Early access · Fintech & banking
Chefoba lets banks, fintechs, and payment providers train shared fraud and AML models on federated data. Each institution keeps its data in place. The result is governed, audited, and regulator-ready from day one, not a generic ML platform with federation bolted on.
Built on a federated learning system evaluated across two UK fintech platforms, four institutional clients, and 21,458 users.
How it works
Chefoba coordinates training across institutions without ever moving raw transaction or customer data between them.
Each participating institution trains on its own transaction data, inside its own infrastructure. Nothing raw ever leaves the building.
Chefoba scores each participating organisation and adaptively weights how much its model updates influence the shared model.
Model updates are combined under policy controls your compliance team sets, with no-code governance and a full audit trail.
The resulting shared model ships with automated regulatory evidence, ready for your compliance review and your regulator.
Backed by evaluation, not a pitch deck
Chefoba's federation core was evaluated end to end on a real 30-day remittance prediction problem across two UK fintech platforms. We report what worked and what didn't.
Federated model AUROC matched centralised training on the same problem. Decentralising the data added no measurable performance cost within a fixed model class.
Subgroup auditing by payment corridor surfaced a severe fairness gap that was invisible in aggregate accuracy metrics. Chefoba is built to find that gap before it reaches production, not after.
Evaluated across four institutional and geographic client partitions with 30 structured transaction features, including honest reporting of privacy-driven accuracy trade-offs.
Also supports
The same governed federation core applies where institutions hold sensitive patient records instead of financial transactions. Chefoba is built primarily for fintech and banking, and supports healthcare deployments on the same platform.
Healthcare use cases →Trust scoring, adaptive weighting, and automated evidence generation carry over unchanged. Only the deployment context differs.
Compare
Most platforms in this space are either broad data infrastructure with privacy bolted on, or open-source federation toolkits with no governance layer. Chefoba is purpose-built for governed, cross-institutional collaboration in regulated industries.
See the full comparison →Trust scoring, adaptive weighting, no-code policy management, and automated regulatory evidence generation are proprietary to Chefoba among the vendors we track.
We're onboarding a limited group of fintech and banking partners before general availability.
Join the waitlist