1,013 Credit Risk jobs in India

Basic Information

Title : Associate/Senior Associate/Delivery Lead

Experience : 2-6 Years

Location : Bangalore, Pune, Gurugram

Key Responsibilities

• Gain deep understanding of the model inventory and the model risk management framework and lifecycle of the client
• Validate CCAR Stress Testing for PPNR, balance sheet, scenario design and loss forecasting models used for internal risk management and provisioning as well as regulatory submissions
• Assess the data requirements of the model, assumptions, and model methodology, analyze model outcomes, track ongoing model performance, and run stress tests on models based on company specific or regulatory stressed economic scenarios
• Provide guidance to model owners for remediation of issues identified during validation to achieve MRM policy adherence
• Provide support to client’s model risk management group in meeting their regulatory commitments
• Interact proactively and build strong relationship with various model owners/stakeholders
• Represent client’s model risk management group in interactions with model owners across lines of business
• Drive adoption of best practices for model validation, assessment and documentation
• Ability to work well in a team and feel comfortable presenting model validation findings
• Gain ongoing knowledge of accepted practices and current research in the areas of mathematical modelling in finance and model risk management, though academic literature and respected financial/economic journals
• Mentor junior quantitative analysts and conduct training sessions on mathematical modelling, quantitative analytics and risk management

Job Requirements

Qualification

• M.Sc/PhD in Mathematics / Statistics / Economics or MBA Finance with experience in an MRM role (Tier I Colleges only )

Experience

• Either, candidate should have exposure to CCAR modelling in an applied setting

Functional Competencies

• Working knowledge in Stochastic Calculus, Linear Algebra, Differential Equations, Statistics, Simulation, Computational Methods and Numerical Analysis (working knowledge or coursework in mathematical finance will be an advantage)
• Strong knowledge in mathematical techniques used in the development of VaR computation, Risk Charge calculations Tail Risk modelling
• Working knowledge of Copula models, Monte Carlo simulation and techniques used in Traded Credit Risk modelling will be a huge plus
• Well versed in regression modelling (Multiple Linear, Logistic, Polynomial, Beta, Poisson, and Time Series) as well as regularization techniques used in regression such as Ridge/Lasso/Elastic Net etc.
• Working knowledge of machine learning models such as Decision Trees, Max Margin Classifiers and model ensemble ideas such as bagging, boosting and stacking
• Well versed in one of R/Python and MS Excel
• Research mindset, strong analytical and problem-solving skills
• Strong documentation skills

Behavioral Competencies

• Excellent team player
• Good verbal and written communication skills
• High accuracy and attention to detail
• Strong conceptual thinking and ability to challenge traditional thought process
• Ability to work efficiently in an unstructured environment
• Self-motivated, ability to multi-task and work under high-pressure situations
• Build strong relationships and networks across different business lines

About Us:

Apollo Finvest is a tech-first NBFC redefining how India lends. Think of us as the AWS for lending ! With cutting-edge APIs, and a splash of startup magic, we're enabling India’s top fintechs to build and scale their lending journeys seamlessly. Innovation meets compliance, and speed meets scale: that's the Apollo way.

Key Responsibilities:

• Develop and manage credit strategies for unsecured personal loans .
• Work on digital underwriting processes and real-time decision engines to support faster, smarter credit decisions.
• Collaborate with product and data teams to strengthen risk assessment frameworks.
• Oversee key parts of the loan lifecycle, including disbursement, repayment, and collections.
• Monitor portfolio performance and formulate risk mitigation measures.
• Stay informed about regulatory updates, credit trends, and industry benchmarks.

What We’re Looking For?

• Minimum 4 years of experience in unsecured personal loans, preferably in a digital lending environment.
• Strong understanding of digital lending platforms, including underwriting and credit policies.
• Experience working with a fintech or NBFC , ideally one with its own consumer-facing app .
• Analytical mindset and the ability to work with large datasets to make informed decisions.
• Strong communication and collaboration skills.

What We Offer?

• Competitive salary and benefits
• Work directly with our CEO (ex-PharmEasy & Hotstar) and CFO (former HDFC ace with 10+ years in financial services) in a high-impact, fast-growing fintech environment.
• A fast-paced, collaborative culture that values innovation, ownership, and bold thinking.

