AI scoring on every application.
Combine BVN, employment data, bank statements, and prior repayment behavior into a single risk score — automatically, transparently, on every loan that comes through your funnel.
Multi-signal scoring
Employment status, bank statement signals, BVN-derived attributes, and prior platform history feed into a single risk score.
Live model performance
Watch how the model is performing against actual repayment outcomes — accuracy, false positives, false negatives.
Explainable decisions
Every score is accompanied by the top factors that drove it. Required for compliance, useful for borrowers.
Risk-tier routing
Low-risk: auto-approve. Mid-risk: officer review. High-risk: auto-decline or escalate. You set the thresholds.
Bank statement parsing
Borrowers upload statements; we extract inflows, outflows, and salary patterns into structured fields automatically.
Audit-ready logs
Every decision logged with input data, model version, score, and human override (if any). Regulators love it.
From application to decision in seconds.
- 01
Capture the application
Borrower submits via your storefront or accepts an invitation. Required documents collected automatically.
- 02
Parse and enrich
BVN lookup runs. Bank statements get parsed. Employment is verified. Identity is confirmed.
- 03
Score the risk
Model produces a risk score with explainability — top factors driving the decision are surfaced.
- 04
Route to action
Auto-approve, send to officer review, or decline based on your configured thresholds.
Pulls signals from across your data sources.
Credit decisioning is only as good as its inputs. We pull from BVN, bank statements, prior LoanHQ history, and partner credit bureaus to build the richest possible picture.
Score smarter. Lend safer.
Set up your risk thresholds and let the model handle the volume.