VP - Credit Portfolio Analytics - BFS

The VP will be responsible for the following activities associated with uncertainty loss modeling: Tail Risk: Credit Economic Capital (EC) Simulated Credit Stress Loss, Stressed EL: Single Serial Scenario Stress Testing. Early Warning: Model design, development, and maintenance

Specialties:

- Infuse high-performance computational loss modeling on credit portfolios.

- Manage the global EC monthly production process.

- Enhance stress loss modeling.

- Expand the application of loss distribution results,

- Upgrade regional and global managerial credit portfolio stress testing,

- Enhance concentrations management to support strategic planning via portfolio optimization.

- Manage EC and Stress Testing model validation processes.

This role will integrate across entities including our primary commercial banking securities, trust banking and regional subsidiaries and entities in the Americas and globally, especially as it relates to global credit loss modeling. In addition, the role will be among the initial hires in the India market for CSG, and as such is expected to anchor the recruitment and development of a portfolio analytics and modeling team in that market.

Main Responsibilities:

- Assist the expansion of CSG's and its global counterparts' capabilities to use EC for managerial stress testing, concentration management, and business strategic planning.

- Lead model updates on key parameter settings such as Correlation structure, Probability of Default (PD)/ Loss Given Default (LGD) correlation and LGD volatility.

- Assist Credit Portfolio Risk Management (CPM) projects (e.g., correlation and concentration analysis, hedge performance analysis, asset allocation, etc.)

- Identify data and parameter improvements within the Moody's RiskFrontier model, the key

- computational engine that drives the EC modeling process.

- Assist factor analysis and explanation of EC and Stress Testing outcomes according to PD, LGD, Exposure At Default (EAD), Exposure shifts, and Parameter settings.

- Support data processing, parameter estimation, impact analysis, and biennial Model Validation / Refinement.

- Share the EC knowledge with internal GPAD team members, also risk partners, Lines of Business, and Senior management.

- Expand team and personal knowledge base across these and related risk types.

- Prefer master's degree in Financial Engineering, Finance, Statistics, Mathematics or a related quantitative field (or foreign equivalent degree).

Requirements:

- Requires 10+ years of Credit Risk experience with knowledge of key analytics tools (e.g. Moody's RiskFrontier, CreditEdge-EDFX; Bloomberg's DRSK, CRPR).

- Superior quantitative and data manipulation capabilities.

- Principles-based Project Management capabilities without sole reliance on an external PM.

- Strong communication skills.

- Ability to work collaboratively and independently in concurrent and asynchronous styles.

- Ability to work with large datasets - required.

- Knowledge of risk methodology, finance/banking to enhance risk analytics.

- Expertise with R, Python, or SAS data programming languages, also SQL required.

- Focus on accuracy and reliability, to ensure confidence in results.

- Helpful

- Prior bank experience is a plus, preferably from risk management.

- Knowledge of Software Engineering and Machine Learning a plus