Fraud Strategy Manager

About the job Fraud Strategy Manager

Role Summary

In this role, you will be involved in the First Party Fraud / Credit Abuse Strategy team for a leading US bank focusing on end-to-end delivery of analysis and seamless execution by collaborating with cross-functional teams. You will get an opportunity to derive insights from large complex datasets and impact business decisions through data-based findings.

Responsibilities

• Design & Implement data driven First Party Fraud/ synthetic frauds strategies, credit abuse.
• Generate and automate regular reports and dashboards for fraud-related KPIs, offering actionable insights for Senior management.
• Analyze transaction data and customer behavior to identify early warning signs of fraud and proactively address vulnerabilities.
• Identification of potential check and deposits fraud - activity related to checks, such as forged checks, counterfeit checks
• Independently address complex problems and share insights from data analysis that integrate with initial hypothesis and business objective
• Comfortable working with large datasets, including managing large number of data sources, analyzing data quality, and pro-actively working with client's data/ IT teams to resolve issues
• Reformulate highly technical information into concise business presentations
• Create presentations and reports based on recommendations and findings

• Bachelor's or master's degree in mathematics, statistics, economics, computer engineering or analytics related field
• 4+ years of consulting, analytics delivery experience in Fraud, Disputes, operations and exposure to credit card & retail banking domains
• Hands-on experience with SAS/SQL and Microsoft Office
• Excellent communication, presentation and story building skills
• Strong analytical skills with the demonstrated ability to research and make decisions based on the day-to-day complex customer problems

• Ability to adapt to emerging analytic tools and solutions into standard operating procedures
• Knowledge of basic machine learning algorithms like decision trees, regression models and clustering
• Expertise in fraud application loss mitigation on cards portfolio