The role is within the Loss / Loan Loss Reserve Forecasting and Stress Testing team. This group is specifically tasked with calculating and managing the net credit loss and loan loss reserve forecast on a $90BN + portfolio and working with the Finance teams to build forecasts for credit losses and loan loss reserves under varying macro-economic and business conditions. The individual will work on efforts around Comprehensive Capital Analysis & Review (CCAR/DFAST) for retail portfolios with primary focus on NA cards.
The individual should demonstrate strong work ethic, teamwork, quantitative and problem-solving skills. The individual is expected to leverage technical and business acumen to deliver high quality results. Responsibilities include but are not limited to understanding the key drivers of losses and loan loss reserves, their relative importance and the current trends; apply this knowledge effectively to forecast losses / loan loss reserves meaningfully and accurately; analyze underlying model outputs relative to other business, ensure that the models provide rational and logical output, Reconcile detailed financial data from disparate data sources, be able to present the findings to their manager and various key stake-holders and senior management across the organization; hold meaningful discussions and present to various review and challenge and / or audit teams and assist with regulatory reviews; ensure best in class governance and documentation practices for these functions; drive process efficiencies through automation for the underlying data, forecasting and reporting processes

Key Responsibilities:
• Work independently and with other team members to effectively execute:
    - Quarterly loss / loan loss reserve forecasting and stress testing processes (CCAR, QMMF, Recovery Plan) deliverables for one or more retail portfolios with primary focus on NA cards
    - Associated governance activities (Manager Control Assessment, End User Computing, Activity Risk Control Monitoring and its Assessment Units)
    - Cross-portfolio and cross-functional collaboration on loss / loan loss reserve forecasting and stress testing analytics
• Assist in review and challenge of existing models, and model outputs to identify areas of improvement relative to portfolio & macro-economic trends.
• Understand the calculation of reserves, components of P&L, and the impact of CECL on CCAR results besides understanding the synergies between two processes.
• Collaborate with other teams like Risk Modeling, Portfolio & New Account Forecasting, Data Reporting and to complete requests on financial planning & CCAR/DFAST results and increased integration of credit risk & PPNR results.
• Perform complex risk policy analytics in terms of sizing the impact of credit/business/regulatory policies on loss performance and incorporate it into the stress testing process.
• Perform econometric analysis to estimate and explain the impact of changing macroeconomic trends on Portfolio Performance Losses, delinquency etc.
• Establish and continually evolve standardized business and submission documentation
• Collaborate with Risk and Finance organization to understand sources of data and continue to improve the process of defining, extracting and utilizing data.
• Identify areas of improvement in BAU and drive process efficiency through process simplification and automation (VBA, SAS, etc.)
• Execute information controls (version control, central results summary) to meet business objectives with utmost clarity.

Qualifications:
• 4+ years of work experience in financial services, business analytics or management consulting.
• Post graduate degree with specialization in a quantitative discipline: Statistics, Mathematics, Economics, Econometrics, Management, Operations Research or Engineering
• Understanding of risk management. Knowledge of credit card industry and key regulatory activities (CCAR) is a plus. Experience in CCAR / DFAST/Stress Testing is preferred.
• Strong understanding and hands-on experience with econometric and empirical forecasting models. Experience in data science / machine learning is preferred with ability to handle large datasets.
• Experience in using analytical packages like SAS, Datacube/Essbase, MS Office (Excel, PowerPoint)
• Vision and ability to provide innovative solutions to core business practices.
• Ability to develop partnerships across multiple business and functional areas.
• Strong written and oral communication skills.

Leadership Competencies:
• Ability and experience to drive changes in order to achieve business targets
• Displays flexibility to work well with varying personal styles
• Takes personal responsibility to lead by example. Understands and appreciates diverse backgrounds.
• Demonstrates strong ethics
• Develops strong cross-functional relationships within and outside Risk Management
• Contributes to a positive work environment; shares knowledge and supports diversity

About Citi:
Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients.

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Job Family Group:

Risk Management

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Job Family:

Model Development and Analytics

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Time Type:

Full time

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Most Relevant Skills

Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

 

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