Position: Lead-Credit Risk Modelling (MNC Consulting Firm)

Role

- The Company provides specialist advisory services across credit risk modelling, model validation, IFRS 9 implementation, portfolio analytics and regulatory risk management to financial institutions and corporate clients
- Develop and review credit risk models using Excel-based rating agency frameworks, Python and statistical techniques including logistic regression, decision trees and ensemble methods.
- Build and enhance IFRS 9 expected credit loss models, including PD, LGD, EAD and CCF components across both simplified and general approaches.
- Develop roll-rate-based PD models using customer-level receivables data, portfolio-level data and ageing cohort analysis.
- Apply advanced methodologies including TTC-to-PiT conversion, Vasicek modelling, survival PDs and term PD structures.
- Conduct credit risk model validations aligned with OCC 2011-12 guidance and Basel requirements
- Perform parameter-level validation including WoE, IV analysis, backtesting and out-of-time performance testing.
- Evaluate statistical, scorecard and hybrid risk models to ensure analytical integrity and regulatory compliance.
- Serve as a subject matter expert in client discussions, supporting solution design, proposal development and project delivery.
- Translate client requirements into practical modelling approaches and commercially relevant analytical outputs.
- Identify opportunities to expand client engagements through value-added risk advisory solutions.




- Support the development of the wider Advisory team's credit risk modelling and validation capability through mentoring, coaching and knowledge sharing.
- Create reusable modelling templates, validation frameworks and best-practice guidance to improve consistency and efficiency.
- Help colleagues develop expertise in statistical modelling, IFRS 9/ECL methodologies, model validation standards and emerging AI-related risk concepts.

Requirements

- 7-12 yrs of hands-on experience in credit risk model development, model validation, IFRS 9/ECL modelling, credit analytics or related risk advisory functions.
- Strong proficiency in Excel and Python for statistical analysis ((logistic regression, decision tree, ensemble methods), model development and validation.
- Deep understanding of credit risk methodologies, scorecard development, rating frameworks, model lifecycle management and regulatory model governance.
- Demonstrated ability to independently manage complex analytical projects and client engagements.
- Solid stakeholder management and communication skills, with the ability to explain complex technical concepts clearly.
- Experience in ECL modeling using both simplified and general approaches as per IFRS guidelines
- Experience of TTC to PiT conversion using Vasicek models
- Knowledge of EXCEL and Python libraries for multivariate/ statistical modeling
- Some exposure to AI models in context of credit risk
- Additional experience in stress testing, reverse stress testing and scenario-based portfolio analytics will be preferred.

Location: Mumbai

This position is for a Client of Vertex Corporate Services which is a Leading MNC Consulting Firm

📌 Lead-Credit Risk Modelling (MNC Consulting Firm) (Mumbai)
🏢 Vertex Corporate
📍 Mumbai