Combine Fraud ML and SIEM into One Seamless Platform
Our platform allows fraud experts and data science teams to streamline predictive fraud modelling and improve both detection and acceptance rates.
- Automate Model Development Lifecycle
- Save thousands of hours in data preparation, feature engineering, resampling and parameter tuning
- Easily verify performance against live data and redeploy automatically.
All devices, All channels, All Attack Vectors
Consumer habits are changing, and with them fraud patterns and exploitation types.
- End to End Payment Fraud Detection Platform
- AML Prevention
- New Device and Account Takeover
Full Compliance Throughout the Decision LifeCycle
ModelFlow provides concise and transparent reasoning for each transaction processed, while fully complying with privacy regulations and standards.
- Fully PSD2 Compliant
- GDPR Compliant
- Complete reporting and data logging on all components of the system
On Prem - Private Cloud - Secured Remote API
Deploy Anywhere, Scale Infinitely
- Containerized Environment Allows Rapid Deployment and Scalablity
- No complex big data infrastructure needed
- Ultra Rapid Response Times
Connect Seamlessly and Keep Transactions Flowing
Orchestration Hub combining all risk assessment sources along the customer journey. Rapid integration alongside preexisting detection systems with custom event handling.
- Case manager with transparent reasons for reject/approve
- Integrate with pre-existing rule based systems
- Fully compatible with 3DS2, SCA
Trust. It's Our Business.
In a world facing challenges and uncertainties, ModelFlow combines cutting edge Auto AI modelling for card fraud, ATO, AML with seamless production deployment, integration of 3rd party detection & legacy systems into one unified risk orchestration hub spanning and securing the entire user interaction journey.
One Unified Fraud Hub
ModelFlow integrates high volume fraud pipelines and AI deployment processes across all channels and devices, while reducing costs of predictive model creation and maintenance.