Associate Director/ Vice President - Model Validation

The Model Risk Management (MRM) provides oversight for the MRM Framework, which consists of the policy, processes, and procedures. The Principal Advisor - Model Risk Management (MRM) will be responsible to conduct independent model validations to ensure models align with business objectives and design objectives. Verify that models are performing as expected, identify potential limitations, which includes assessing potential impact. Perform annual reviews and review the on-going monitoring reports to ensure that the models are performing as intended.

You will be based out of First Citizens India (FCI) office in Bangalore, report into the Associate Director of Model Risk Management, India, and function as an integral member of the global MRM organization. The role will work collaboratively with the global MRM team and act as their point of contact in India.

You will be responsible for supporting all aspects of the global MRM program. The successful candidate will support the global MRM efforts to ensure that models are appropriately designed, implemented, and managed including but not limited to conceptual soundness, model implementation and use, model documentation, model performance monitoring, governance, tuning and validation.

The role will manage a team of resources with solid MRM experience and skills, partners with global stakeholders to establish effective collaboration and partnership to build and manage talent capabilities. Communicates and collaborates across a broad set of stakeholders. Responsive to changes in the business environment.

Essential

Primary Responsibilities:

• Comprehensive Model Validation: Conduct thorough and comprehensive validations of various model components, ensuring that they are accurate, reliable, and aligned with the intended business objectives and regulatory requirements. This includes but is not limited to:
• Model Inputs Analysis: Apply data analysis techniques to assess the quality, integrity, and appropriateness of data used in the models. Examine data extraction, cleaning, transformation processes, and evaluate data-related assumptions and limitations.
• Model Framework Evaluation: Scrutinize the model design and construction, verifying the suitability of the modeling framework and theory for the intended use. Review model segmentation, variable selection, model testing procedures, and evaluation model assumptions, limitations, and risks.
• Model Code Review: Review model code to ensure correctness, accuracy, and absence of material errors. Collaborate with model developers to address any identified issues.
• Outcomes Analysis: Assess both in-sample and out-of-sample back test results; evaluate sensitivity and scenario testing, stress testing, benchmark model development, and quantitative and business performance metrics.

• Risk Identification and Mitigation: Provide effective challenges and identify potential model risks. Recommend appropriate mitigation measures and enhancements to improve model quality and compliance with regulatory standards.
• Documentation and Reporting: Produce high-quality, comprehensive validation reports that clearly communicate findings, recommendations, and potential risks to both technical and non-technical stakeholders. Ensure that validation documentation adheres to internal standards.
• Audit and Regulatory Review Support: Assist in gathering and providing materials requested by internal audit and regulators, drafting responses to questions, and defending validations in exams.
• Continuous Learning and Improvement: Stay up to date with emerging trends and best practices in model validation and regulatory requirements. Contribute to the enhancement of the model validation framework by suggesting process improvements and implementing industry-leading methodologies.
• Develop and maintain model governance documentation and performance monitoring, including periodically presenting results to MRM Leadership.
• Interact with all key stakeholders including model users, model owners, vendors, Model Risk Governance, and other Validators throughout the model lifecycle including validation, ongoing performance evaluation.
• Build relationships across model owners, data scientists, Model Risk Management, Audit, and third-party vendors.
• Use subject matter expertise and analytics to proactively identify and address gaps and identify emerging risks.
• Contribute towards remediation efforts for model-related issues identified through exams, audits, and model validations.