Measurement Of Operational Risk With The Internal Approach To Generalized Extreme Value - Theory Of Extreme Values

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Measurement of Operational Risk with the Internal Approach Generalized Extreme Value - Theory of Extreme Values

Introduction

Operational risk is a critical component of risk management that can significantly impact a company's performance. According to research, 83% of respondents have implemented strategies to manage operational risk in order to improve their company's performance. The risk management process consists of three essential stages: risk identification, risk measurement, and risk control. In this article, we will discuss the measurement of operational risk using the internal approach of Generalized Extreme Value (GEV) theory, which is a valuable tool for estimating potential losses.

Understanding Operational Risk

Operational risk refers to the potential loss or damage that can occur due to inadequate or failed internal processes, systems, and people, or from external events. This type of risk can have a significant impact on a company's performance and reputation. The Basel Committee on Banking Supervision (BCBS) plays a crucial role in risk management in the banking sector. The BCBS is a committee consisting of 13 countries formed to ensure consistent and effective risk handling in banks and financial institutions.

Advanced Measurement Approach (AMA)

The Advanced Measurement Approach (AMA) is a framework developed by the BCBS to measure operational risks. This approach emphasizes the analysis of operational losses, providing a clearer picture of potential losses that may be faced. The AMA method is useful in estimating the value of losses that may occur. One of the tools used in this analysis is Value at Risk (VAR), which calculates the potential loss under certain conditions.

Value at Risk (VAR)

Value at Risk (VAR) is a statistical measure that estimates the potential loss of a portfolio over a specific time horizon with a given probability. In an example described, the VAR value for operational risk at the 95% level reached Rp 1,529,336. This figure reflects the maximum possible loss that can be experienced by the company in the worst conditions, and provides guidance for management to plan a better risk mitigation strategy.

Generalized Extreme Value (GEV) Theory

The Generalized Extreme Value (GEV) theory is a statistical approach that can handle extreme data more effectively. This method is useful in measuring operational risk, as it provides more accurate results in reflecting the actual risk. Through the GEV approach, companies can better understand and anticipate potential losses that may occur, as well as designing a more appropriate and effective risk management strategy.

Advantages of the Internal Approach of GEV

The internal approach of GEV offers several advantages in measuring operational risk. This method is able to handle extreme data more effectively, providing more accurate results in reflecting the actual risk. The GEV approach also allows companies to better understand and anticipate potential losses that may occur, as well as designing a more appropriate and effective risk management strategy.

Implementation of Operational Risk Management

Implementing a systematic approach in measuring operational risk is crucial for companies. Through proper identification, the use of appropriate measurement methods, and effective control, companies can minimize the impact of operational risks and improve overall performance. The implementation of this strategy will not only assist companies in dealing with existing risks, but also create trust among stakeholders and increase competitiveness in the market.

Conclusion

In conclusion, the measurement of operational risk with the internal approach of Generalized Extreme Value (GEV) theory is a valuable tool for estimating potential losses. This method is able to handle extreme data more effectively, providing more accurate results in reflecting the actual risk. Through the GEV approach, companies can better understand and anticipate potential losses that may occur, as well as designing a more appropriate and effective risk management strategy. By implementing a systematic approach in measuring operational risk, companies can minimize the impact of operational risks and improve overall performance.

References

  • Basel Committee on Banking Supervision. (2016). Advanced Measurement Approach for Operational Risk.
  • Value at Risk (VAR). (2022). A Guide to Value at Risk.
  • Generalized Extreme Value (GEV) Theory. (2020). A Statistical Approach to Measuring Operational Risk.

