Manager, Credit Risk

BDO India; Mumbai City; Sur place; INR 2 500 000 - 4 000 000; Plein temps

Résumé du poste

BDO India seeks an experienced Credit Risk & Analytics professional to join our team in Mumbai. You will lead consulting engagements with banks, financial institutions, NBFCs and corporates, focusing on credit risk modelling, IFRS 9 implementation, ECL estimation, and stress testing.

You will develop and validate models for PD, LGD, and EAD, analyse provisioning methodologies, and deliver actionable recommendations.

Qualifications

• Postgraduate degree or higher in Finance, Economics, Statistics, Data Science, Mathematics, or related quantitative field.
• Experience in Credit Risk analytics, modelling, or risk consulting.
• Strong IFRS 9, ECL and credit risk provisioning knowledge.
• Hands-on experience in PD, LGD and EAD modelling.
• Proficiency in Python, SQL, SAS, or R.
• Excellent project, stakeholder management, and communication skills.
• Ability to lead teams and mentor staff.

Responsabilités

• Lead and deliver credit risk consulting engagements covering IFRS 9, ECL estimation, model development and validation, ICAAP reviews, stress testing, and provisioning frameworks.
• Develop, assess, and enhance credit risk models, including PD, LGD, and EAD.
• Perform ECL computation and analysis, evaluate provisioning methodologies, and recommend improvements.
• Apply statistical and quantitative techniques such as regression analysis, transition matrices, and default modelling.
• Analyse credit risk across diverse lending products including wholesale, corporate, auto, personal, and mortgages.
• Work with large datasets to support model development, validation, and risk analytics.
• Apply Python, SQL, SAS, or R to develop and test credit risk models and solutions.
• Assess model performance, assumptions, and alignment with regulatory requirements.
• Engage with client stakeholders to understand business requirements and present findings.

Connaissances

Credit risk modelling

IFRS 9 / ECL

Client management

Project delivery

Team leadership

Programming

Formation

Postgraduate degree or higher in Finance, Economics, Statistics, Data Science, Mathematics, or related quantitative field

Outils

Python

SQL

SAS

R

Description du poste

About the Role

We are looking for an experienced professional to join our Credit Risk & Analytics team and work on consulting engagements with leading banks, financial institutions, NBFCs, insurance companies, and corporates.

The role focuses on credit risk modelling, IFRS 9 implementation, Expected Credit Loss (ECL) estimation, stress testing, and credit risk framework enhancement. The ideal candidate will combine strong quantitative and analytical capabilities with client management and project delivery skills, along with the ability to guide teams and contribute to the firm's growth.

Key Responsibilities

• Lead and deliver credit risk consulting engagements covering IFRS 9, Expected Credit Loss (ECL) estimation, credit risk model development and validation, ICAAP reviews, stress testing, and provisioning frameworks.
• Develop, assess, and enhance credit risk models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Perform ECL computation and analysis, evaluate provisioning methodologies, and recommend improvements to credit risk measurement and reporting frameworks.
• Apply statistical and quantitative techniques, including regression analysis, roll rate analysis, transition matrices, Markov chains, and default and recovery rate modelling.
• Analyse credit risk across diverse lending products, including wholesale and corporate loans, auto loans, personal loans, mortgages, and education loans.
• Work with large and complex datasets to support model development, validation, performance assessment, and risk analytics.
• Apply programming and data analysis tools such as Python, SQL, SAS, or R to develop, test, and enhance credit risk models and analytical solutions.
• Assess model performance, assumptions, limitations, and outcomes, ensuring alignment with applicable regulatory requirements and industry practices.
• Engage with client stakeholders to understand business requirements, present findings, and provide actionable recommendations.
• Manage day-to-day project execution, including work plans, deliverables, timelines, quality reviews, and stakeholder communication.
• Lead, mentor, and develop team members, providing technical guidance and supporting hiring and capability-building initiatives.
• Provide regular updates to the Business Unit Leader on project progress, key risks, deliverables, and engagement outcomes.

Required Qualifications and Experience

• Postgraduate degree or higher in Finance, Economics, Statistics, Data Science, Mathematics, or a related quantitative discipline.
• Relevant experience in Credit Risk, Credit Risk Analytics, quantitative modelling, or risk consulting.
• Strong understanding of IFRS 9, Expected Credit Loss (ECL), and credit risk provisioning methodologies.
• Hands-on experience in developing, validating, or enhancing credit risk models involving PD, LGD, and EAD.
• Knowledge of statistical modelling techniques, default and recovery rate estimation, and credit risk stress testing.
• Proficiency in at least one relevant programming or analytical tool, such as Python, SQL, SAS, or R.
• Experience handling large datasets and applying quantitative techniques to credit risk analysis.
• Strong project management, stakeholder management, analytical, and problem-solving skills.
• Excellent report-writing, presentation, and communication skills.
• Ability to work independently, manage multiple assignments, and lead teams while maintaining high standards of delivery.

Preferred Qualifications

• Professional certifications such as FRM, CFA, PRM, or an equivalent qualification.
• Experience delivering credit risk consulting engagements for banks, NBFCs, or other financial institutions.
• Exposure to ICAAP reviews, regulatory stress testing, IFRS 9 implementation, ECL framework reviews, and provisioning assessments.
• Experience managing client engagements, mentoring teams, and contributing to business growth and practice development.