Kita transforms messy documents into reliable data for lenders in emerging markets

In the business corridor, I once saw a birth certificate filled in by hand, in pen. It reminded me how far digital lending still is from the real world.

Fintech of the day: Kita

Kita is building something very practical. Document AI for lenders in emerging markets, where the truth about a borrower is often trapped in messy PDFs, scans, photos, and forms that were never designed for machines.

The company was founded by Carmel Limcaoco and Rhea Malhotra. Their bet is simple: if you can reliably read invoices, bank statements, and tax forms, you can turn unstructured paperwork into risk signals a lender can actually use. Faster underwriting. Fewer manual checks. Less fraud slipping through because someone missed a line in a statement.

This matters a lot in markets like the Philippines, where many people and small businesses live outside the comfort of a clean credit score. I have seen lenders trying to make decisions with incomplete histories and documents that are inconsistent from one region to another. The hard part is not only OCR. The hard part is making sense of a country where the data is fragmented and the context is everything.

What I like about Kita’s approach is that it is not only about consumers. It is also about small businesses. A shop owner with invoices, tax forms, and bank statements should not wait weeks for a loan just because a human analyst needs to retype the same numbers into a spreadsheet. If AI can standardise inputs and flag anomalies, banks can say yes faster and say no with more confidence when something looks wrong.

In fintech, we spent years hoping one unified credit score would magically fix access to credit. In many places, that never became the solution. Document AI feels like a more honest bridge. Not perfect, but grounded in what people actually have today: paperwork.

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I would love to see Kita win in the Philippines and then expand to other markets where “messy documents” are the default, not the edge case. The next billion customers will not look like a neat CSV.

Where do you see document AI making the biggest difference in lending, consumer credit, SME loans, or trade finance?

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