Fraud and Digital Acquisition Business Intelligence Analyst

Fraud and Digital Acquisition Business Intelligence Analyst

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• Connect business problems with data to produce insightful, data-driven analysis.
• Leverage analytics and risk models to drive operational improvements in areas such as fraud detection and customer onboarding.
• Analyze portfolio behavior to identify anomalies, emerging trends, drop-off points, and areas for improvement across customer funnels.
• Conduct root cause analysis on performance issues and fraud events to uncover underlying causes and continuously improve coverage and efficiency.
• Identify proxy variables or creative data substitutes when ideal data is not available.
• Design and maintain dashboards and analytical tools that track overall business performance, including DCA metrics (e.g., approval rates, automation rates, conversion trends) and fraud performance (e.g., fraud loss performance, rule efficiency, alert-to-case conversion rates) over time.
• Monitor system KPIs, evaluate performance trends, and recommend improvements.
• Deliver insights to the organization that optimize revenue and risk.
• Support the implementation of data-driven strategies that transform processes to enable efficiency and scale.
• Contribute to optimizing fraud detection systems to capture fraud and minimize customer disruptions.
• Collaborate with Data Scientists to support the building and operationalization of machine learning models to solve risk problems and enhance fraud detection.
• Assist in incorporating external threat intelligence and business context into strategic recommendations.
• Cross-Functional Collaboration & Communication:
  • Partner across internal stakeholders—including Fraud, Risk, Product, Technology, Sales, Marketing, Legal, and Compliance—to align analytics with business goals and support cross‑functional initiatives.
  • Communicate complex analytical concepts and findings to non‑technical stakeholders effectively.
  • Build and maintain strong relationships with internal stakeholders.

• Data Analysis & Insight Generation:
  • Connect business problems with data to produce insightful, data‑driven analysis.
  • Leverage analytics and risk models to drive operational improvements in areas such as fraud detection and customer onboarding.
  • Analyze portfolio behavior to identify anomalies, emerging trends, drop‑off points, and areas for improvement across customer funnels.
  • Conduct root cause analysis on performance issues and fraud events to uncover underlying causes and continuously improve coverage and efficiency.
  • Identify proxy variables or creative data substitutes when ideal data is not available.
• Reporting & Dashboard Development:
  • Design and maintain dashboards and analytical tools that track overall business performance, including DCA metrics (e.g., approval rates, automation rates, conversion trends) and fraud performance (e.g., fraud loss performance, rule efficiency, alert‑to‑case conversion rates) over time.
  • Monitor system KPIs, evaluate performance trends, and recommend improvements.
  • Deliver insights to the organization that optimize revenue and risk.
• Strategy & System Optimization Support:
  • Support the implementation of data‑driven strategies that transform processes to enable efficiency and scale.
  • Contribute to optimizing fraud detection systems to capture fraud and minimize customer disruptions.
  • Collaborate with Data Scientists to support the building and operationalization of machine learning models to solve risk problems and enhance fraud detection.
  • Assist in incorporating external threat intelligence and business context into strategic recommendations.
• Cross-Functional Collaboration & Communication:
  • Partner across internal stakeholders—including Fraud, Risk, Product, Technology, Sales, Marketing, Legal, and Compliance to align analytics with business goals and support cross‑functional initiatives.
  • Communicate complex analytical concepts and findings to non‑technical stakeholders effectively.
  • Build and maintain strong relationships with internal stakeholders.