You find out after it's already happened.
A month-end report is a photograph; the business is a film. By the time the ledger shows a miss, the intervention window has closed.
Credit Risk Orchestration · Nairobi
The borrower you just wrote off was your best customer.
UNBRDN is a read-only intelligence layer that shows you a small business in trouble weeks before the ledger does — early enough to restructure instead of write off. It sits on top of your existing core system. No replacement, no downtime, and every credit decision stays with your committee.
A backtest on your own book, at no cost.
Send us a CSV export of your loan ledger — 24 months if you have it. We run it through UNBRDN and show you what our screen would have flagged, and when, against what actually happened. No integration, no IT involvement, no commitment. If it tells you nothing you didn't already know, that's a useful answer too.
The machinery is built to write people off.
Not through negligence. Through timing. Every part of a conventional credit process reports on the past, and the past is the one thing the person accountable for the loan book cannot change.
The same borrower gets different answers.
Similar files, different officers, different outcomes. Portfolio risk you can't predict because the decisions weren't consistent.
You can't show your working.
When an auditor asks how a loan was approved, “the officer used judgement” is an increasingly difficult answer.
Recovery starts too late to work.
By the time the recovery team mobilises, the borrower is in crisis and most of the recoverable value has gone.
Three stages across the credit lifecycle.
UNBRDN reads from the systems you already run. All credit approvals remain with your own committee.
Screen
Price the borrower on real cash flow before lending, not on a snapshot. Bank and mobile-money statements are read, normalised and turned into a decision-grade view of how the business actually earns.
What it means for you: You approve on evidence you can point to, and two officers looking at the same file reach the same answer.
Monitor
Continuous early warning against your own policy thresholds, not a universal benchmark. Amber flags before a payment is missed. IFRS 9 Stage 2 tracking automated.
What it means for you: You get a window in which a restructure is still cheap, and your staging position is defensible without a manual exercise.
Rehabilitate
A structured turnaround path instead of a write-off, and the cured borrower re-enters origination as a known risk.
What it means for you: The relationship survives, and the borrower you already understand becomes your best-qualified next loan.
That last step is the one nobody else builds. It's the whole point.
The loop most lenders never close.
- Screen
- Monitor
- Rehabilitate
- Re-lendreturns to Screen as a known risk
Most lenders never close this loop. The cured borrower is the best-qualified lead you already own.
It sits on top. Nothing gets replaced.
Your existing systems
Core bankingCollectionsPortfolio toolsExternal data sources
UNBRDN intelligence layer
Read-onlyScreenMonitorRehabilitate
Outputs
Early-warning alertsCredit memosCommittee packsFull audit trail
- Reads from your systems, never writes to them
- Deploys in weeks
- Zero engineering downtime
Frontier-grade credit AI, on hardware you own.
We built two proprietary models — one that reads bank and mobile-money statements, one that reasons through the credit decision. Both are small enough to run on a single GPU inside your own building, which means borrower data never leaves your environment and there is no per-decision cloud fee. In our benchmarking they reach parity with the leading frontier models at a fraction of the cost per decision.
- Data never leaves your building
- Cost per decision falls as your book grows
- No vendor can change your price, your model, or your access
Who built it.
Alex Ndubai
Founder & CEO
Two decades in credit recovery and SME lending.
Erick Oluoch
Co-Founder & CFO
20+ years in institutional credit risk. Founder Chairman, Association of Debt Recovery Agents Kenya.
Ernest John Ndung'u
Co-Founder & CTO
Architect of the UNBRDN platform. Senior Software Engineering Manager at Microsoft.
We came at this from the recovery end. Twenty years on the wrong side of these decisions shows up in what we chose to build.
What we have observed so far.
Observed across deployments and pilots — direction, not a guarantee.
- ~25%
- reduction in non-performing loans
- ~30%
- improvement in portfolio at risk
- ~90%
- faster underwriting — mixed borrower data to a decision-grade view in under five minutes
- 21 days → 48 hours
- time to disburse on secured SME files
- 101,000+
- live accounts processed in a single portfolio review
Amber flags fire against your own thresholds, typically weeks before the ledger misses a payment. We do not publish a fixed prediction window, because the right window is the one your own policy defines.
Backed by
Nairobi International Financial CentreCertified — July 2026 cohort- ISO 27001-aligned
- GDPR and Kenya DPA 2019 compliant
- IFRS 9 aligned
Start with your own book.
A CSV export, a backtest, and an honest read of what our screen would have flagged and when. No integration, no commitment.
Request a backtestOr just talk to a founder — support@valrcapital.co