
One of the world's largest insurance and financial-services groups, serving close to 130 million customers across 70 countries.
Industry
Insurance
Services
Stack
OCR · NLP · Machine Learning · Real-Time Dashboards
How SquareShift delivered it.
The challenge
Hundreds of the client's risk analysts spent thousands of hours manually reviewing medical journals, publications, and social media feeds to catch emerging risk signals. Analysts started each search from a blank page.
What we delivered
SquareShift built a custom OCR system that pulls text from journals and publications, plus machine learning models that read the text and spot emerging trends. The results appear on a real-time dashboard that gives analysts a starting point instead of a blank page.
The outcome
Risk analysts now spend less time on manual document review and more time acting on the signals that matter.
An early-warning system is only as good as its first step — OCR that reliably turns a scanned journal page into clean text is what makes everything the models find afterward trustworthy.
AI & Machine Learning Practice Lead, SquareShift
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