CrossFraud – Enterprise Fraud Risk Management Solution

Any economy relies on secure transactions and effective security to maintain a safe and efficient business environment. There is a significant business need for inexpensive, adaptable, real-time, cross-channel fraud detection and prevention solutions. MTL has defined a new way forward to address the issue through its highly flexible CrossFraud solution which has been successfully deployed and proven in leading banks in India and abroad.


CrossFraud is a highly advanced fraud detection solution and is ideal for banks and financial institutions which wish to be ready for the new era of risk and fraud management. CrossFraud is a complete solution to address fraud detection for Issuers, Acquirers and Processors. CrossFraud smartly blends the base technologies of Business Rules, Data Mining, Statistical Analysis and additional techniques like Complex Event Processing and Integrated Scoring to create a comprehensive self-learning solution. These techniques have been modulated for faster and precise fraud detection. In addition, these techniques help adaptive learning and are thus able to cover difficult to detect frauds as well.


Most risk and fraud solutions are built on technologies of BI and AI such as Business Rules, Neural Networks, Data Mining and Statistics. CrossFraud being no exception still edges out the competition as it combines AI and BI to produce a hybrid system that, aligned with comprehensive forensic features, produces a system that allies the non-deterministic power and flexibility of neural networks with the deterministic power of traditional rules that help in circumventing most types of frauds.


Salient Features:

  • Artificial Intelligence (AI): Neural Networks and Support Vector Machine based Clue Detectors.
  • Business Intelligence Rules: BI tools help the forensics experts with a single unified view. CROSSFRAUD offers a powerful and flexible rule builder engine as a key differentiator.
  • Complex Event Processing (CEP): Helps detecting patterns and relationships between events and offers event filtering, aggregation and abstraction.
  • Hybrid Scoring System: Combination of Rule System, Complex Event Processing (CEP), Artificial Intelligence (AI) and Business Intelligence (BI) in detecting fraud patterns for AML and fraud risk management.
  • Fraud by Example or Memorizer: Memorizer (patent-pending technology) is an innovative tool to detect the patterns in banking transactions based on examples shown or added by forensic experts during case management.


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