Define risk-based scenarios through a graphical UI. No need to code complex queries or algorithms.
Ingest and process billions of data points from multiple sources and identify suspicious transactions and behaviours in real-time.
Allocate investigations to team members, and manage the process from identification through to action and outcome.
Connect external and internal data along with our Fraud Decision Engine
Scalable Rule and Ruleset Management
Dynamic Rules based on pattern recognition
Sophisticated Rule Creation with the Feature Platform
Actionable Rules with Customized Decisioning
Set Risk approach based threshold values
Automated Rule Recommendation to Detect New Fraud Patterns
Rule Performance Monitoring and Testing
Customer Behavior Analytics
Customer Risk Score for easy decisioning
Entity Relationship Analytics based Network Diagram
Customer Segmentation based on Risk approach (Black/Grey/White)
Fraud Pattern Analysis
Auto ML based fine tuning of Models
Reduce False Cases Modeling
Alert Generation & Investigation
Alert Severity Categorization (High/Medium/Low)
Integration with Multiple System through APIs
Highly efficient Advance Matching Module
Customer profile based recommendation workflow
Recommendation Engine Performance Monitoring and Testing
Use the very latest AI to aid your analysts in identifying true false negative, and highlighting false positives.
Rapidly plug holes in your existing AML processes, identify previously unknown threats and strengthen your controls.
Install or reinforce your AML system in a matter of hours, on premise or cloud, and instantly adapt to new regulations.
Use a dedicated test area to reduce false positives by up to 97% and uncover hidden money laundering patterns.
Define and test new rules and regulatory scenarios through a graphical UI built for non-technical business users.
An AML platform adaptable to every company's needs, from global to boutique financial services firms.
Our Risk & Fraud Platform are designed for unified deployment to detect fraud or point solutions to cover your specific needs.
Resolve entity for both structured and semi structured data including transaction. Provides single view of customer which forms the foundation of fraud analytics.
Identify complex relationship using behavioural , KYC & Transactional data. Explore the Network for potential fraud probability to bring context to data.
Make automated decisions using AI Scoring across: Transactions Analytics, Entity Level Analytics, Network Level Analytics
Use Third party data such as KYC, Trade Intelligence etc to generate insights beyond the bank data to help identify the relationship as well as check historical background of customers.