Assistant Risk Analyst

As an experienced candidate, you will be responsible for various key result areas in the field of Anti-Money Laundering (AML) and Fraud Analytics. Your role will involve the following supporting actions:

• AML Transaction Monitoring & Pattern Detection:
• Lead comprehensive AML transaction monitoring programs across all business verticals.
• Develop and implement advanced pattern detection algorithms to identify suspicious transaction patterns, layering activities, and structuring behaviors.
• Design automated alert generation systems with intelligent threshold calibration to optimize detection rates while minimizing false positives.
• Conduct periodic effectiveness reviews of monitoring scenarios and update detection rules based on emerging typologies and regulatory guidance.
• Collaborate with Compliance and Legal teams for suspicious transaction reporting (STR) preparation and regulatory submissions.
• Fraud Analytics & Anomaly Detection:
• Establish robust fraud analytics frameworks for real-time and batch fraud detection across various areas such as Insurance claims, Investment transactions, Digital Lending applications, Payment transactions, and Super App activities.
• Develop machine learning models for anomaly detection including unusual transaction patterns, account takeover attempts, identity fraud, and application fraud.
• Create behavioral profiling systems to identify deviations from normal customer patterns and flag high-risk activities.
• Implement automated fraud scoring mechanisms with dynamic risk rating based on multiple parameters.
• Prepare detailed fraud trend analysis reports and collaborate with business units on fraud prevention strategies.
• Operational Risk Dashboards & Automation:
• Design and deploy comprehensive operational risk dashboards providing real-time visibility into risk metrics, control effectiveness, and emerging risk trends.
• Automate recurring risk reporting processes including KRI tracking, control testing results, incident monitoring, and risk event analysis.
• Develop self-service analytics capabilities enabling business units and risk teams to access relevant risk data and insights on demand.
• Implement predictive analytics models to identify potential operational failures, process breakdowns, and control gaps before materialization.
• Establish governance frameworks for dashboard maintenance, data quality validation, and user access management.
• Compliance Risk Analytics & Reporting:
• Develop data-driven compliance monitoring frameworks tracking adherence to regulatory requirements across all business verticals.
• Create automated compliance dashboards monitoring key compliance metrics, regulatory deadline tracking, obligation fulfillment, and breach identification.
• Conduct periodic compliance effectiveness assessments using data analytics to identify control gaps and areas requiring remediation.
• Prepare comprehensive compliance reports for senior management, board committees, and regulatory submissions.
• Analyze regulatory changes and assess impact on existing monitoring frameworks, recommending necessary enhancements.
• Data-Driven Control Insights & Recommendations:
• Analyze control testing results and monitoring data to derive actionable insights on control effectiveness and improvement opportunities.
• Develop evidence-based recommendations for control enhancements, process improvements, and risk mitigation strategies.
• Prepare executive presentations and reports translating complex analytical findings into business-relevant insights.
• Conduct root cause analysis on control failures, compliance breaches, and risk events to recommend preventive measures.
• Establish feedback loops ensuring recommended controls are implemented and effectiveness is validated through ongoing monitoring.
• Cross-Functional Analytics Collaboration:
• Partner with various business teams to understand risk profiles and analytics requirements.
• Coordinate with IT and Data Engineering teams for data integration, system enhancements, and analytics platform development.
• Collaborate with Internal Audit, Compliance, Legal, and Regulatory Affairs on audit support, compliance validation, and regulatory response preparation.
• Provide analytics expertise and insights to business strategy discussions, product launches, and process redesign initiatives.
• Facilitate knowledge sharing across business verticals on best practices, emerging risks, and effective control measures.
• Advanced Analytics & Machine Learning Applications:
• Research and implement cutting-edge analytics techniques including machine learning, artificial intelligence, and predictive modeling for risk detection.
• Develop unsupervised learning models for unknown pattern discovery and emerging risk identification.
• Create supervised learning models for classification, prediction, and risk scoring applications.
• Implement natural lan