Fraud Analytic/Fraud Strategy Role - Credit Risk Team - Credit Card Domain (3-12 yrs)
About this role:
The Consumer Credit team is responsible for leading, developing and implementing strategic initiatives and processes to drive the company credit culture, appetite, and business performance. The team is seeking a highly motivated and talented individual to be part of the Consumer Lending Credit Risk team.
Primary role is to apply strong business knowledge and advanced analytical skills to solve business questions, think out-side-of-the-box and develop innovative yet practical risk management strategies impacting the bottom line of the business. An individual who is results driven, goal oriented, and enjoys a fast-paced working environment will find this opportunity both challenging and exciting.
- This would primarily be in a IC/Lead Role supporting Transaction and Authorization Fraud process for business cards
- The incumbent would functionally contribute as an SME/Lead to the Consumer Lending Credit Risk team and execute relatively large and complex projects with moderate to high risk for the line of business.
- Leads significant initiatives and processes, and partners with line of business management to drive the company credit culture, appetite, and business performance with inputs from senior leadership. Acts as a subject matter expert for senior leaders.
- Assesses and predicts risk and performance through business analysis and/or modeling. Establishes effective policies, processes, and tools to identify and manage risks. Uses predictive sciences for developing future ready solutions.
- Leads or assists in development of predictive strategies / solutions across customer life-cycle, for example new account acquisitions across underwriting, approve/decline, limit assignment, business rules development, product development support. Analyzes big data and understand / monitor trends to provide actionable insights across a range of risk analytics initiatives.
- Develops comprehensive monitoring frameworks and dashboards and provide statistically sound diagnostic evaluation of any emerging or unexpected risk areas to enhance intelligence and facilitate faster decision making.
- Reports on asset quality, portfolio trends, credit policy exceptions across various credit, vintage, product, offer, channel, industry segments using visualization tools such as Excel VBA, Tableau and/or SAS Visual Analytics.
- Develop new and enhance existing models for managing fraud risk, payment risk, credit bust outs, credit abuse. Evaluate new data sources and attributes, internal and external from extensive case reviews for efficacy in models.
- Builds risk rating methodologies using advanced analytics approaches including statistical modeling and machine learning techniques, not limited to Random Forest, Decision Trees, Segmentation, and/or Time-series modeling.
- Develops quantitative/qualitative models for forecasting losses in supporting portfolio planning, loan loss provisioning, or new account acquisitions.
- Develop complex programming models to extract data and/or manipulate databases such as ORACLE, Teradata.
- Ensures resolution of matters requiring attention (MRA) from outside regulators, Audit, Corporate Model Risk or internal review teams. May partner with other business units, Audit, Legal, regulators, and industry partners on risk related topics.
- To be effective in this position, you will need to have a good understanding of credit, practice in the test and learn discipline and exploratory analysis, and be fluent in both the key technical tools of credit risk decisioning and sound credit judgment.
- Bachelor's degree or higher in a quantitative fields such as applied mathematics, statistics, engineering, finance, economics, econometrics or computer sciences
- 7+ years of progressive experience in credit and risk analytics roles
- Hands on Experience in at least one area in credit risk analytics - credit strategy / modeling techniques / Forecasting techniques / data architecture & management
- Detailed understanding of risk domain; Strong Risk analytics skills and understanding of P&L, drivers
- Expertise in few programming and statistical packages - SAS, SQL, VBA, Macros, R, Python, E-miner, Tableau, SAS VA
- Knowledge of advanced statistical tools such as Segmentation Tools, Decision Trees, Clustering, Regression, and other statistical modeling and/or Machine Learning techniques
- Ability to lead project teams and coordinate with multiple stakeholders.
- Strong analytical skills with ability to turn findings into executable plans to meet business objectives
- Ability to identify and evaluate trends, isolate root cause, and provide swift/thorough resolution
- Advanced degree in statistics/finance /engineering/economics/other quantitative disciplines
- Knowledge and understanding of (consumer and small business loan) credit card lending practices, policies, procedures, and key drivers impacting credit offerings
- Ability to contribute to strategic decisions and coordinate with multiple stakeholders. Develop consensus and gain buy-in for strategic priorities
- Strong project management skills with ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment
- Strong ability to develop partnerships and collaborate with other business and functional area