- The incumbent would functionally contribute as an SME to the Unsecured Lending Credit Risk team and lead large and complex projects.
- Provides credit risk governance across assigned a specific business or functional role. Leads significant initiatives and processes, and partners with line of business management to drive the company credit culture, appetite, and business performance. Acts as a subject matter expert for executive leadership on highly complex issues.
- 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 for 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.
- 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. Expert in statistical software such as SAS, SQL, Python, E-miner, among others.
- Develops quantitative/qualitative models for forecasting losses in supporting portfolio planning, loan loss provisioning, or new account acquisitions. May provide input for CCAR, Basel and other regulatory submissions.
- Develop complex programming models to extract data and/or manipulate databases such as ORACLE, Teradata.
- 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.
- 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.
- Leads implementation of complex initiatives with moderate to high risk for the line of business
- Lead project teams and may mentor but does not manage other team members.
- To be effective in this position, you will need to have a deep understanding of credit from an acquisition’s perspective, a broad and strategic perspective on risk management, practice in the test and learn discipline for strategy development, and be fluent in both the key technical tools of credit risk decisioning and sound credit judgment.
- Over all experience around 10+ years in similar role with at least 7 years of unsecured lending experience in analytic functions
- Bachelor’s degree or higher in a quantitative field such as applied mathematics, statistics, engineering, finance, economics, econometrics or computer sciences
- Experience in credit risk analytics
- Advanced SAS, Macros knowledge, R, Python
- Advanced degree in statistics/finance /engineering/other quantitative disciples
- Strong Knowledge of MS Office Tools / Segmentation Tools / Decision Trees
- Strong technical skills and problem-solving skills
- A strong track record and business knowledge in the financial services sector with a deep understanding of credit card credit or fraud risk from a full-cycle perspective, including testing and control within a large financial institution.
- Experience working horizontally across the organization.
- Strong operational and execution skills, with keen attention to detail.
- Masters in a Quantitative or Advanced Analytics discipline