Broadgate
About the Company:
Our client is a fast-growing financial technology company providing credit and financial wellness products across the consumer and lending ecosystem. The organization leverages data, analytics, and modern technology to expand responsible access to credit and improve customer experience.
Role Overview: Develop and execute enterprise-wide fraud prevention and detection strategies across products and channels. Evaluate and implement best-in-class fraud prevention technologies and data sources. Create and maintain a multi-year roadmap for fraud strategy, technology enhancement, and data integration. Analyze internal and external fraud data to identify trends, emerging risks, and actionable insights. Serve as a subject matter expert for fraud strategy, tools, data, and risk analytics. Build and monitor key fraud performance metrics and dashboards to measure effectiveness and identify opportunities. Lead initiatives related to identity verification, device intelligence, and KYC improvements. Design and maintain advanced analytical tools and algorithms to detect and mitigate fraud. Continuously tune and optimize existing fraud rules, scorecards, and workflows to enhance detection accuracy. Partner with IT, Product, and Operations to enhance system integration, rules deployment, and automation capabilities. Prepare and deliver high-quality reporting and recommendations to senior management and other stakeholders. Stay abreast of evolving fraud tactics, technologies, and regulatory expectations to ensure best-in-class defenses. Provide thought leadership and mentor junior analysts to build organizational fraud analytics capability.
Experience and Education
Bachelors degree in Statistics, Economics, Finance, Mathematics, Data Science, or a related quantitative discipline. Masters degree preferred. Minimum of 4+ years of experience in financial services with a focus on fraud risk management, analytics, or strategy. Proven experience with fraud tools and third-party data providers (e.g., TransUnion, Clarity, iOvation, LexisNexis, NeuroID, etc.). Strong hands-on skills in data analysis using SAS, SQL, Python, or similar tools. Deep understanding of fraud typologies, identity verification, and application fraud mitigation across digital and traditional channels. Demonstrated ability to translate data-driven insights into actionable business strategies. Strong cross-functional collaboration and communication skills with both technical and non-technical stakeholders. Ability to manage multiple initiatives simultaneously and influence at all organizational levels
Role Overview: Develop and execute enterprise-wide fraud prevention and detection strategies across products and channels. Evaluate and implement best-in-class fraud prevention technologies and data sources. Create and maintain a multi-year roadmap for fraud strategy, technology enhancement, and data integration. Analyze internal and external fraud data to identify trends, emerging risks, and actionable insights. Serve as a subject matter expert for fraud strategy, tools, data, and risk analytics. Build and monitor key fraud performance metrics and dashboards to measure effectiveness and identify opportunities. Lead initiatives related to identity verification, device intelligence, and KYC improvements. Design and maintain advanced analytical tools and algorithms to detect and mitigate fraud. Continuously tune and optimize existing fraud rules, scorecards, and workflows to enhance detection accuracy. Partner with IT, Product, and Operations to enhance system integration, rules deployment, and automation capabilities. Prepare and deliver high-quality reporting and recommendations to senior management and other stakeholders. Stay abreast of evolving fraud tactics, technologies, and regulatory expectations to ensure best-in-class defenses. Provide thought leadership and mentor junior analysts to build organizational fraud analytics capability.
Experience and Education
Bachelors degree in Statistics, Economics, Finance, Mathematics, Data Science, or a related quantitative discipline. Masters degree preferred. Minimum of 4+ years of experience in financial services with a focus on fraud risk management, analytics, or strategy. Proven experience with fraud tools and third-party data providers (e.g., TransUnion, Clarity, iOvation, LexisNexis, NeuroID, etc.). Strong hands-on skills in data analysis using SAS, SQL, Python, or similar tools. Deep understanding of fraud typologies, identity verification, and application fraud mitigation across digital and traditional channels. Demonstrated ability to translate data-driven insights into actionable business strategies. Strong cross-functional collaboration and communication skills with both technical and non-technical stakeholders. Ability to manage multiple initiatives simultaneously and influence at all organizational levels