Failure to Monitor and Manage Risk

Based on its communication with the top management and in line with their business objectives, the firms will decide to assume certain risks while mitigate, transfer or ignore the other risks. It’s the job of the risk management to ensure that this happens.

To do so, risk managers are required to constantly monitor the risk activity of the firm, and take necessary actions where required.

Financial firms have exposure to many derivative positions and instruments with embedded derivatives. Some of these products are extremely sensitive to changes in market conditions. Therefore, even if the firm doesn’t make any new trades or changes in its positions, the risk profiles of these existing positions can change drastically. For example, a position with a positive exposure could turn negative very quickly and that too with a very small change in a market variable such as interest rates.

This makes the job of monitoring and hedging these risks on a continuous basis very difficult. The risk managers may fail to do their job efficiently just because how quickly the risk profiles change and how very small changes in markets drive these changes.

The risk manager may have to identify possible scenarios and build solutions that could be implemented to reduce risks quickly. They may also be required to have contingency hedging plans in place.

Apart from this, we also have the problem of hidden risks. Especially in large organizations, it is possible for traders to take risks that can remain hidden for a long time. This could happen if the positions are created in such a way that the risks are not detected by the risk management systems.

A firm could design and organize its risk management function in such a way that it recognizes and identifies all risks, but that could become extremely expensive, and may also hurt the innovativeness and flexibility of the firm.

This article is based on the paper “Risk Management Failures: What are They and When Do They Happen?” by Rene M. Slutz, which is a part of the FRM syllabus.

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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.