VP; Quantitative Methodology, Counter-Party Credit

New York,, NY

Brief Description:

Support methodologies related to CCAR capital calculation and regulatory filing. This includes leading the specification, implementation, performance monitoring and maintenance of these methodologies.  

Job Function:

  • Support Counterparty Credit Risk methodology development and implementation for trading products, including OTC derivatives, exchanged traded derivatives, TBA and SFT. CCR risk methodologies include, but not limited to, exposure simulation models, model calibration, derivative pricing models, CVA models, as well as Risk Not in CVA.
  • Facilitate the quarterly CCAR run for ongoing regulating filing.
  • Provide risk modeling transparency. This is primarily facilitated by the completion of significantly enhanced documentation for the risk models that will satisfy the emerging regulatory expectations (for example, SR-11-7 guidelines published by the Fed).

Methodology Maintenance and Monitoring

  • Remediate model issues from internal validation, internal audit as well as external regulators.
  • Re-submit model white papers on regular basis with portfolio and model features update
  • Maintenance the existing models. This includes ensuring adequate review of the assumptions on an ongoing basis, timely calibration of the models and monitoring of model limitations. This also may include benchmarking against other alternatives, taking appropriate actions as informed from the model performance tracking and/or the independent review performed by the Enterprise Model Risk Management group.

Coordinate with internal stake holders and external regulators

  • Interact with CCAR IT, Risk IT, Global Risk Analytics and US Enterprise Market Risk teams to implement end-to-end automation of CVA and FVA calculation for CCAR reporting.
  • Interact with other CCAR work streams to ensure consistency in methodologies and key assumptions across CCAR program.
  • Interact with regulators regarding stress testing methodology and analysis for counterparty credit risk. Provide comprehensive explanation of the stress testing results to the risk managers and senior management.
  • Interact with market data work streams to ensure the accuracy and completeness of the market data used to support the various models. Market data is a key underlying component for the all key risk models, and is accordingly a critical area of focus under CCAR. The work related to market data will involve a significant amount of effort and change in order to comply with the Regulatory expectations.



  • Experiences and knowledge of regulatory requirements and stress testing of counterparty risk of financial institutions. Good product knowledge across fixed income, equity and derivative instruments.
  • Masters in Financial, Engineering or equivalent.
  • PhD in Finance, Engineering or Applied Sciences.
  • Preferred: Quantitative modeling skill in counterparty credit risk.

Contact Details:

Dan Alzapiedi