Credit Risk Model Development and Validation

Job Description

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. Multiple positions required; Experience level 2-12 years of experience; Location: Bangalore 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 Experience in bureau data from credit unions e.g. D&B, Experian, Equifax, Transunion Experience in vendor models and ratings like Fitch, Credit pro, Moody etc. Knowledge about external / benchmark models on consumer portfolios is a plus (FICO Score, Standards and Poor's, Fitch or Moody's Ratings) 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 requirement Preferred candidate profile