Fraud Strategy Lead (Credit Card & DDA)
Team: Risk / Underwriting
Location: Remote / USA
Commitment: Full-time
Workplace Type: remote
Salary:
✅ What You’ll Do
- Program build: Design and stand up our multi‑layer fraud stack (application, account opening/funding, account takeover, transaction monitoring, disputes/chargebacks).
- Vendor strategy: Select, integrate, and tune identity, device, behavioral, and transaction‑risk providers; negotiate and measure ROI.
- Decisioning & analytics: Develop rules, features, and models; define thresholds to control false positives/negatives; run A/Bs and champion‑challengers.
- Data & signals: Operationalize bureau, banking, PII, device/IP, email/phone, telco, velocity, and network signals into a single decisioning framework.
- Program Quality & performance: Monitor precision, capture rate, approval impact, and loss basis points; calibrate and backtest.
- Cross‑functional execution: Partner with Product, Engineering, Data, Ops, and Compliance (KYC/AML, FCRA/GLBA, Reg E/Reg Z).
- Guide dispute strategy to minimize friendly/first‑party abuse.
⚡️What Makes You a Great Fit
- Identity / synthetic detection: SentiLink, Socure, LexisNexis Risk Solutions/ThreatMetrix, Experian CrossCore, Equifax/Kount, TransUnion TruValidate, Ekata (Mastercard), IDology.
- Document & biometric IDV: Onfido, Jumio, Veriff.
- Device / IP / reputation: Fingerprint (FingerprintJS), iovation/TruValidate, ThreatMetrix, MaxMind, IPQS, Arkose Labs.
- Banking & income data: Plaid, Finicity, Argyle, Pinwheel.
- Decisioning & case management: Alloy, Unit21, Sardine, Sift, Feedzai, Featurespace, FICO Falcon, Actimize, SAS FMS (examples).
- Network tools (issuer): 3‑DS 2.x, Visa/Mastercard issuer risk tools.
- Experience with graph/network features, device clusters, and behavioral biometrics.
👀 What We’re Looking For (requirements)
- 7+ years in issuer‑side fraud for cards and/or DDA/neobank (experience on the Consumer and Commercial side is a definite plus).
- Demonstrated build‑from‑scratch experience: stood up a new fraud stack or materially re‑platformed one.
- Hands‑on with SQL and practical Python/R for feature/rule prototyping and performance analysis.
- Depth in 1st‑party vs 3rd‑party vs synthetic patterns (e.g., bust‑out, thin‑file synths, ATO).
- Proven track record balancing loss bps versus approval rate and customer friction.
- Vendor evaluation and commercial ownership (pricing, SLAs, monitoring, deprecation).
- Comfort working independently; can own roadmap, write PRDs/specs, and ship with engineers.
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