Job Description

Alexander Barnes is leading the search for a Head of Fraud Product for a global fintech operating across cards, bank payments, and digital accounts.

This hire will own the end-to-end fraud programme globally, building and scaling fraud prevention through product, engineering, data, and operations, embedded directly into each customer and payment flow.

Purpose of the role

This role owns fraud outcomes across the lifecycle. Detection, decisioning, intervention, and learning. From signal design to real-time controls to operational feedback loops.

To define and deliver a global fraud product strategy covering:

• Card fraud
• Bank and payment fraud
• Account Takeover

Key responsibilities

• Global fraud strategy: Define and drive the global fraud roadmap across cards, bank payments, and account access, aligned to business growth and risk appetite.
• Product and engineering delivery: Work directly with product and engineering teams to design, build, and ship fraud controls embedded into each product and flow.
• Detection and prevention: Develop real-time fraud detection and prevention capabilities using rules, signals, and ML models across multiple fraud typologies.
• End-to-end ownership: Own how fraud is identified, actioned, reviewed, and learned from across the full customer and transaction lifecycle.
• Data and model partnership: Partner with data science to shape model inputs, thresholds, precision/recall trade-offs, and ongoing performance monitoring.
• Operational integration: Build tight feedback loops with fraud operations so intelligence, outcomes, and emerging threats directly inform product improvements.
• Global scale and consistency: Ensure fraud controls scale across regions while remaining effective against local fraud patterns and behaviours.

Ideal candidates will bring

• Senior experience building fraud prevention in fintech, payments, or financial services.
• Direct exposure to card fraud, bank payment fraud, and account takeover.
• Proven experience delivering fraud controls through product and engineering, not policy alone.
• Strong understanding of ML-driven fraud detection and its real-world limitations.
• Comfort owning outcomes across multiple products and markets.
• Experience working closely with fraud operations, investigations, or risk teams.
• A data-led mindset with the ability to turn insights into shipped solutions.