Fraud Risk Analytics Team Manager
Lead enterprise strategy and execution to prevent, detect, and disrupt digital fraud, scam victimization, and money mule activity across customer channels. This role integrates fraud strategy, financial crime intelligence, customer protection, and operational response to reduce losses, protect customers, and strengthen regulatory compliance.
Combines fraud prevention with scam ecosystem defense.
Serves as a bridge between fraud, cyber, and product teams.
Focuses on proactive risk reduction rather than only reactive response.
Key Responsibilities
- Risk Strategy & Oversight
Develop and execute a holistic digital fraud, money mule, and scam prevention strategy across channels, including online banking, payments, onboarding, and authentication.
Embed prevention-first controls across the product lifecycle and customer journeys.
Advise executive leadership on emerging fraud threats, regulatory expectations, and risk posture.
Define risk appetite, key performance indicators, and loss targets for digital fraud and scam exposure.
- Analytical Leadership
Build and mentor a team of data scientists and analysts to develop and implement advanced machine learning and statistical models for fraud detection and prevention.
Drive portfolio fraud analytics across customer segments and provide actionable insights to inform risk strategies.
Develop predictive models to monitor and mitigate emerging fraud threats, integrating real-time detection capabilities with engineering and technology teams.
Use data-driven insights to recommend improvements to fraud prevention systems and technologies.
- Program Development & Collaboration
Partner with internal stakeholders, external vendors, and customers to launch and update risk controls across products.
Act as Business Segment Relationship Manager for vendor partnerships, ensuring compliance with third-party risk management requirements.
Collaborate with audit, business segment, and corporate risk teams to address issues and support strategic objectives.
- Operational Excellence
Manage, mentor, and develop a team within Fraud Strategy and Analytics, fostering a collaborative, innovative, and high-performance culture.
Establish team goals, measure performance, and ensure alignment with company objectives.
Drive operational efficiency and scale through process improvement, automation, and staff development.
Develop chargeback management strategies for card issuing and travel-related businesses.
- Documentation & Compliance
Create and approve risk assessments for new product launches and enhancements.
Maintain current documentation, including credit policies, procedures, and process flows.
Ensure adherence to corporate and business unit policies, standards, and regulatory requirements.
Qualifications
- Bachelor’s degree required; advanced degree preferred. In lieu of a degree, additional years of segment-specific or risk-related experience may be considered.
- 10+ years of experience in fraud strategy, fraud prevention, data analytics, and risk management.
5+ years of experience in digital fraud risk management.
- Deep expertise in identity and payment fraud methods, tools, and processes for prevention, detection, and fraud operations.
- Advanced proficiency in data science techniques, including machine learning, predictive modeling, statistical analysis, and data.
- Experience with fraud detection platforms, rule engines, and data visualization tools.
- Strong understanding of payment processing systems, card networks, and risks specific to card transactions and corporate expense management.
- Excellent analytical, organizational, and problem-solving skills.
- Strong verbal and written communication skills, with the ability to present requirements and issues clearly.
- Ability to lead multiple projects simultaneously, prioritize effectively, and thrive in a fast-paced, evolving environment.
Proficiency in Microsoft Office and analytical tools such as SageMaker, Python, R, SQL, and/or SAS.
- Knowledge of risk management principles and regulatory compliance requirements.