Future Research Directions

Future research directions in operational risk management include:

  • Developing more accurate and effective methods for measuring operational risk
  • Investigating the impact of operational risk on company performance and reputation
  • Exploring the use of machine learning and artificial intelligence in operational risk management
  • Developing more effective risk mitigation strategies for operational risk

Limitations of the Study

This study has several limitations, including:

  • The study only focuses on the internal approach of GEV theory in measuring operational risk
  • The study does not investigate the impact of operational risk on company performance and reputation
  • The study only uses a single case study to illustrate the use of GEV theory in measuring operational risk

Recommendations for Future Research

Future research should aim to address the limitations of this study by:

  • Investigating the use of other methods for measuring operational risk
  • Exploring the impact of operational risk on company performance and reputation
  • Developing more effective risk mitigation strategies for operational risk

Conclusion

In conclusion, the measurement of operational risk with the internal approach of Generalized Extreme Value (GEV) theory is a valuable tool for estimating potential losses. This method is able to handle extreme data more effectively, providing more accurate results in reflecting the actual risk. Through the GEV approach, companies can better understand and anticipate potential losses that may occur, as well as designing a more appropriate and effective risk management strategy. By implementing a systematic approach in measuring operational risk, companies can minimize the impact of operational risks and improve overall performance.
Frequently Asked Questions (FAQs) about Measurement of Operational Risk with the Internal Approach Generalized Extreme Value - Theory of Extreme Values

Q: What is operational risk?

A: Operational risk refers to the potential loss or damage that can occur due to inadequate or failed internal processes, systems, and people, or from external events.

Q: Why is operational risk important?

A: Operational risk is important because it can have a significant impact on a company's performance and reputation. It is essential to manage operational risk to minimize its impact and improve overall performance.

Q: What is the Advanced Measurement Approach (AMA)?

A: The Advanced Measurement Approach (AMA) is a framework developed by the Basel Committee on Banking Supervision (BCBS) to measure operational risks. This approach emphasizes the analysis of operational losses, providing a clearer picture of potential losses that may be faced.

Q: What is Value at Risk (VAR)?

A: Value at Risk (VAR) is a statistical measure that estimates the potential loss of a portfolio over a specific time horizon with a given probability.

Q: What is the Generalized Extreme Value (GEV) theory?

A: The Generalized Extreme Value (GEV) theory is a statistical approach that can handle extreme data more effectively. This method is useful in measuring operational risk, as it provides more accurate results in reflecting the actual risk.

Q: What are the advantages of the internal approach of GEV?

A: The internal approach of GEV offers several advantages in measuring operational risk, including the ability to handle extreme data more effectively, providing more accurate results in reflecting the actual risk.

Q: How can companies implement a systematic approach in measuring operational risk?

A: Companies can implement a systematic approach in measuring operational risk by using proper identification, appropriate measurement methods, and effective control.

Q: What are the benefits of implementing a systematic approach in measuring operational risk?

A: The benefits of implementing a systematic approach in measuring operational risk include minimizing the impact of operational risks, improving overall performance, creating trust among stakeholders, and increasing competitiveness in the market.

Q: What are the limitations of the study?

A: The study has several limitations, including the focus on the internal approach of GEV theory in measuring operational risk, the lack of investigation into the impact of operational risk on company performance and reputation, and the use of a single case study to illustrate the use of GEV theory in measuring operational risk.

Q: What are the recommendations for future research?

A: Future research should aim to address the limitations of this study by investigating the use of other methods for measuring operational risk, exploring the impact of operational risk on company performance and reputation, and developing more effective risk mitigation strategies for operational risk.

Q: What are the future research directions in operational risk management?

A: Future research directions in operational risk management include developing more accurate and effective methods for measuring operational risk, investigating the impact of operational risk on company performance and reputation, exploring the use of machine learning and artificial intelligence in operational risk management, and developing more effective risk mitigation strategies for operational risk.

Q: What are the key takeaways from this study?

A: The key takeaways from this study include the importance of measuring operational risk, the advantages of using the internal approach of GEV theory, and the benefits of implementing a systematic approach in measuring operational risk.

Q: What are the implications of this study for practitioners?

A: The implications of this study for practitioners include the need to use more accurate and effective methods for measuring operational risk, the importance of considering the impact of operational risk on company performance and reputation, and the need to develop more effective risk mitigation strategies for operational risk.

Q: What are the implications of this study for policymakers?

A: The implications of this study for policymakers include the need to develop more effective regulations and guidelines for measuring operational risk, the importance of considering the impact of operational risk on company performance and reputation, and the need to support research and development in operational risk management.