Director, Fraud Strategy & Analytics (United States)
We are looking for a Director of Fraud Strategy and Analytics to own end-to-end fraud strategy, analytics, and risk operations across our subprime consumer lending portfolio. In this role, you will build and run the fraud function at ADF. You will set the fraud risk appetite, stand up the operating rhythm, govern policies and rules, and own the feedback loop with manual review, IDV exceptions, disputes, chargebacks, ACH returns, provisional credit, and recoveries. You will balance loss mitigation against approval rates, unit economics, and customer experience. You will also be the senior fraud partner to the revenue, product, credit/risk, data engineering, and compliance teams, as well as executive leadership. This is a builder role in a lean, fast-moving, and ambiguous environment. We're looking for a curious, enterprising, hands-on leader who thinks differently. You can write code and pull your own data, and you're energized by owning a function end-to-end and managing a smart, nimble team remotely. Key Responsibilities: Fraud Strategy Roadmap: Owns and evolves 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. Fraud Risk Appetite & Framework: Defines and maintains 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; aligns framework to enterprise risk and audit expectations. Policy, Rule & Decisioning Governance: Governs 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. Portfolio Fraud Monitoring: Directs portfolio fraud monitoring and operating rhythms—loss rates, capture rates, false-positive rates, approval and funding impact, vintage and segment KPIs, disposition mix—and drives timely action when performance drifts. Fraud Model & Scorecard Oversight: Oversees fraud model and scorecard performance (PSI, score drift, KS, decay, gain/lift, override rates) and the cadence for recalibration, rule adjustment, and escalation; partners with data science on model strategy, but leads the strategy, deployment, and monitoring layer. Emerging Threats & Fraud Ring Detection: Sets the agenda for emerging fraud trends, ring, and cross-channel vulnerability detection, including graph and link analysis, velocity signals, and consortium intelligence; ensures findings are sized, prioritized, and translated into rule, policy, and operational responses. Third-Party Signal Strategy: Leads 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. Fraud Risk Operations Ownership: Manage the interface between fraud strategy and risk operations—queue design, override governance, manual review, IDV exceptions, disputes, chargebacks, ACH returns, provisional credit, and recoveries; translates investigator insight into rule, policy, staffing, and reporting changes. Data & Platform Partnership: Partners with product, data engineering, and decisioning platform teams to evolve fraud data sources, feature stores, decision engine capabilities, and monitoring infrastructure; represents fraud strategy in cross-functional prioritization. Test-and-Learn Standard: Defines 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. Regulatory & Compliance Alignment: Ensures 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 Red Flags Rule—and partners with Compliance, Legal, BSA, and Internal Audit; supports SAR narratives, regulatory exams, and audits. Executive Interactions: Produces and presents 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. External Representation: Serves as the senior fraud strategy expert for the company; represents fraud strategy externally with vendors, consortia, industry working groups, and law enforcement partners. Team Leadership: Leads, coaches, and grows the fraud strategy and analytics team (strategists, analysts, and data scientists); sets priorities, performance expectations, hiring plans, and career paths. Performs other duties as assigned. Required Qualifications: Education & Experience: 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). Must include prior ownership of a fraud strategy and analytics function end-to-end, with measurable improvement in fraud loss, approval rates, and customer experience. Consumer-Lending Fraud Experience (Non-Negotiable): Direct fraud strategy experience in unsecured personal loans, ideally in near-prime/subprime installment, BNPL, or similar high-fraud-risk consumer credit. Skills & Competencies: Builder / Start-Up-Ready Operator (Non-Negotiable): Demonstrated experience building or materially upgrading a fraud function—not just running one at a large bank. Comfortable with ambiguity, gaps in tooling, and doing the work yourself when needed. Track record of self-initiated projects—tools built, analyses run, functions stood up—without waiting for structure or headcount. Operating Credibility (Non-Negotiable): Can walk into an unfamiliar consumer-loan portfolio and articulate a credible first-90-day plan covering fraud strategy, risk operations, and the servicing interface. Typology Depth: Deep understanding of fraud typologies in consumer lending, as listed under Key Responsibilities, and how they manifest across application, funding, and account data. Model & Scorecard Fluency: 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. Hands-On Analytical Skills: 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). Comfortable using AI to run analysis, generate insights and build presentations iteratively. Curiosity & Different Thinking (Non-Negotiable): Asks sharp, unprompted questions about the business, the portfolio, the data, and the customer. Comes to interviews with a point of view. Challenges assumptions constructively; connects fraud to credit, product, and unit economics. Decisioning Execution: Demonstrated experience driving policy, rule, and threshold changes through a decisioning platform end-to-end, including change control and monitoring. Risk Operations Track Record: Direct ownership or close partnership with a manual-review/IDV exception/disputes function, including staffing, SLA, and override design. Vendor Management: Experience evaluating and managing third-party fraud, identity, device, and consortium vendors, including commercial and performance trade-offs and contract negotiation input. Representative providers include Prove, Socure, Neuro-ID, LexisNexis, Ekata, SentiLink, and consortium data. Regulatory Knowledge: Working knowledge of US consumer lending fraud-adjacent regulation, as listed under Key Responsibilities, and experience partnering with Compliance, BSA, and Internal Audit. Executive Communication: Excellent executive communication; able to translate fraud analytics and trade-offs into recommendations for senior leadership, operations, and technical partners. Concise and evidence-backed, and comfortable presenting to the CEO/CRO and Board. Preferred Qualifications (Nice to Have): Advanced Analytics: Exposure to graph/network analysis for fraud ring detection, machine learning fraud models, and real-time decisioning platforms (e.g., Provenir, Taktile, Zoot, SAS, FICO Falcon, in-house engines). External Engagement: Established relationships with fraud consortia, industry working groups, and peer risk leaders. <
