For risk & underwriting
Faster decisions. Your policy.
The full underwriting engine, driven by an underwriting agent that assembles
the data picture your team would build by hand, applies your rules, and shows its working on
every call. Avexo executes your credit box consistently. It does not change it.
Your stretch of the line
The desk owns underwriting and disbursal.
The engine turns a qualified lead into a defensible, auditable decision, then hands the rest of the line the data it produced.
01LeadSales floor
02UnderwriteFull data picture, scored against your policy
03DisburseDecision and drawdown, with a complete trail
04MonitorStrategy
05InsightStrategy
What's broken
Manual underwriting doesn't scale. Quality doesn't either.
The losses don't come from a shortage of good borrowers. They come from depth-limited underwriting, applied unevenly, on files that looked clean on the financials.
01
Depth depends on who opened the file. A senior underwriter checks a dozen things, including whether the top customers and suppliers are real and whether the director is selling to himself. A junior checks half that and skips the network layer, because it takes hours and no form requires it. Same ticket, different output. The gap shows up in DPD three months later.
02
The most important checks are the least auditable. AML screening, counterparty cross-checks, supplier identity: done differently by every analyst, logged inconsistently, often not logged at all. When a file turns bad, the trail on what was actually checked is thin, and "the underwriter reviewed it" is not an answer for your board or your regulator.
03
Scaling means hiring, not optimising. Every file is hours of lookups and manual checks. To do ten times the volume at the same quality, you need close to ten times the people. There is no other path under the current model.
Why it matters
One file a quarter that clears where a thorough senior's supplier and related-party check
would have flagged it is enough to erase the margin on the hundred that went right. One in a
hundred is all it takes.
What the engine does
A defensible decision, faster.
01
The full data picture, automated. Registries, filings, commercial and consumer bureaus, banking and transaction data, tax filings, litigation and watchlists: pulled, cross-referenced and flagged. No manual lookup, no step that depends on the analyst remembering to check.
02
Your policy, encoded. Your cutoffs and rules run the decision. We do not touch your credit box; we apply it the same way on every file, and the limit falls out of policy rather than analyst gut.
03
Shows its working. Every call arrives with the evidence and the trail behind it, versioned and ready for second-line review and audit.
04
Checks ordered by cost and signal. Vendor pulls run cheapest-and-strongest first. If an early signal is enough to decline, the pipeline stops there instead of running the full stack anyway. Full depth is reserved for files that clear the early gates.
Risk coverage
Every risk your committee raises, covered by design, not by luck.
The questions a credit committee always asks, and the specific machinery that answers each one on every file. Nothing here depends on the analyst remembering to check.
01
Identity risk. KYB and KYC against official registries, not self-declared documents. We trace the ultimate beneficial owners up the ownership chain and screen the entity and every director against sanctions, PEP and AML watchlists. An entity that cannot be verified in any registry does not clear.
02
Credit risk. Full financial spread and ratio analysis, benchmarked against the peer distribution rather than read in isolation. Corroborated by commercial and consumer bureaus and external ratings, and cross-checked against bank-statement cash flow and filed revenue.
03
Fraud risk. Our differentiator. Our proprietary network model turns the supply chain into a fraud sensor: related parties, common directors, circular and round-trip trade, counterparty concentration, and counterparties with no digital or registry footprint. Almost no one uses the network as a fraud signal, because it is too slow to do by hand.
04
Model risk and quality. An AI model is a living system, so maintenance is part of the product. We run continuous benchmarking against realised outcomes, drift monitoring, and automated variable discovery, and every decision is versioned and audit-trailed. The model does not decay quietly.
Where the line is
The credit decision stays with the lender. Avexo is enabling technology; final approval and
policy ownership remain with your desk.
See a real underwriting run.
Sample cases, the data sources for your market, and the full proposal are shared privately on request.