Hr Center

Description Comprehensive Capital Analysis Review (CCAR) is a semi-annual US Federal Reserve regulatory submission. It is used to ensure that institutions have robust, forward-looking capital planning processes that account for their unique risks and sufficient capital to continue operations throughout times of economic and financial stress. As part of CCAR, the Federal Reserve evaluates institutions capital adequacy, internal capital adequacy assessment processes, and their plans to make capital distributions, such as dividend payments or stock repurchases. CCAR includes a supervisory stress test to support the Federal Reserve's analysis of the adequacy of the firms capital. Boards of directors of the institutions are required each year to review and approve capital plans before submitting them to the Federal Reserve. Being the Statistical modeler, the incumbent will be responsible for end-to-end responsibility of PPNR models (Statistical & Conceptual soundness) for a particular business / functions, sharing periodic updates to Senior Governance Group, presenting models to Federal Reserve / OCC / FDIC / Model Risk Management and align PPNR models with Citi's base operating plan. The detailed responsibilities includes: Development of econometric forecasting models for key Balance sheet and income statement line items for capital and business planning purposes. This includes the calculation of Net Interest Income (NII), Non Interest Revenue (Non-NIR), Interest Rate Exposure (IRE), Economic Value Sensitivity (EVS), and other associated interest rate risk metrics. Deep understanding of statistical techniques such as Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration. Steering stakeholder conversations with Businesses, Finance, Treasury and Risk to seek their sign-offs on Champion models. Manage the Segmentation, Risk Identification, overlay discussions with Businesses and Finance teams. Responsible for reviewing and timely submission of Model development documentation (MDDTs) for entire PPNR modeling landscape to Model Risk Management. Align with Model Risk Management on modeling and validation practices and have periodic check-ins with them. Create a culture of accountability and strict quality control of the data integrity and modeling process Develop and maintain a comprehensive modeling system that maintains consistent approach to