1. AI/ML-Based Alert Triage System
- Objective: Develop an AI-driven solution that automatically reviews, prioritizes, and either escalates or dismisses alerts based on predefined criteria (e.g., transaction size, frequency, geographic location, etc.).
- Key Features:
- Integration with existing TMS
- AI/ML model to classify and rank alerts based on risk levels
- Ability to explain decisions (e.g., why a particular alert was flagged as high-risk)
- Reduced false positives through improved pattern recognition
2. Natural Language Processing (NLP) for Investigative Analysis
- Objective: Create a solution that uses NLP techniques to automatically parse, understand, and analyze unstructured data such as customer communications, transaction narratives, and external reports.
- Key Features:
- Automated extraction of key information from structured and unstructured data
- Risk-based prioritization of alerts based on the semantic context of the data
- AI-driven investigation summaries for AML analysts
- Continuous learning from historical investigation outcomes
3. Predictive Analytics for Proactive Detection
- Objective: Develop a predictive analytics system that forecasts potential future suspicious activity based on historical alert patterns, transaction data, and external events.
- Key Features:
- Predictive modeling using historical data to identify trends
- Proactive identification of high-risk customer segments or transactions
- Early warning system for emerging fraud or money laundering schemes
- Integration with external data sources (e.g., political risk, customer sentiment, market trends)
4. Collaborative Automation with Human-in-the-Loop (HITL)
- Objective: Build a hybrid solution where AI assists analysts by handling routine tasks (e.g., data gathering, initial alert triage) while human experts make final decisions on complex cases.
- Key Features:
- Automated workflows for alert data gathering and preliminary analysis
- Smart recommendations for analyst review, reducing manual intervention
- A feedback loop where human decisions improve the machine's decision-making over time
- Real-time alerts and notifications to analysts for urgent cases
Expires on January 08, 2025
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