Fragmented records, unlinked newspaper notices, and manual checks that routinely fail have left India's lending system exposed. Cubictree’s AI Property Compliant Report is changing that, one property at a time Gayatri Guha The file was complete. The legal opinion was clean. The sanction letter
Cubictree extracts 35M property notices from 125K Indian newspapers (10-year physical archive) using multilingual AI and links them to 4.5B+ litigation records, classifying property risk in 4 levels for lenders. For lending institutions, this surfaces hidden fraud—same collateral across multiple loans, properties previously sold—that manual compliance systems have historically missed, enabling data-driven risk decisions at scale.
The file was complete.
The legal opinion was clean.
The sanction letter had been issued.
By every conventional measure, an 180 crore loan processed through a major institution in New Delhi had passed.
What nobody had looked at was a newspaper notice, published in a regional publication, flagging that the transaction was fraudulent.
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