Transaction fraud
Identify coordinated behaviour across accounts, devices and channels.
Noysau develops compliance and risk products built on graph intelligence.
A transaction, customer or document tells only part of the story. Noysau connects data so fraud, compliance and risk teams gain the missing context.
Identify coordinated behaviour across accounts, devices and channels.
Connect flows and focus reviews on sensitive cases.
Resolve related identities, documents and entities.
Complement assessment with understandable relationship signals.
For payment service providers across WAEMU, KER brings fraud detection, AML analysis and case handling into one workspace.
Graph variables provide context that rules and conventional models cannot capture alone. They can help distinguish a community solidarity chain from a mule network.
Discover KER
Noysau turns relationship complexity into readable, controlled and traceable decisions.
See the relationships that give meaning to an isolated event.
Focus human review on situations that require it.
Retain the facts, factors and decision path.

« Our market needs compliance and risk management tools designed around its own financial ecosystem. The challenge is not merely to detect an unusual structure, but to understand its context: distinguish a legitimate neighbourhood savings circle from a network of mule accounts, then give your risk teams the evidence they need to make a sound decision. »
Abdoulaye A. GayeFounder | Machine Learning Engineer
The blog examines the operational choices surrounding fraud, AML and relationship analysis.
What must be defined before settlement.
FraudWhy the network matters more than an isolated profile.
GovernanceTurning a signal into a defensible decision.
We agree the need, authorised data and success criteria before any demonstration.