Auditing & Evaluating Banks’ Risk Models: A Non-Quantitative Approach

March 6-7, 2017, New York City   Seminar Location

July 12-13, 2017, New York City  Seminar Location

November 8-9, 2017, New York City  Seminar Location

Many classes sell-out; we suggest registering at least two weeks in advance to ensure your seat.

Hours9:00 am – 5:00 pm; Registration/Breakfast: 8:30 am; Dress Code: Business Casual

CPE Credits: 14
Level: Basic/


Prerequisites: None
Method: Group Live

This course is designed for market professionals who do not come from quantitative backgrounds and who need to audit or examine banks risk models. In this interactive class, participants will learn about widely used credit, market, liquidity, and operational risk models that are used to measure these risks for internal bank purposes and to calculate banks’ economic and regulatory capital. Relevant cases and articles will be discussed.

Course Objectives

At the end of this course, participants should be able to:

  • Identify different risk models used by banks
    •  Credit, market, liquidity, and operational
  • Define risk data aggregation and its importance
  • Discuss best practices in auditing and examining banks’ risk models

Module I — Data and Systems

  • Define risk data aggregation
  • Identify key Basel Committee risk data aggregation principles
    • BCBS 239
  • Evaluate banks’ ability to comply with risk data principles

Module II — Credit Risk Models

  • Describe inputs necessary to measure credit risk
    • PD, LGD, and EAD
  • Discuss different ways that market participants derive credit risk inputs
  • Calculate Expected Loss and Unexpected loss
  • Discuss mapping of internal ratings into external ratings
  • Compare and contrast widely used credit risk models
    • Credit migration
    • CVaR
    • Merton models

Case: Long Term Capital Management and Management’s View of Sovereign Risk in Modeling 

Module III — Market Risk Models

  • Compare and contrast market risk in the banking book and trading book
  • Discuss different models to calculate interest rate risk in the banking book
  • Identify methodologies to calculate Value-at-Risk for the trading book
    • Traditional approaches
    • Notional amount
    • Value of a basis point and duration (bond market)
    • Value-at-Risk concept
    • Definition of VaR
      • Specified maximum loss
      • Specified time period
      • Specified probability
    • Calculating VaR
      • Variance-covariance approach
      • Monte Carlo approach
      • Historical simulation
      • Advantages & disadvantages
  • Establish important elements in backtesting
  • Compare and contrast Expected Short-Fall with VAR
  • Highlight key Basel III requirements in market risk models

Case Study: JP Morgan’s ‘Whale’ and VaR 

Module IV — Operation Risk Models

  • Discuss differences in internal and external loss data aggregation
  • Identify advantages and shortcomings of
    • Top-down models
    • Bottom-up models
  • Compare and contrast Basel Committee operational risk measurement methodologies
  • Discuss potential changes in Basel Committee guidance to measuring operational risk

Module V — Asset Liability Management and Capital Models

  • Identify typical ALM models
  • Discuss economic and regulatory capital models
    • Recent trends in light of Basel III and Dodd-Frank’s Title I

Module VI — Best Practices in Auditing and Examining Models

  • Discuss Basel committee model guidelines
  • Discuss key elements of ‘Guidance on Model Risk Management’ (SR 11-7)
    • OCC and Federal Reserve guidance
    • Model development, validation, implementation, and use
  • Define model governance and its application
  • Identify key policies, procedures, and internal controls necessary in model risk management
  • Evaluate importance of documentation and maintaining a model inventory

Exercise: Groups will create a questionnaire to guide them in auditing or examining banks’ risk models.

Summary Conclusion and Question and Answer Session

US $1695.00

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