Data Analysis Expert for Financial Crime Prevention

6 hours ago


Stockholm, Stockholm, Sweden SEB group Full time

The Financial Crime Prevention function at SEB Group is accelerating the deployment of advanced financial crime prevention capabilities to continuously meet regulatory expectations and become a leader in fighting financial crime. The Financial Crime Prevention function encompasses Fraud Prevention, Anti-Money Laundering (AML) transaction monitoring, sanctions, and customer screening.

The Transaction Monitoring unit within the Financial Crime Prevention function is seeking a skilled professional to ensure the work to further enhance SEB Group's Transaction Monitoring scenarios and provide appropriate risk coverage to identified risks for the Group. This role can be based in Stockholm or Riga.

About the Role

The primary objective of this position is to aid in the development of SEB Group's TM risk coverage and detection capabilities to continuously meet regulatory expectations and ensure that SEB becomes a market leader in the fight against financial crime.

Key Responsibilities:

  • Analyze financial crime datasets to detect abnormalities, patterns, and trends associated with money laundering and other illicit activities;
  • Develop interactive dashboards and visualizations using Tableau;
  • Conduct root cause analysis on flagged transactions or customer activity to identify vulnerabilities;
  • Assist management with providing reports using data from the dataset according to set requirements;
  • Contribute to data quality improvements;
  • Work on defining new TM scenario requirements and TM scenario change management based on identified gaps in the Business Warning & Reporting Area (BWRA), including continuously aligning with the BWRA for new risks and gaps identified outside of the BWRA's yearly cycle;
  • Act as the subject matter expert in collaboration with development organizations, working with change management, scenario optimization, and deployment of new or changed TM scenarios;

Requirements:

  • Academic degree in Finance, Business, Law, Mathematics, Data Engineering, IT, or equivalent;
  • At least 2 years of experience working with data analysis, including strong skills in data transformation using tools like Excel and SQL;
  • Proficiency in data visualization tools such as Tableau, Power BI, or QlikView;
  • Experience with Python (considered a strong advantage);
  • Familiarity with Transaction Monitoring, Scenario Development, and Change Management utilizing Advanced Analytics and AI/ML techniques (considered an advantage);


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