The Fraud Risk Analytics is part of the Consumer Banking Risk Management and Fraud Center of Excellence (COE) team within Consumer and Community Banking Risk. This team is responsible for analysis related to various fraud mitigation strategies. As a Fraud Risk Strategy Analytics Associate within our Risk Management team, you will have the opportunity to analyze emerging fraud and scam trends, develop new fraud fighting products, and work with cross-functional teams. You will leverage your strong analytical and problem-solving skills to interpret large amounts of data and its impact in both operational and financial areas. This role provides an opportunity to develop creative solutions to challenges presented by fraud activity and to contribute significantly to our risk management efforts. Responsibilities: Develop and maintain periodic analytics to provide management with full insight into emerging trends and the quality of the originated accounts Attain a detailed understanding of key performance metrics and profitability drivers, enabling the delivery of insights encompassing the full account lifecycle Acquire an understanding of the operational processes (e.g. manual underwriting, portfolio management, collections) which will aid in understanding acquisition performance drivers Conduct ad hoc analytics and contribute to various projects representing Risk Management Required qualifications, capabilities and skills 4+ years of professional experience, experience in risk management, strategic analytics, or data science required. Strong analytical, interpretive and problem solving skills with the ability to interpret large amounts of data and its impact in both operational and financial areas Strong written and verbal communication skills and ability to interact with all levels of the organization is required with the ability to storyboard along with the ability to defend storyboard position Ability to develop elegant and common-sense solutions to complex business challenges Strong knowledge of programming language like: Python, SAS, R and SQL Proficient in Excel & PowerPoint Preferred qualifications, capabilities and skills 2years of experience in Fraud risk roles preferred Experience with Fraud Wrongdoers, Mules and 1st party fraudsters/ID theft Strong P&L knowledge and understanding of drivers of profitability Demonstrated experience with data analysis, designing & analyzing experiments, and Modeling A bachelor's degree in Finance, Accounting, Economics, Statistics or equivalent work experience preferred
