BCBS 239: Best Practices in Risk Data Aggregation

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Course Features

  • Course date:11/14/2019
  • Course Duration: 2 Day
  • Level: Beginner-intermediate
  • Prerequisites: None
  • Method: Live & Virtual
  • Venue: MicroTek
  • Time: 9:00 am – 5:00 pm
  • Dress Code: Business Casual
  • Category:
  • Certificate: Yes
  • CPE Credits: 14
  • Course Code: 105

BCBS 239: Best Practices in Risk Data Aggregation

The Basel Committee prepared the ‘Principles for Effective Risk Data Aggregation and Risk Reporting’ in 2013, because in the years leading to the global financial crisis, banks’ information technology and data architecture were inadequate to support prompt and accurate identification and measurement of financial risks such as credit, market, operational, and liquidity risks.

Until the market has proof that banks’ data are accurate, appropriate, complete, and timely, there is little reason to believe stress results and that banks would be sufficiently capitalized in a time of stress.  Additionally, without strong data aggregation, banks’ capital ratios, liquidity and leverage buffers, and the content of living wills cannot be trusted.

Course Objectives

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

  • Describe the role of the Financial Stability Board and the Basel Committee for Banks Supervision
  • Define risk data aggregation
  • Enumerate and describe the Basel Committee’s ‘Principles for Effective Risk Data Aggregation and Risk Reporting’
  • Discuss FDIC and Federal Reserve requirements for living wills
  • Identify Federal Reserve requirements for CCAR, CLAR, and stress tests
  • Evaluate bank examiner requirements for pricing and capital models
  • Describe challenges to effective risk data aggregation
  • Discuss best practices to achieve BCBS 239 compliance


Module I        Global and Domestic Standard Setters and Data Aggregation

  • Describe role of the Financial Stability Board
  • Identify responsibilities of the Basel Committee for Bank Supervision
  • The US’ Financial Stability Oversight Council

Module II       Basel III Data Requirements

  • Identify data requirements for
    • Capital ratios and other buffers
    • Credit, market, and operational risk models
  • Describe data requirements for Pillar II and III

 Module III     Dodd-Frank and Data

  • Explain Basel III and Dodd-Frank intersection
  • Discuss relevant data intensive Dodd-Frank Title I components and their requirements
    • Capital ratios and other buffers
    • Comprehensive Capital Adequacy Reviews (CCAR)
      • Federal Reserve Requirements
    • Comprehensive Liquidity Asset Review (CLAR)
    • Dodd-Frank Act Stress Tests (DFAST)
      • Federal Reserve Requirements
    • Living wills
      • FSB’s Key Attributes of Effective Resolution Regimes
      • FDIC Guidelines

Module IV      Basel’s Principles for Data Aggregation and Risk Reporting

  • Define data aggregation
  • Enumerate and describe the fourteen principles

Module V       Banks Progress on Data Aggregation

  • Identify how banks are coping with organizational challenges
    • Multiple requests for stress testing resources
    • Board engagement
    • Silo mentality
    • Modeling risk interaction
    • Data granularity
  • Discuss findings in recent surveys by
    • The Basel Committee
    • Markit

Module VI      IT Architecture

  • Discuss developments in IT teams at large banks
  • Compare and contrast necessary data and systems needs to meet BCBS 239
  • Identify capabilities to address entire balance sheet
  • Evaluate necessary stress testing framework and governance

Module VII    Auditing and Examining Internal Credit, Market, and Operational Risk Models

  • Describe OCC’s SR Letter 11-7 & its impact on all banks
  • Discuss best practices to audit and examine banks’ internal models
    • Credit risk models- Black-Scholes Merton, Risk migration frameworks, CVaR
    • Market risk models – VaR and Expected Shortfall frameworks
  • Identify relationship between models and Basel III formulae
  • Evaluate banks’ practices in input selection, model creation and validation, and how banks use models
  • Describe what bank regulators, auditors and internal controls personnel should be looking for in
    • auditing and examining internal models

Summary Conclusion and Question and Answer Session



Bad Risk Data Could Be Big Banks’ Downfall

Risk Data Aggregation: Why Regulators and Banks Are Finally Paying Attention



  • Mayra Rodríguez Valladares is the Managing Principal of MRV Associates.  She specializes in training and consulting solutions for Basel III, Dodd-Frank, risk management, financial derivatives, capital markets, foreign exchange, and corporate finance.  She has worked with the private sector and foreign central banks in the US, UK, Latin America Eastern Europe, Central, and Southeast Asia, …
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