We are seeking a highly analytical and detail-oriented Fraud Analyst to join our Client Service Operations team. The role focuses on identifying, investigating, and preventing fraudulent activities across banking products and digital platforms. The ideal candidate will have strong knowledge of U.S. financial regulations, fraud typologies, and data analysis tools.
Key Responsibilities
Fraud Detection, Alert Analysis & Case Management
- Review fraud alerts generated by surveillance systems to identify patterns, typologies, and emerging fraud schemes across payment channels (ACH, wire, card, crypto, etc.).
- Conduct detailed analysis of customer profiles, behaviors, and transactions to assess fraud risk indicators.
- Document findings clearly and escalate cases for further investigation when required.
- Collaborate with client Fraud Risk and Compliance teams to refine monitoring scenarios and thresholds.
- Recommend process enhancements to minimize false positives and strengthen detection capability.
Quality, Reporting & Process Improvement
- Ensure all alerts, investigations, and escalations meet quality standards and comply with documentation requirements.
- Partner with investigators, compliance officers, and data analytics teams to enhance investigative outcomes.
- Provide insights on fraud trends and contribute to management reports and dashboards.
- Suggest process improvements and contribute to risk mitigation strategies.
Qualifications & Experience
- Bachelor's degree required; concentration in Finance, Accounting, Criminology, Risk Management, or related field preferred.
- 35 years of experience in transaction monitoring, fraud risk management, or financial crime investigations, preferably within banking, fintech, or consulting/advisory firms.
- Familiarity with digital assets / crypto transactions is preferred.
Technical Skills & Knowledge
- Proficiency with transaction monitoring systems (Unit 21, Actimize, SAS AML, FIS, Oracle Mantas, or similar).
- Strong Excel and data analysis skills; ability to work with large datasets and identify anomalies.
- Knowledge of fraud typologies and detection techniques (account takeover, first-party fraud, mule accounts, social engineering schemes).
- Certifications such as CAMS, CFE, CFCS are a plus.
