Head of Fraud Detection

India; Netherlands; Singapore, Central, Singapore

As the Head of Fraud Detection, you will be at the forefront of protecting Aspire and its customers from fraud. This role is laser-focused on the continuous development, tuning, and optimization of our fraud detection systems. You will be the go-to expert for our rules-based engines and machine learning models, ensuring they are not only effective but also efficient. Your primary objective will be to enhance our detection capabilities to proactively identify and mitigate emerging fraud threats while supporting Aspire's rapid global expansion. You will define and execute the vision for Aspire’s fraud detection framework, ensuring its alignment with both regulatory landscapes and our strategic growth.

Key Responsibilities:

• Own Detection Systems: Take complete ownership of the performance and strategy for our fraud detection rules and models.
• Rule and Model Lifecycle Management: Design, implement, test, and deploy new fraud detection rules and machine learning models. Continuously monitor their performance and iterate to improve efficacy.
• Effectiveness and Efficiency Metrics: Be accountable for and actively drive improvements in key detection metrics, including:
  • Transaction Detection Rate (TDR)
  • Account Detection Rate (ADR)
  • Value Detection Rate (VDR)
  • Alert False Positive Rates
• Fraud Loss Metrics: Directly influence and take ownership of critical financial fraud metrics, including customer and Aspire fraud losses.
• Strategic Roadmap: In collaboration with product and data science teams, define and drive the roadmap for our fraud detection systems. This includes prioritizing new data sources, model enhancements, and rule logic to counter evolving fraud typologies.
• System Optimization: Continuously refine detection thresholds and model parameters based on data-driven insights from fraud investigations, quality control findings, and business feedback to minimize false positives and enhance detection accuracy.
• Innovation in Detection: Champion the integration of advanced AI/ML, automation, and predictive analytics to evolve our fraud prevention toolkit beyond traditional methods.
• Cross-functional Partnership: Act as the subject matter expert on fraud detection, collaborating closely with Fraud Operations, AML, Compliance, and Product teams to embed robust, automated fraud prevention measures into our products and workflows.
• Team Leadership: Lead and mentor a specialized team on the technical aspects of fraud detection, fostering a culture of innovation, data-centric decision-making, and precision.

Minimum Qualifications

• Experience:
  • Minimum of 7 years of hands-on experience in fraud management within a FinTech or regulated financial institution.
  • A proven track record of designing, building, and scaling fraud detection systems, with demonstrable expertise in rule writing within rules-based engines and the implementation of machine learning models.
  • Experience in designing and securing customer journeys is highly advantageous.
• Technical Knowledge:
  • Deep understanding of fraud detection tools and platforms (e.g., Sardine, ThreatFabric, Feedzai, Riskshield).
  • Strong familiarity with the underlying data architecture required for effective fraud detection and monitoring.
• Skills:
  • Excellent problem-solving abilities, with a knack for breaking down complex and ambiguous issues into structured, actionable solutions using a first-principles approach.
  • Hands-on proficiency in designing, implementing, and testing detection rules and logic.
  • Exceptional analytical skills, with a proven ability to leverage data to drive insights and tangible improvements in detection systems.
  • Proficiency in SQL is essential. Experience with Python or R for data analysis and model development is highly desirable.
  • Strong communication skills (both written and verbal) with the ability to articulate complex technical concepts to diverse audiences in a simple and effective manner.