Apply Today!

If you're passionate about credit strategy and excited to shape the future of digital lending, write to us at or !

Key Responsibilities:

• Perform comprehensive credit risk evaluations of corporates, especially within the financial services domain (NBFCs, fintechs, corporates, etc.).
• Analyze financial statements, business models, and sector-specific risks to assess creditworthiness.
• Conduct in-depth due diligence, including participation in business meetings with promoter/management, discussions with rating agencies, site visits, and thorough industry analysis.
• Stay abreast of regulatory changes impacting the financial sector or current portfolio (e.g., RBI, SEBI guidelines).
• Collaborate with business, Risk and compliance teams timely evaluation for credit call.
• Recommend risk mitigants tools and develop model for recurring credit development, provide live feeds, Update and approval from IC/CC members
• Support the development of sector-specific credit frameworks and risk appetite statements. Understanding debt instruments / fixed income product.
• Updated current bank/rating agency credit risk models understand market sources tool for credit analysis.

Required Skills & Qualifications:

• Bachelor's/Master’s degree in Finance, Economics, Commerce, or related field. CA/CFA/MBA preferred.
• 3–8 years of experience in credit risk assessment, particularly within the financial sector.
• Strong understanding of financial statements, cash flow analysis, capital structure, and regulatory frameworks.
• Knowledge of RBI regulations and sector-specific nuances in banking, NBFCs, Corporates and other financial institutions.
• Proficiency in financial modeling, risk scoring, and credit rating methodologies.
• Excellent analytical, communication, and presentation skills.
• Experience in conducting ground-level due diligence and client interactions.

Credit Risk

Location - Bangalore, Hyderabad, Mumbai, Pune, Gurgaon

Notice - Immediate to 60 days

Experience - 3+ years

Overview PwC is one of the most prestigious professional services firm in the world, serving as the auditor to nearly half of the world’s largest banks. PwC US Risk and Regulatory (R&R) comprises of a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and driver of, industry leading practices and has deep knowledge of regulatory expectations. R&R professional’s experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk—as well as those used for financial reporting, valuations and economic capital estimation. Risk Analytics Center of Excellence (CoE), is the India extension of R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises of risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM etc. and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting edge innovation using data science, Artificial Intelligence, Machine Learning and Deep Learning.

Credit Risk Analytics Professional Job Specification:

Candidate would be responsible for developing, validating, auditing and maintaining credit risk models. Candidates would be expected to support financial institutions on meeting jurisdictional regulatory requirements and their broader risk management initiatives.

Core Skill Requirements

Candidate must have relevant experience in in statistical / mathematical modeling, quantitative research, credit risk management, or related field at a reputed bank, investment or broker services, asset management firm, Insurance provider or a consulting firm. Wider skill requirements include:

• Experience in Credit Risk Modeling PD/LGD/EAD – TTC, PIT, Stressed and unstressed portfolio
• Experience in Model Development, Model Validation, Model Audit (implementation and execution experience will not be considered directly relevant)
• Knowledge of one or more of global regulatory norms - CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR-11/7, E-23 around data sufficiency, modeling methods, industry standards etc.
• Well versed with one or more statistical techniques used in credit risk modeling – Logistic Regression, Time series, OLS, Probit models, Survival techniques, Tobit, Fractional Logistic, Beta model, State Transition Matrix, Single Factor Merton model etc. Experience in Machine learning algorithms like Random Forest, SVM, Neural Network etc. and Artificial Learning use cases such as Natural Language Processing, Robotics etc. will be a plus
• Proficiency in one or more analytical tools such as SAS, R, Python, Matlab, Scala, VBA etc. Experience in Data Science and cloud based analytics platform will be a plus
• Understanding of credit risk metrics like RWA, Expected loss, Regulatory and Economic capital, OTTI, Watchlist, Asset quality etc.
• Conceptual understanding of the data and methodology used for credit risk regulatory models
• Leveraging experiential know-how of a wide range of loan types, including C&I, CRE, RRE, ABL, Leasing, Credit Card, Vehicle, Personal etc.
• Prior experience in domains like commercial banking, retail banking, treasury, investment management and strong knowledge of risk data analysis and development, strategy design and delivery deployment.
• Vendor Experience

o Experience in bureau data from credit unions e.g. D&B, Experian, Equifax, Transunion

o Experience in vendor models and ratings like Fitch, Credit pro, Moody etc. o Knowledge about external / benchmark models on consumer portfolios is a plus (FICO Score, Standards and Poor's, Fitch or Moody's Ratings) o Selecting, implementing and/or using commercial credit risk workflow, analytics- e.g., Moody's KMV, S&P and/or, reporting technologies- e.g., Oracle, Cognos, et al.

