Job Description
About KPMG in India
KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.
KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.
Key Responsibilities
Credit Risk Model Development and Validation
- Develop quantitative models within the credit risk domain, including IRB and IFRS 9 components.
- Define solutions and frameworks for credit risk stress testing, ensuring internal model consistency and practical application.
- Perform model validation and ensure compliance with regulatory frameworks such as Basel III and IFRS.
- Conduct stress testing for credit risk, incorporating various scenarios and macroeconomic sensitivities.
Tool Development and Implementation for Credit Risk
- Develop and implement tools in Python to simulate portfolio impacts for various scenario analyses related to credit risk.
- Replicate existing tools built in SAS into Python to enhance efficiency and scalability.
- Utilize SQL for data management and analysis, ensuring robust data handling and processing capabilities.
- Has demonstrated skills in regression techniques such as linear, multiple, logistic and polynomial regression with a strong understanding of statistical concepts and methodologies, including hypothesis testing, confidence intervals, p-values, variable selection, model evaluation, and assumptions of regression analysis such as test for normality, multicollinearity, heteroskedasticity
Policy Formulation and Process Mapping
- Frame and review policies related to Credit Risk and various areas of Credit risk including ECL, Capital computation, stress testing etc.
- Develop and optimize methodologies.
- Perform gap analysis and benchmarking against regulatory guidelines and best practices.
Stakeholder Management and Communication
- Build strong relationships with internal and external stakeholders to facilitate the understanding and application of credit risk models, frameworks, and tools.
- Provide sharp data analytics to contribute to key decisions related to credit risk management, ensuring insights are actionable and aligned with business objectives.
- Communicate complex technical concepts to non-technical stakeholders effectively.
Technical Expertise and Continuous Improvement
- Maintain proficiency in programming languages such as Python, SQL or SAS and explore
- Stay updated with the latest developments in credit risk modeling, stress testing methodologies, and regulatory requirements.
- Contribute to continuous improvement initiatives by identifying opportunities for process optimization and innovation.
Market and Geographical Exposure
- Work on projects across different geographies and gain insights into diverse regulatory environments and market conditions.
- Provide strategic credit risk insights and recommendations based on diverse market conditions and regulatory environments.
Equal employment opportunity information
KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.
Qualifications
Bachelors / Masters degree in Finance, Economics, Statistics, Computer Science, or a related field. A masters degree or professional certifications (e.g., CA, FRM, CFA) are highly desirable.
