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Credit & Market Risk Analytics
2 months ago
Credit Risk / Market Risk Analytics
Candidate would be responsible for developing, validating, auditing and maintaining credit/ market 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: BLR/ MUM/ KOL/ HYD
Candidate must have relevant experience in in statistical / mathematical modeling, quantitative research, credit or market 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:
For Credit Risk:
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.
For Market Risk:
Independently built and managed quantitative market and counterparty risk analytical models
• Strong experience/knowledge in at least some of the following areas (in quant space)
o Counterparty Credit Risk (PFE, CVA, XVA)
o Pricing and valuation - Derivatives (across one or more asset classes)
o Modeling of Risk Metrics (e.g, EPE, PFE, RWA, Greeks)
o Market Risk Scenarios and Stress Testing
o Development, prototyping and back-testing of Monte Carlo Credit Exposure Models o Incremental default risk, specific risk charge and stressed VaR o Worked on multiple Market Risk Models like to develop/review calculation of VaR(Historical, Parametric and Monte Carlo), RNiV, CCAR, IRC Model Validation/ development and present value for various type of instruments using any statistical tool
• Strong experience/knowledge in at least some of the following areas (business knowledge) o Good knowledge of market risk concepts: Risk Factor, VAR, Earning at Risk, cash flow at risk, ETL, PV01, Independent Validation, Exotic derivatives, FX, Interest rate derivatives, volatility, commodities, credit derivatives, Fixed income, Hull & White, Monte Carlo simulation, Capital calculations
Knowledge and experience with counterparty risk concepts (PFE,SA-CCR, EPE etc o Leveraging experiential know-how of a wide range of financial products like Equity, Derivative, Swaps, IR, Credit derivatives, OTC products, Swaps, Securitization, CDO's etc.
o Knowledge of one or more of global regulatory Topics BASEL II/III, IFRS 9, CCAR/DFAST, CECL, FRTB, SR-11/7 around data sufficiency, modeling methods, industry standards etc. • Assisted clients to design and implement strategic and functional changes across risk management, treasury, front office, middle office, and back office activities with a focus on risk and valuation processes, regulatory compliance, analytics, strategy, and organizational structure.
• Programming and Algorithms: R, Python, SAS, Matlab, Scala, VBA etc.
• Experience with with Murex, QRM, Reuters, FINCAD, Bloomberg and Algo is a plus
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
