Citi Group CCAR Model Development - C11 GURGAON 

India, Haryana, Gurugram 

953494348

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  Job Description
  Comprehensive Capital Analysis Review (CCAR) is an annual regulatory submission to US Federal Reserve Board (FRB). It is used to ensure that institutions have robust, forward-looking capital planning processes that account for their unique risks and sufficient capital to continue operations throughout times of economic and financial stress. As part of CCAR, the Federal Reserve evaluates institutions' capital adequacy, internal capital adequacy assessment processes, and their plans to make capital distributions, such as dividend payments or stock repurchases.Responsibilities:Development of econometric forecasting models for keyassociated interest rate risk metrics.
  Developing Champion and Challenger models using different time series forecasting methodologies to comply with SR 15-18 guidance.
  Development of Benchmark models using Industry data series to meet regulatory requirementsResponsible for understanding changes to quantitative requirements published by MRM in Model Testing Guidance and presenting the key changes to senior model development leads. Also, be a champion in addressing observations raised by MRM and Internal Audit in a quantitative manner by thinking out-of-box.model runs under different scenarios provided by Economic Scenario Group.Responsible for writing model development documentation and partner with Model Risk Management (MRM) to address their feedback.Qualifications / skill sets:3-5 years of relevant statistical /business experience in financial services
  Strong understanding of statistical techniques such as
  Ordinary Least Square regression (OLS), Fixed-effect Panel Regression, Error Correction Models, Seemingly Unrelated regression and Cointegration.
  Understanding of Machine learning algorithms will be a plus
  Hands-on experience in programming and modeling using
  SAS, Python and R is preferred.
  Follow a culture of accountability and strict quality control of the data integrity and modeling processMust be able to present technical matters in a way that is meaningful to the audienceEducation:Masters / PhD in quantitative discipline such as Statistics, Economics or related discipline .

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