Recommendations for Improving Control Environment at AIB/Allfirst

Below are the recommendations with respect to improving the control environment at Allfirst and AIB. The controls in AIB should be benchmarked against these to ensure consistency

  • First, business strategy in the trading areas should be reconsidered, specially proprietary trading. The scope and location of all proprietary trading activity within the AIB Group should be carefully reconsidered. Trading activities should be limited only to those markets where AIB has a real competitive advantage.

  • Second, AIB should conduct a careful and thorough review of risk management architecture

  • Third, there should be changes in the relationship between Allfirst and AIB. Lines of reporting for Allfirst treasury and other functions, particularly risk taking functions, should be crystal clear. There should be greater representation on the Allfirst Board by non-management directors of AIB and at least one such member should sit on the Allfirst audit committee.

  • Fourth, AIB and Allfirst should conduct personnel reviews in light of the management and control failures that have been identified. Our findings make clear that AIB and Allfirst should review each and every member of the Allfirst Treasury department to determine if they have the necessary expertise to remain in their positions.

  • Finally, if any proprietary trading and client-trading activities continue at Allfirst, they should be conducted only under the most controlled circumstances. The same types of rigorous controls should be applicable throughout the AIB Group wherever proprietary trading is conducted.

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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.