PPNR- Model validation/Model development

2 days ago

Bengaluru, Karnataka, India Careernet Technologies Full time ₹ 12,00,000 - ₹ 36,00,000 per year
Overview: The PPNR Model Validation/Model Development role is crucial for ensuring the accuracy and reliability of predictive models used in the projection of pre-provision net revenue (PPNR) for financial institutions. The individual in this role will be responsible for developing and validating a variety of models that support PPNR estimation processes, helping to drive data-informed decision-making and risk management strategies.Key Responsibilities:
  • 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.
Required Qualifications:
  • 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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