Non-functional skill requirements:

In order to succeed in PwC Risk CoE, it is desirable for candidates to possess:

• Understanding of market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business
• Excellent oral and written communication skills
• Solid analytical and problem-solving skills; ability to isolate and solve issues using large amounts of data
• Process orientation with strong technical skills and attention to detail
• Deep technical capabilities and industry knowledge of financial products
• Willingness to travel to meet client needs, as needed

Educational Background:

Desired candidate must have a master’s degree or higher in a quantitative discipline such as Economics, Statistics, Mathematics, Operation Research, Econometrics, Data Science, Finance, Engineering + MBA; advanced degree is a plus; Industry relevant certifications in CQF, FRM, CFA, CPA certification is a plus

Additional Requirement for Senior Positions:

Candidates aspirant of senior positions at PwC Risk CoE are expected to possess:

• Proven consulting skills to structure vague problems at hand and conceptualizing solutions
• Credentials in leading and driving large and or complex risk analytics engagements and initiatives independently
• Experience in supporting sales pursuits for risk analytics offerings and solutions
• Ability to manage multiple engagements simultaneously along with leading people and initiatives
• Strong conceptual understanding of various functional/technical skills
• Ability to drive innovation and thought leadership in the risk management domain
• Intellectual property, patents and exclusive rights on any innovative solution is a plus

Role - Credit Risk - GenAI

Location - Bangalore, Hyderabad, Pune, Mumbai, Gurgaon

Notice - Immediate to 60 days

Experience - 2 to 7 years

Overview

PwC is one of the most prestigious professional services firms in the world, serving as the auditor to nearly half of the world’s largest banks. PwC US Risk and Regulatory (R&R) comprises a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and is a driver of, industry-leading practices and has a deep knowledge of regulatory expectations. R&R professionals’ experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk—as well as those used for financial reporting, valuations, and economic capital estimation.

Risk Analytics Center of Excellence (CoE), is the India extension of the R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM, etc., and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting-edge innovation using Data Science, Artificial Intelligence, Machine Learning, and Deep Learning.

AI/ML & Credit Risk Analytics Professional – Job Specification:

Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives.

Multiple positions required;

Experience level: 2–6 years of relevant experience

Location: Bangalore

About the Team

The Risk Analytics Center of Excellence (CoE) is an integral part of PwC US’s Risk and Regulatory (R&R) practice, delivering advanced quantitative risk solutions to global banks and financial institutions. Our team is composed of highly skilled professionals with deep expertise across credit risk modeling, AI/ML development, model validation, and regulatory compliance. We apply a combination of traditional statistical approaches and

advanced AI/ML techniques to solve complex risk challenges across portfolios and geographies.

Role Overview

We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability.

Key Responsibilities

• Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts.
• Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches.
• Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful.
• Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc.
• Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments.
• Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations.
• Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space.

Required Skills & Experience

• 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation.
• Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital).
• Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages
• Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices.
• Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools.
• Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus.
• Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations.

Education & Certifications

• Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance.
• Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred.
• Contributions to opensource AI / ML projects and competitions is preferred

Job Position: Credit Risk Analyst (Periodic review process)

Location: Thane

What does a successful Credit Analyst do at FISERV?

The Credit Risk Analyst will be responsible for evaluating the creditworthiness of potential clients and assessing the overall risk associated with credit decisions. This role involves analyzing financial data, monitoring credit trends, and developing risk assessment models to support informed decision-making. The ideal candidate will possess strong analytical skills, attention to detail, and a passion for driving financial performance while ensuring compliance with regulatory standards.

