Note: The job is a remote job and is open to candidates in USA. Applied Data Finance is seeking a Director of Fraud Strategy and Analytics to oversee the fraud strategy and analytics for their subprime consumer lending portfolio. This role involves developing the fraud strategy roadmap, managing a team, and collaborating with various departments to ensure effective fraud risk management.
Responsibilities
- Own and evolve fraud strategy across application, funding, and account/post-book fraud — covering identity, synthetic, first-party, third-party, account takeover, bust-out, never-pay, credit washing, mule/APP scams, and income/employment misrepresentation — balancing loss reduction with approval rates, conversion, funding, and customer experience to meet portfolio-level KPIs
- Define and maintain the fraud risk management framework, including fraud risk appetite (e.g., net fraud loss bps, fraud/AR ratio, first-payment-default fraud rate), tolerances, and escalation triggers; align the framework to enterprise risk and audit expectations
- Govern fraud policy, rules, and decisioning thresholds end-to-end — standards for proposal, review, approval, deployment, monitoring, retirement, and change control — with clear sign-off across risk, compliance, and operations
- Direct portfolio fraud monitoring and operating rhythms — loss rates, capture rates, false-positive rates, approval and funding impact, vintage and segment KPIs, disposition mix — and drive timely action when performance drifts
- Oversee fraud model and scorecard performance (PSI, score drift, KS, decay, gain/lift, override rates) and the cadence for recalibration, rule adjustment, and escalation; partner with data science on model strategy, while leading the strategy, deployment, and monitoring layer
- Set the agenda for emerging fraud trends, ring, and cross-channel vulnerability detection, including graph and link analysis, velocity signals, and consortium intelligence; ensure findings are sized, prioritized, and translated into rule, policy, and operational responses
- Lead third-party fraud and identity signal strategy — KYC/CIP, identity verification, device intelligence, behavioral biometrics, consortium data, bank/transaction data, income/employment verification, and credit bureau fraud alerts — including vendor evaluation, benchmarking, commercial negotiation input, and onboarding/retirement decisions
- Partner with fraud operations to align real-time monitoring, queue strategy, SLA management, and case outcomes with analytics; convert investigator insight into rule, policy, staffing, and reporting changes
- Partner with product, data engineering, and decisioning platform teams to evolve fraud data sources, feature stores, decision engine capabilities, and monitoring infrastructure; represent fraud strategy in cross-functional prioritization
- Define the test-and-learn standard — champion/challenger, policy backtests, holdouts, and A/B tests — to quantify the impact of strategy changes on fraud, approvals, funding, and downstream credit performance
- Ensure fraud strategy is aligned with applicable US consumer lending regulations and guidance — including Regulation E, Regulation Z, FCRA, GLBA, UDAAP, BSA/AML/KYC/CIP, OFAC, and the Red Flags Rule — and partner with Compliance, Legal, BSA, and Internal Audit; support SAR narratives, regulatory exams, and audits
- Produce and present executive-level fraud reporting and deep dives — loss attribution, typology trends, decisioning outcomes, false-positive and approval trade-offs, and strategic options — for senior leadership and the Board/Risk Committee
- Serve as the senior fraud strategy expert for the company; brief executives, support audits and regulatory reviews, and represent fraud strategy externally with vendors, consortia, industry working groups, and law enforcement partners
- Lead, coach, and grow the fraud strategy and analytics team (strategists, analysts, and data scientists); set priorities, performance expectations, hiring plans, and career paths
Skills
- Bachelor's degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, Engineering, or related); advanced degree a plus
- 10+ years in fraud strategy, fraud analytics, or fraud risk management in consumer lending, fintech, cards, or financial services, including 5+ years leading teams (managers and individual contributors)
- Track record of owning a fraud strategy and analytics function — setting strategy, defining risk appetite, governing policies and rules, and delivering measurable improvements in fraud loss, approval rates, and customer experience
- Deep understanding of fraud typologies in consumer lending — identity, synthetic, first-party, third-party, account takeover, bust-out, never-pay, credit washing, mule/APP scams, and income/employment misrepresentation — and how they manifest across application, funding, and account data
- Strong working knowledge of fraud models and scorecards — how they are built, evaluated, and monitored — with the ability to set strategy, interpret outputs (KS, PSI, gain, drift), and direct technical partners; hands-on model development not required
- Proficiency in SQL and at least one of Python or R for independent data pulls, validation, and rapid analysis; comfort in a modern data environment (cloud data warehouses, BI tools, feature stores)
- Demonstrated experience translating analytics into clear policy, rule, and threshold decisions and driving them through a decisioning platform end-to-end, including change control and monitoring
- Experience evaluating and managing third-party fraud, identity, device, and consortium vendors, including commercial and performance trade-offs and contract negotiation input
- Working knowledge of US consumer lending fraud-adjacent regulation — Reg E, Reg Z, FCRA, GLBA, UDAAP, BSA/AML, KYC/CIP, OFAC, Red Flags Rule — and experience partnering with Compliance, BSA, and Internal Audit
- Excellent executive communication; able to translate fraud analytics and trade-offs into recommendations for senior leadership, operations, and technical partners
Company Overview