Effective Risk Data Aggregation and Risk Reporting

The financial crisis that began in 2007 revealed that many banks, including global systemically important banks (G-SIBs), were unable to aggregate risk exposures and identify concentrations fully, quickly and accurately. This meant that banks' ability to take risk decisions in a timely fashion was seriously impaired with wide-ranging consequences for the banks themselves and for the stability of the financial system as a whole.

The Basel Committee's Principles for effective risk data aggregation will strengthen banks' risk data aggregation capabilities and internal risk reporting practices. Implementation of the principles will strengthen risk management at banks - in particular, G-SIBs - thereby enhancing their ability to cope with stress and crisis situations.

Download PDF - Principles for effective risk data aggregation and risk reporting

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.