What will you do:

• Analyze financial statements, credit reports, and other relevant data to assess the credit risk of potential clients.
• Monitor existing client accounts to identify potential credit risks and trends.
• Prepare regular reports on credit risk exposure and present findings to management.
• Work closely with the underwriting teams to provide insights and recommendations regarding credit decisions.
• Collaborate with compliance and legal teams to ensure adherence to regulatory requirements.
• Assist in the development and validation of predictive models to enhance credit decision-making processes.
• Stay updated on market trends, economic conditions, and regulatory changes that may impact credit risk.
• Investigations include the gathering of data from various sources and systems and interpreting the data to manage the risk.

What will you need to know:

• Bachelor's degree and/or equivalent 2+ years of experience in credit risk analysis, preferably within the payment processing or financial services industry.
• Strong analytical skills with the ability to interpret complex financial data.
• Knowledge of credit risk assessment frameworks and regulatory requirements.

What would be great to have:

• Excellent communication skills, both written and verbal, with the ability to present findings to stakeholders.
• Detail-oriented, organized, and able to manage multiple priorities effectively.
• MBA in Finance or CA as a fresher.

Key Responsibilities:

• Perform comprehensive credit risk evaluations of corporates, especially within the financial services domain (NBFCs, fintechs, corporates, etc.).
• Analyze financial statements, business models, and sector-specific risks to assess creditworthiness.
• Conduct in-depth due diligence, including participation in business meetings with promoter/management, discussions with rating agencies, site visits, and thorough industry analysis.
• Stay abreast of regulatory changes impacting the financial sector or current portfolio (e.g., RBI, SEBI guidelines).
• Collaborate with business, Risk and compliance teams timely evaluation for credit call.
• Recommend risk mitigants tools and develop model for recurring credit development, provide live feeds, Update and approval from IC/CC members
• Support the development of sector-specific credit frameworks and risk appetite statements. Understanding debt instruments / fixed income product.
• Updated current bank/rating agency credit risk models understand market sources tool for credit analysis.

Required Skills & Qualifications:

• Bachelor's/Master’s degree in Finance, Economics, Commerce, or related field. CA/CFA/MBA preferred.
• 3–8 years of experience in credit risk assessment, particularly within the financial sector.
• Strong understanding of financial statements, cash flow analysis, capital structure, and regulatory frameworks.
• Knowledge of RBI regulations and sector-specific nuances in banking, NBFCs, Corporates and other financial institutions.
• Proficiency in financial modeling, risk scoring, and credit rating methodologies.
• Excellent analytical, communication, and presentation skills.
• Experience in conducting ground-level due diligence and client interactions.

Role - Credit Risk - GenAI

Location - Bangalore, Hyderabad, Pune, Mumbai, Gurgaon

Notice - Immediate to 60 days

Experience - 2 to 7 years

Overview

PwC is one of the most prestigious professional services firms in the world, serving as the auditor to nearly half of the world’s largest banks. PwC US Risk and Regulatory (R&R) comprises a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and is a driver of, industry-leading practices and has a deep knowledge of regulatory expectations. R&R professionals’ experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk—as well as those used for financial reporting, valuations, and economic capital estimation.

Risk Analytics Center of Excellence (CoE), is the India extension of the R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM, etc., and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting-edge innovation using Data Science, Artificial Intelligence, Machine Learning, and Deep Learning.

AI/ML & Credit Risk Analytics Professional – Job Specification:

Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives.

Multiple positions required;

Experience level: 2–6 years of relevant experience

Location: Bangalore

About the Team

The Risk Analytics Center of Excellence (CoE) is an integral part of PwC US’s Risk and Regulatory (R&R) practice, delivering advanced quantitative risk solutions to global banks and financial institutions. Our team is composed of highly skilled professionals with deep expertise across credit risk modeling, AI/ML development, model validation, and regulatory compliance. We apply a combination of traditional statistical approaches and

advanced AI/ML techniques to solve complex risk challenges across portfolios and geographies.

Role Overview

We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability.

Key Responsibilities

• Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts.
• Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches.
• Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful.
• Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc.
• Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments.
• Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations.
• Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space.

Required Skills & Experience

• 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation.
• Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital).
• Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages
• Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices.
• Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools.
• Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus.
• Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations.

Education & Certifications

• Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance.
• Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred.
• Contributions to opensource AI / ML projects and competitions is preferred