Risk Analyst (SQL), Card Payment Fraud

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

About the RoleWe are seeking a detail-oriented and proactive Risk Analyst ( KYC Fraud Prevention & Compliance Rule Analysis) to join our Risk Management team. In this role, you will be responsible for using rules/ML models/AI to a) detect and prevent fraudulent activities related to onboarding processes and existing user accounts; and b) leverage risk team data insights to support co-prevention scope for compliance TS/TM direction. You will play a key role in protecting our platform’s integrity, ensuring compliance with KYC (Know Your Customer) regulations, and safeguarding our users’ assets.

Responsibilities: : Real-time transaction monitoring: Monitor card authorization flows and flag suspicious activity across debit/credit card portfolios. Fraud rule strategy: Design, test, tune, and deploy fraud detection rules and risk scoring strategies at the authorization (auth) decision point — balancing fraud capture rate against false-positive / decline rates. Investigation & case management: Investigate suspected fraud cases (account takeover, counterfeit/cloned cards, stolen card, CNP fraud, first-party/friendly fraud), determine root cause, and take action (block, step-up, decline). Loss & performance analysis: Track fraud losses, chargeback rates, approval rates, and key risk KPIs; produce dashboards and reporting for management. Chargeback & dispute support: Work with dispute/chargeback teams on fraud-related chargebacks and network (Visa/Mastercard) reason codes. Cross-functional collaboration: Partner with product, engineering, data science, and compliance to improve fraud models, tooling, and controls. Emerging threat detection: Stay ahead of evolving fraud typologies, BIN attacks, enumeration/testing attacks, and organized fraud rings.

Requirements: : 3+ years in card payment fraud risk, ideally on the issuer or card processor / issuer-processor side. Solid understanding of the card payment lifecycle: authorization, clearing, settlement; the roles of issuer, acquirer, card network (Visa/Mastercard), and processor. Familiarity with authorization message flows (ISO 8583), auth/decline codes, AVS, CVV, and 3-D Secure (3DS) / SCA. Working knowledge of fraud typologies: card-not-present (CNP) fraud, account takeover (ATO), counterfeit/cloned cards, lost/stolen, BIN attacks, card testing/enumeration. Experience with fraud detection / rules engines (e.g., Falcon, SAS, Feedzai, Featurespace, or in-house platforms). Strong data analysis skills: SQL required; ability to interrogate transaction data and quantify fraud/risk trade-offs. Understanding of chargeback lifecycle and network dispute reason codes.

Nice to have:: Experience tuning real-time authorization rules and measuring fraud vs. false-positive trade-offs. Exposure to machine learning fraud models and feature engineering for risk scoring. Crypto card experience: familiarity with crypto-linked cards and crypto-to-fiat settlement at auth. Knowledge of PCI-DSS and relevant regulatory/compliance requirements. Industry certifications (e.g., CFE — Certified Fraud Examiner).