As a part of the CCAR Team, the AVP/VP will manage all CCAR initiatives and submissions through data capture, consolidation, transformation, reconciliation and analysis. The responsibilities include:
- Development of econometric forecasting models for all significant balance sheet assets and liabilities for capital and business planning purposes. This includes the calculation of Net Interest Income (- NII- ), which is also referred to as Net Interest Revenue (- NIR- ), Interest Rate Exposure (- IRE- ), Economic Value Sensitivity (- EVS- ), and other associated interest rate risk metrics.
- Development, documentation and testing of product models needed as input to Financial Planning and Risk Management forecasts.
- Evaluate the impact on the product models of various scenarios used for Comprehensive Capital Analysis & Review (CCAR) submissions
- 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 data quality and modeling methods, audit, back test, tracking, annual validation. This is critical in reducing the model operating risk
- Coordinate COE FP&A activities for CCAR, including liaising with business units, risk and treasury
- Present stress test and other scenarios to corporate FP&A senior management
- Ability to build key relationships with finance and business teams
- Must be able to present technical matters in a way that is meaningful to the audience
- Highly motivated, participative team player with a change agent mentality that can provide leadership
- Ability to influence people and empower team members to be proactive and focused on partnerships and results
Qualifications
Other requirements:
- 9 - 12 years of relevant finance/business/accounting/statistical experience in financial services
- MBA/Masters in Economics, Finance, Accounting or related discipline
- Expertise in Stochastic Modeling Approaches, Modern Risk Management Theory and Modern Financial Theory
- Experience developing econometric and multivariate regression models. Good understanding of Seemingly Unrelated regression, Panel Data regression and Fixed effect models
- Extensive hands-on experience in programming and modeling using SAS
- Excellent presentation skills; the ability to translate complex financial schedules into meaningful presentations is critical; demonstrated analytical skills including the ability to synthesize quantitative and qualitative data to draw conclusions and assist on decision making
- Ability to build key cross functional and cross business relationships
- Must be able to present technical matters in a way that is meaningful to the audience
- Broad and deep understanding of accounting principles, investment, accrual products and corporate finance concepts
- Demonstrated leadership and team management skills and ability to managing multiple projects and deadlines
- Experience in model validation, documentation and tracking
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