Underwrite borrowers anywhere in the world, in minutes.
LendTrace reads borrower documents, completes incomplete files, and drafts cited credit memos — so your officers can focus on the call that matters.
- account_holderMaria Santos
- available_balance38420.50 PHP
- monthly_inflow52,310.00
- tamperingnone · 0.04
Files sit incomplete. Good borrowers walk.
In emerging markets, the bottleneck isn't modeling — it's the file. Borrowers send messy documents, formats are local, and the bureau gives you nothing.
Credit officers spend most of their week reading, keying, and reconciling. The real decision takes minutes.
Files arrive incomplete
Borrowers send screenshots, photos, partial PDFs. Officers chase missing pages for days.
Documents don't fit your tools
GCash screenshots, KTP cards, CFDIs — none of them play nicely with form-based intake.
Reconciliation is manual
Cross-checking declared revenue against bank inflows happens in spreadsheets, by hand.
Verification is uneven
Tampering checks are inconsistent across analysts. Risk slips through the cracks.
From days to minutes, on the same file.
Same SME application, same files. LendTrace collapses every stage that doesn't require human judgment.
Three AI layers. One underwriting stack.
Each layer is useful on its own, and they compose into a single pipeline that turns raw borrower documents into a cited, decision-ready memo.
LendTrace Capture
Reads any borrower document, on day one.
Vision-language models extract structured fields from screenshots, PDFs, photos at angles, and local-format documents. No templates. No fine-tuning per format.
AI Credit Officer
Completes the file by talking to the borrower.
A polite, multilingual agent that follows up on missing pages over WhatsApp, SMS, or email — until the file is decision-ready.
AI Underwriter
Drafts a cited credit memo.
A structured recommendation with every claim cited back to a source line. Your team approves, declines, or overrides — every time.
Maria operates a small sari-sari store with consistent inflows. Bank statements reconcile with declared revenue within 1%. One minor inconsistency flagged for review.
Decision rests with credit officer. Always.
LendTrace never approves loans. Your team makes every call. Always.
LendTrace Underwriter
The whole stack. Borrower documents in, cited credit memo out. Built for lenders who want one vendor, one contract, one source of truth.
LendTrace Capture
Just the document API. Drop it into your existing workflow, get clean structured fields and fraud flags back.
Explore LendTrace Capture →Push borrower documents
Any format. Screenshots, PDFs, photos. Local IDs and bank statements supported.
Get deterministic signals
Structured JSON with cited sources, completeness scores, and tampering flags.
Generate a cited memo
An auditable recommendation with every line traceable back to a source document.
One stack. Every scenario you underwrite.
Microfinance & small-ticket consumer
High volume, thin files, lots of mobile money. Capture reads it; the API gives a yes/no signal in under a second.
SME & commercial lending
Heavy documents, real reconciliation, real memos. Drafted in 30 seconds, your officer signs.
CDFI & community lending
Mission-driven institutions need consistent, auditable decisioning. Deploy in your VPC, on your terms.
Decision-ready files, not raw extractions.
We don't hand you a JSON dump. We hand you a structured applicant profile, every claim cited back to a source line, ready for your officer to read and sign.
Your team spends time on judgment, not bookkeeping.
- ✓Identity verified · ktp_front.jpg
- ✓Address confirmed · barangay_permit.pdf
- ✓3 months bank statements reconciled
- ✓DSCR 1.84× · bank_stmt_q3.pdf
- ✓Monthly inflow ₱52,310 · gcash-jan.jpg + 2
- ✓Stable 9-month trend
One minor inconsistency: declared revenue ₱2.4M vs. AFS ₱2.38M. ~1% variance — likely rounding.
AI-native underwriting in emerging markets just became possible.
For the first time, vision-language models can read messy local-format financial documents — GCash screenshots, KTP cards, CFDIs — fluently and reliably, in the wild.
The bottleneck of underwriting in emerging markets has always been the file. That bottleneck is now a software problem.
Built for the markets where lending is hardest.
We started where the documents are messiest and the bureaus thinnest. Three regions live, more on the way.