PPNR- Model validation/Model development
4 days ago
- Develop and implement statistical models to forecast PPNR components such as net interest income, fee income, and operating expenses.
- Evaluate model performance and assess the appropriateness of model assumptions, inputs, and methodologies.
- Conduct thorough validation of PPNR models in accordance with regulatory requirements and best practices.
- Collaborate with stakeholders to understand business needs and ensure model outputs align with organizational objectives.
- Provide expertise and guidance on model development, validation, and documentation to cross-functional teams.
- Perform quantitative analysis to identify trends, patterns, and potential risks in PPNR data.
- Contribute to the enhancement of model governance frameworks, policies, and procedures.
- Support model implementation and ongoing monitoring activities, including model performance tracking and reporting.
- Stay abreast of industry trends, regulatory developments, and emerging techniques in PPNR modeling and validation.
- Participate in model risk committees and communicate validation findings to senior management.
- Master's or Ph.D. in Statistics, Mathematics, Economics, Finance, or a related quantitative field.
- 3+ years of experience in quantitative modeling, statistical analysis, and/or financial risk assessment within the banking or financial services industry.
- Demonstrated proficiency in programming languages such as R, Python, or SAS for model development and validation.
- Strong understanding of financial products, PPNR drivers, and balance sheet dynamics.
- Familiarity with regulatory requirements related to model risk management and validation (e.g., SR 11-7, CCAR, DFAST).
- Proven ability to apply advanced statistical and econometric techniques to solve complex business problems.
- Experience with model validation techniques, including back-testing, stress testing, and sensitivity analysis.
- Excellent written and verbal communication skills, with the ability to articulate technical concepts to non-technical stakeholders.
- Detail-oriented approach with a focus on accuracy and quality in model development and validation processes.
- Ability to work effectively in a collaborative, cross-functional environment and manage multiple priorities concurrently.
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