Fraud Prevention Strategy Owner
Responsibilities
You are responsible for mitigating fraud across all outgoing payment rails, including card payments and money transfers.
Rail
Channels
Typologies in scope
Card rails
Debit card on Mastercard and Shazam, ATM, digital wallets
Card-not-present, counterfeit and skimming, lost/stolen, card testing, ATM cash-out, wallet token fraud, stand-in exposure
Money movement rails
ACH (outbound and inbound), P2P claim-link sends, push and pull via card rails
Unauthorized transfers, authorized push payment scams, ACH return and kiting abuse, beneficiary-add fraud, balance drain
Both
Account opening, login, profile changes
Account takeover, synthetic identity, first-party fraud, mule accounts used to cash out fraud
Rule lifecycle
Own the full rule book on our fraud risk management (FRM) platforms
Respond to an emerging fraud pattern within 24 hours of detection: diagnose, deploy a containment rule, and document the change.
Run every rule change through a documented process: hypothesis, back-test or shadow mode, expected alert volume, approval, deploy, post-change review.
Keep a rule inventory with owner, rationale, last-tuned date and performance for each rule
Own the bank's rule approval workflow and change log
Analytics and models
Monitor transaction, login and payment data daily to spot new attack patterns before losses build.
Use SQL/Python to size losses, back-test rules and measure the false-positive cost of every control.
Apply ML and AI tools (anomaly detection, clustering, LLM-assisted alert triage)
Operations
Prioritise the fraud roadmap by fraud exposure, friction to good customers and operational cost, and defend the trade-offs with data.
Partner with the operations team on the disputes related to fraud
Own the rule playbooks in the fraud analyst SOP and close the feedback loop from analyst outcomes into rule tuning; the Fraud Ops Lead owns the queue, SLAs and card actions.
Automate repetitive review and reporting work so analyst time goes to judgment calls.
Lead fraud incident response: contain, quantify, communicate, and write the post-mortem.
Feed confirmed fraud and dispute outcomes into Reg E dispute handling and chargeback recovery.
Experience and Qualifications
6+ years in fraud strategy or fraud analytics at a US bank, card issuer, aquirer, neobank or payments company.
Hands-on rule authoring in a production fraud rules engine, vendor (Featurespace, Feedzai, SAS Fraud Management, FICO Falcon) or in-house.
Proven track record cutting fraud losses without a matching rise in false positives, with numbers to show it.
Strong SQL and working Python; comfortable building your own back-tests and dashboards without waiting on a data team.
Working knowledge of US payment rails and their fraud patterns: card networks, ACH (Nacha rules), and real-time or P2P payments.
Working knowledge of Reg E error-resolution obligations for card and electronic fund transfers.
Practical use of ML or AI in fraud: you have shipped, tuned or retired a model-driven control, not just read about one. You also use AI tools daily to automate analysis and manual workflows.