Director of Fraud Risk Management

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of comprehensive fraud risk management for Flex’s credit card and DDA portfolio across both consumer and small business sectors.

• Examine patterns of acquisition and onboarding fraud, identity signals, document authenticity, synthetic identity indicators, and anomalies in approvals.

• Oversee the performance of KYC/KYB verifications and pinpoint any friction or control gaps.

• Track first-party fraud, third-party fraud, synthetic identity fraud, DDA-specific fraud vectors, and patterns related to authorizations and transactions.

• Manage analytical perspectives on disputes, chargebacks, friendly fraud, recovery rates, and the timing of loss emergence.

• Develop and sustain fraud detection frameworks to address emerging attack patterns.

• Integrate device, IP, identity, bureau, transaction, and behavioral data to uncover coordinated fraud rings and related anomalies.

• Conduct regular fraud risk assessments and present exposure implications to risk committees and senior leadership.

• Create fraud segmentation strategies to enhance detection tuning, policy interventions, and loss reserve calibrations.

• Collaborate with credit, legal and compliance, financial crimes, operations, and product teams.

• Aid in fraud-loss scenario analysis and stress testing initiatives.

• Act as the internal expert on fraud analytics, detection standards, taxonomy, and measurement frameworks.

• Report directly to the Chief Risk Officer as part of the Risk Management Leadership Team.

⛳️ Requirements

• 7–15 years of practical experience in fraud risk management, with direct responsibility for detection and loss management across consumer and small business products.

• Experience in both banking or regulated card programs and fintech is strongly preferred.

• Profound expertise in first-party, third-party, and synthetic identity fraud typologies.

• Capability to analytically differentiate fraud typologies in credit card and DDA contexts.

• Proficiency with device fingerprinting, IP intelligence, identity graph analysis, behavioral biometrics, velocity rules, and machine learning-based anomaly detection.

• Understanding of DDA fraud vectors, such as ACH origination and return abuse, check fraud, Reg E dispute dynamics, and the intersections of payment fraud/account takeover.

• Skilled in SQL and Python or R programming languages.

• Ability to formulate detection logic, conduct cohort analyses, and attribute losses from raw data.

• Familiarity with SAR filing thresholds, Reg E obligations, FCRA considerations related to adverse actions, and BSA/AML red flags.

• A senior-level perspective on emerging attack vectors and detection assumptions.

• Proficient in modeling the exploitation of products, policies, and verification weaknesses by bad actors.

• Strong quantitative aptitude along with the capability to identify and escalate shifts in loss or dispute patterns.

• Ability to convey complex fraud dynamics to risk committees, product teams, and senior leadership.

🏝️ Benefits

• Equity in the company in addition to base compensation.