Job Views:  
4055
Applications:  34
Recruiter Actions:  18

Job Code

456368

AVP/VP - Comprehensive Capital Analysis Review

8 - 13 Years.Mumbai
Posted 7 years ago
Posted 7 years ago

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.

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 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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Job Views:  
4055
Applications:  34
Recruiter Actions:  18

Job Code

456368

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