Fraud Analytics Manager
5 days ago
We are seeking a highly skilled Fraud Analytics Manager to join our team at Scotiabank. As a key member of our Fraud Management Group, you will play a critical role in ensuring the overall success of our fraud mitigation strategies.
Key Responsibilities- Contribute to Fraud Strategy Development: Collaborate with cross-functional teams to design and implement advanced analytics techniques to enhance fraud mitigation capabilities for multiple products across the Canadian Retail portfolio.
- Lead Fraud Analytics Initiatives: Develop, execute, and monitor fraud strategies for customer onboarding and product applications, ensuring compliance with governing regulations and internal policies.
- Expertise in Fraud Platforms: Become an SME of Application Fraud platforms such as Citadel, ThreatMetrix, Emailage, EnStream, PRM, etc., and leverage this expertise to drive strong partnership with Fraud Operations.
- Performance Reporting and Analysis: Regularly report on the performance of existing fraud strategies deployed in Canadian Banking, identifying areas for improvement and opportunities to enhance risk/return.
- Collaboration and Communication: Drive strong partnership with Fraud Operations, IT partners, and vendors to identify opportunities for improvement, ensuring alignment with business objectives.
- Risk Management and Escalation: Identify and escalate fraud risks that are or will become in excess of the Risk Appetite, ensuring timely and effective mitigation.
- Data-Driven Decision Making: Leverage data mining tools (SAS, Python, R) to formulate fraud strategies that minimize fraud losses while maintaining a positive customer experience and controlling operating costs.
- Leadership and Project Management: Lead/participate in the identification, development, and implementation of new initiatives, contributing to and supporting a variety of projects and initiatives across the Fraud Management Group.
- Operational Risk Management: Understand how the Bank's risk appetite and risk culture should be considered in day-to-day activities and decisions, actively pursuing effective and efficient operations of his/her respective areas.
- Education: University degree in statistics, mathematics, or computer science.
- Experience: 3-5 years analytical experience, including statistical analysis, ideally related to Fraud Analytics or Risk Management.
- Technical Skills: Strong coding, organizing, and manipulating large amounts of data (SAS, R, Python), experience with PRM or similar fraud platform strongly desired.
- Soft Skills: Strong prioritizing, planning, analytical, presentation, project management, and relationship building skills, strong communication skills essential with clients, vendors, and management.
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