TradingHub AMLA is a SaaS solution designed to detect and mitigate the risk of money laundering in financial markets. Unlike traditional rules-based systems, AMLA employs a model-based approach calibrated from historical data to identify suspicious trading patterns and behaviors. The platform analyzes trade economics, settlement data, and customer due diligence (KYC/CDD) information, providing a holistic risk assessment for each customer. AMLA aggregates multiple risk signals, recognizing that the presence of several red flags is more concerning than isolated incidents. The system offers flexibility through an optional Calculation as a Service (CaaS) module, allowing users to define custom risk detection metrics and scenarios. AMLA is built to address regulatory requirements and market participant needs, supporting robust compliance and risk management for financial institutions.

Key Features

Model-Based Suspicious Behavior Detection Uses advanced models calibrated from historical data to identify money laundering risks.

• Avoids unreliable, simplistic rules
• Detects complex and evolving suspicious patterns

Holistic Customer Risk Aggregation Aggregates multiple risk signals for comprehensive risk assessment.

• Increases accuracy by considering all relevant red flags
• Prioritizes high-risk customers for investigation

Wide Detection Metrics Evaluates risk using trade economics, settlement, and KYC/CDD data.

• Goes beyond settlement-focused approaches
• Provides broader coverage of potential money laundering activities

Flexible Customization (CaaS Module) Allows users to define custom risk metrics and detection scenarios.

• Supports both simple and complex use cases
• Adapts to specific institutional requirements

Regulatory Compliance Support Addresses needs identified by regulators and market participants.

• Facilitates compliance with evolving AML regulations
• Provides audit trails and reporting for regulatory review

Benefits

Enhanced Detection Accuracy Improves identification of sophisticated money laundering schemes.

• Reduces false positives compared to rules-based systems
• Captures complex, cross-product abuse

Operational Efficiency Streamlines compliance and risk management workflows.

• Aggregates risk signals for focused investigations
• Reduces manual review burden

Regulatory Confidence Supports robust compliance with financial market AML requirements.

• Comprehensive reporting and audit capabilities
• Addresses regulatory expectations for customer risk assessment

Scalability and Flexibility Adapts to diverse institutional needs and market conditions.

• Customizable detection metrics
• Suitable for a wide range of financial institutions