Senior Fraud Lead - Payment Experience
Thomson ReutersRemotePosted 9 April 2026
Job Description
Senior Fraud Lead - Payments Experience
Thomson Reuters is seeking a Senior Fraud Lead to own and scale its enterprise-wide fraud monitoring and risk control program across digital commerce, subscription billing, refunds, and dispute management. This is a high-visibility, strategic-and-hands-on leadership role sitting within the Payment Experience function.
The successful candidate will serve as the primary fraud Subject Matter Expert (SME) for the organization — designing detection models, owning platform configuration, driving governance, and providing executive-ready risk narratives to senior leadership and audit forums. You will be the single accountable owner for fraud strategy and operations across Thomson Reuters' global eStore and billing ecosystem, spanning Stripe (Radar, Disputes), CyberSource (Decision Manager), and emerging payment channels.
This role offers the opportunity to build and mature a newly centralized fraud function from a strong foundation — fraud losses were reduced by 95% in FY2025 — and to shape its next-generation capabilities across a multi-year roadmap aligned to ORC (Operational Risk Committee) mandates.
About the Role:
1. Fraud Risk Strategy & Program Ownership
Own the end-to-end Fraud Monitoring Strategy across all channels: eStore (DCP and legacy), guest checkout, agent-assisted payments, billing, renewals, refunds, and dispute lifecycle.
Define and maintain the fraud risk appetite , control objectives, and escalation thresholds in alignment with the Operational Risk Committee (ORC) and Enterprise Risk Management Framework.
Develop and execute the fraud tooling and capability roadmap , including rule framework enhancements across Stripe and CyberSource, and integration of fraud signals with internal data platforms.
Proactively identify and respond to emerging fraud typologies including card testing attacks, account takeover (ATO), refund abuse, synthetic identity fraud, and social engineering via agent-assisted flows.
Design, develop, and optimize fraud detection models using machine learning, behavioral analytics, and anomaly detection techniques.
Leverage Thomson Reuters CLEAR and Fraud Detect platforms — including public records, device authentication, and identity verification data — to surface patterns indicative of fraud, waste, and abuse.
2. Platform Ownership — Stripe & CyberSource (Hands-On)
Serve as primary platform owner and SME for:
Stripe Radar — custom rule authoring, adaptive acceptance, blocklists/allowlists, risk signal configuration, and rule tuning
Stripe Disputes & Chargeback tooling — workflow configuration, evidence management, response SLA monitoring
CyberSource Decision Manager — risk profiles, rule logic, and decision flow optimization
Design and tune advanced fraud controls including:
Velocity and burst detection
BIN / issuer-country and geo mismatch controls
Device and IP reputation strategies
Refund and dispute abuse detection
New account and new card spend threshold controls (72-hour risk windows)
Partner with Product and Engineering to implement:
3DS / EMV 3DS routing strategies across DCP eStore channels, aligned to Visa Secure, Mastercard Identity Check, and AMEX SafeKey standards
Risk scoring thresholds that balance authorization approval rates with fraud loss objectives
Usage caps and automated alert workflows for new account onboarding risk
3. Fraud Monitoring, Investigations & Incident Response
Oversee ongoing fraud monitoring operations across all channels: DCP/eStores, Agent-Assisted Guest Pay, Billing/Collections (Pay-by-Link), and subscription billing.
Lead investigation of high-severity fraud incidents including root cause analysis, containment, and control remediation.
Own and operate the fraud incident lifecycle: Detection → Containment → Remediation → Post-Incident Review.
Act as the escalation point for Security, Legal, Compliance, and Finance for major fraud events exceeding ORC escalation thresholds (e.g., financial ... (truncated, view full listing at source)
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