Team Member-SUPPORT SERVICES-Credit Industry Research

1. Credit Risk Analytics and Modelling - Analyse, model, validate and document various measures of Credit Risk for use in Expected Credit Loss and Capital computations.
   • Hands-on experience in building, implementing, documenting, monitoring, validating, refining models and scorecards - in particular for PD, LGD, EAD and related Credit Risk metrics - using statistical methods and / or expert judgement based techniques.
   • In depth understanding of the techniques and functional insights that drive Credit Risk models and the experience of having used modelled output in computing Expected Credit Loss (ECL) under Ind AS, Credit Risk Capital under Internal Ratings based approaches, Economic Capital and having taken these measures through the scrutiny of auditors and regulators. This is the main requirement of the role and the individual should have a good knowledge of this function.
   • Derive insights from data and effectively communicate these insights to Risk, Credit and Business teams. Develop Risk Dashboards and analytical reports for Senior Management.
2. Preparing and submitting reports to the regulator and / or senior management on a periodic and adhoc basis. The job-holder will be responsible for computing and reporting ECL and related metrics on an on-going basis.
3. Ability to work with (gather, consolidate, prepare, summarise) large data sets on a routine basis with an eye for detail and flair for numbers. Data cleansing and preparation for use in model building.
4. Ensure reliability, integrity and consistency of reported and underlying data

1. About 4 to 8 years of experience in a Bank, NBFC, Consulting Firm, Rating Agency in the areas of working PD, LGD, ECL, EAD. Exposure to risk reporting or financial reporting would be an advantage.
2. Degree in statistics, mathematics or econometrics (or equivalent professional qualifications) with hands-on experience in statistical model development, implementation, validation would be an advantage.
3. Experience and expertise in using any one or more among Python / SAS / R. Intermediate level SQL skills will be useful.
4. Strong experience in areas like delinquency or loan loss forecasting, expected credit losses capital computation under advanced approaches.
5. Above average to advanced excel skills

Experience in projects involving automation / data consolidation in the areas of risk or financial reporting would be an advantage

• CA or MBA with FRM preferred
• Understanding analysis of various types of credits
• Proven management and supervisory skills
• Excellent interpersonal skills, verbal/written communication skills and strong project management skills
• Above average to advanced excel skills
• Experience in working with Python, SQL or SAS would be an added advantage.