Vice President, Specialist, Model Validation, Risk Management Group

DBS Bank Ltd; Mumbai City; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

DBS Bank Ltd. is seeking an experienced professional to lead its Model Validation function within the Risk Management Group.

The role involves independently validating credit risk models used across wholesale and retail banking, assessing design, data quality, implementation, and ongoing performance to ensure regulatory compliance and sound financial risk management. Responsibilities include validation of PD/LGD/EAD models, governance, reporting, backtesting, and stakeholder engagement with

Qualifications

• 10+ years in model validation or development, with credit risk exposure.
• Experience validating both wholesale and retail banking models.
• Experience with AI/GenAI modelling and lifecycle.
• Ability to adopt new modelling areas like climate risk.
• Understanding of model governance principles.

Responsibilities

• Conduct end-to-end independent validation of credit risk models across wholesale and retail banking.
• Critically evaluate model development methodologies and assumptions.
• Assess data quality and suitability for modelling and monitoring.
• Verify robust implementation of models in systems.
• Review ongoing model performance monitoring, backtesting, and sensitivity analyses.
• Establish governance and model validation policy in line with regulatory requirements.
• Prepare comprehensive validation reports and present findings to stakeholders.
• Ensure compliance with SR 11-7, CECL, IFRS 9, Basel Accords.
• Engage with developers for constructive challenge throughout the lifecycle.
• Collaborate with risk management teams, business lines, and internal audit.
• Contribute to process, methodology, and tool improvements.

Skills

Credit risk concepts

RBI Basel guidelines

Analytical thinking

Communication skills

Attention to detail

Collaboration

Regulated finance experience

Model validation

Data analytics

Problem solving

Education

Graduate/Postgraduate degree in quantitative discipline

Tools

Python

R

SAS

SQL

Job description

Job Purpose

We are seeking a highly motivated and skilled individual to lead the Model Validation function with Risk Management Group. The successful candidate will be responsible for independently validating a diverse range of credit risk models used across both wholesale and retail banking businesses. This role involves assessing model design, data quality, implementation, and ongoing performance to ensure models are fit for purpose, compliant with regulatory requirements, and effectively manage financial risk.

Key Accountabilities and Requirements:

• Independent Model Validation: Conduct end-to-end independent validation of credit risk models, including but not limited to:
  • Wholesale Banking Models: PD, LGD, EAD models for corporate, commercial real estate, and other institutional exposures; stress testing models; counterparty credit risk models; credit rating models
  • Retail Banking Models: PD, LGD, EAD models for mortgages, auto loans, credit cards, personal loans; application scorecards, behavioral scorecards, collections models.
• Methodology Review: Critically evaluate model development methodologies, underlying assumptions, conceptual soundness, and quantitative techniques.
• Data Quality Assessment: Assess the quality, completeness, and appropriateness of data used in model development and ongoing monitoring.
• Implementation Review: Verify the accurate and robust implementation of models within relevant systems.
• Performance Monitoring: Review and challenge ongoing model performance monitoring frameworks and results, including backtesting, benchmarking, and sensitivity analysis.
• Governance and Policy: Establish Governance processes and Model validation Policy in line with local regulatory and group requirements.
• Documentation & Reporting: Prepare comprehensive validation reports detailing findings, limitations, recommendations, and conclusions. Present findings to model owners, developers, and relevant committees.
• Regulatory Compliance: Ensure models and validation practices comply with internal policies and external regulatory requirements (e.g., SR 11-7, CECL, IFRS 9, Basel Accords).
• Challenging Model Development: Proactively engage with model developers to provide constructive challenge and guidance throughout the model lifecycle.
• Stakeholder Engagement: Collaborate effectively with model development teams, risk management functions, business lines, internal audit, and regulators.
• Continuous Improvement: Contribute to the enhancement of validation processes, methodologies, and tools.

Required Experience

• 10+ years of experience in model validation or model development, specifically with exposure to credit risk models.
• Demonstrable experience with model review and validation pertaining to both wholesale banking and retail banking
• Understanding of technical modelling requirements throughout model life cycle covering data analytics, coding, development, deployment, monitoring and maintenance for both traditional AI and Gen AI models
• Capacity to adopt new modelling areas (e.g., climate risk & Agentic AI) and problem solving
• Understanding of model governance requirements and principles

Education / Preferred Qualifications

Post -graduate/ Graduate degree in quantitative discipline (such as Statistics, Mathematics, Quantitative Finance, Data Analytics or equivalent) is preferred

Core Competencies

• Deep understanding of credit risk concepts, including PD, LGD, EAD, ECL, credit ratings, credit scores, and stress testing.
• Familiarity with relevant RBI and Basel guidelines
• Understanding of financial products and business processes in both wholesale and retail banking segments.
• Analytical & Critical Thinking: Exceptional analytical, problem-solving, and critical thinking skills with the ability to identify subtle model weaknesses and propose practical solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts clearly and concisely to both technical and non-technical audiences.
• Attention to Detail: Meticulous attention to detail and a commitment to producing high-quality work.
• Collaboration: Ability to work independently and as part of a team in a fast-paced environment.
• Experience in a regulated financial institution environment.

Technical Competencies

• Strong proficiency in statistical modeling techniques: regression analysis, econometrics, time series analysis, machine learning algorithms (e.g., logistic regression, decision trees, random forests, gradient boosting).
• Expertise in programming languages for data analysis and statistical modeling: Python, R, SAS.
• Familiarity with database querying tools (SQL) is a plus.
• Experience with large datasets and data manipulation.

Location:

Mumbai

Job:

Analytics

Schedule:

Regular

Employee Status:

Full time