Real-time fraud detection
Identify fraudulent transactions in real time using ML models combining rules and anomalies.
-50%
fraud loss reduction
The problem
No reliable steering on real-time fraud detection.
The current process is manual or inconsistent.
Decisions come too late due to weak signals.
Credit/fraud risk is poorly anticipated.
Prerequisites: required data & tools
Required data
- Transactions
- profils customers
- patterns historiques
Compatible tools
- Featurespace
- Feedzai
- SAS
- custom ML
Not sure you have the data? Our Maturity Auditor can assess your situation in two weeks.
Explore the Maturity Auditor →What we implement in 6-12 months
In 6-12 months: Identify fraudulent transactions in real time using ML models combining rules and anomalies. with measured impact on fraud loss reduction.
Weeks 1-2
Diagnosis
Weeks 3-6
Build
Week 7+
Delivery
Concrete deliverables
Business framing and decision rules for real-time fraud detection
Operational engine for real-time fraud detection
Steering dashboard with alerts
Action playbook and governance
Expert insight
Direct ROI: 40–70% reduction in fraud losses. Requires real-time processing.
— Datasive, expertise terrain
Tech maturity
High
Mature solutions, fast deployment
Medium
Maturing tech, requires customization
Emerging
Cutting-edge innovation, R&D approach
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Ready to solve this problem?
First step: a 30-minute call to understand your context.