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Fraud Risk Analyst x2

Northern Trust
Limerick, Ireland
On-site

About this role

About The Role

The Fraud Prevention Analyst role will be responsible for utilizing analytical skills and innovative strategies to detect, prevent, and report fraudulent activities at Northern Trust. This role will operate within a fast paced and dynamic global fraud team that is instrumental in protecting our clients against financial fraud.

Daily activities include, but are not limited to:

  • Utilize advanced data analysis techniques to detect and prevent fraud within client facing applications. Review comprehensive daily reports to identify anomalous patterns, transactions, or behaviors that may indicate unauthorized activity or fraud.
  • Review and verify login anomalies and suspicious transactions to identify or prevent policy violations, identity theft, and financial crimes by means of web-based and internal system research, coordinated efforts through cross-functional partnerships, client and internal partner notifications and interviews.
  • Analyze datasets from various sources and systems to identify and prevent potentially fraudulent activity. Research complex account movements that may involve multiple transaction channels, accounts, or client relationships.
  • Review and authenticate alerts generated by the Internal Fraud Detection systems. Validate transactions and activities using data from multiple sources. Escalate cases as needed to managers, HR and Fraud Investigations.
  • Leverage advanced skills and subject matter expertise to work independently, within an established fraud research and mitigation framework, to detect and respond to identity theft, scams and fraud risks appropriately and effectively.
  • Conduct thorough and well documented analysis, in accordance with policy and procedures. Consult with cross-functional departments to validate or invalidate suspicious transactions, and take appropriate proactive action to protect clients and the bank from additional fraud exposure.
  • Maintain the integrity of highly s

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