Fraud Risk Manager

Job Description

• Define and manage large-scale fraud prevention initiatives from scoping to implementation and continuous improvement.
• Set up mechanisms to track performance metrics, identify trends, and define mitigation plans as required
• Lead and mentor a team of fraud risk management professionals, fostering a collaborative, high-performance culture.
• Communicate effectively with executive-level stakeholders, regulatory bodies, and external partners
• Build and maintain strong partner relationships to support fraud management initiatives
• Oversee timely and accurate submission of regulatory returns pertaining to fraud and data to RBI and other authorities.
• Maintain oversight of regulatory and internal reporting, ensuring risk-related MIS and risk metrics are updated.
• Deep understanding of payment systems, fraud detection technologies, and risk management tools.
• Experience with developing and implementing fraud controls, policies, and solutions.
• Develop Fraud Detection Models: Design and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns.
• Enhance Systems: Continuously optimize fraud monitoring systems to improve detection accuracy and reduce false positives.
• Data-Driven Insights: Analyse internal and external data sources to identify vulnerabilities and recommend proactive measures.
• Performance Metrics: Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies. Industry Monitoring: Stay updated on emerging fraud tactics, industry benchmarks, and regulatory changes.
• Competitor Analysis: Analyse competitors risk management strategies to identify opportunities for improvement.
• Market Trends: Provide actionable insights from market intelligence to inform strategic decision-making.

Experience

• 10+ years of experience in fraud, risk management, or least 3 years in a leadership role.

Technical Skills

• Expertise in data analytics tools (e.g., Python, R, SQL, SAS).
• Familiarity with machine learning platforms and fraud detection software.
• Knowledge of industry-specific regulations and compliance standards.

Key Competencies

• Strong analytical and problem-solving skills.
• Excellent leadership and team-building abilities.
• Strategic thinker with strong business acumen.
• Effective communicator with the ability to convey complex data insights to non-technical stakeholders.