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Review of Capital Adequacy Requirements for Operational Risk (Orca) for Insurance Companies

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Review of Capital Adequacy Requirements for Operational Risk (Orca) for Insurance Companies
1. Introduction
The main objective of the review is to analyse the assessment of operational risk in life insurance companies and the process to develop a framework to assess the capital requirements relating to operational risk, taking into account the capital requirements of other risks and their interaction.

2. Summary
What is Operational Risk?
Operational Risk is one of the six risk categories in the Prudential Sourcebook (PSB), along with credit risk, market risk, liquidity risk, group risk and insurance risk.
 It is described as "the risk of loss resulting from inadequate or failed internal processes, people and systems, or from external events".

Benefits from assessing, monitoring and controlling organisations Operational Risk exposures:
 Management can make conscious decisions about what risks they want to accept, what risks they want to eliminate or reduce and what risks they wish to transfer.
 By measuring the risks, the benefits of their actions can be monitored.
 By analysing the Operational Risk losses, trends can be identified, lessons can be learned and appropriate action can be taken.
 Management controls can be enhanced to reduce the possibility of losses.

Operational Risk CAR Challenges:
 The risks involved, and their individual circumstances and loss amounts, are potentially extremely varied and relatively infrequent in occurrence.
 Operational risks are typically long-tailed and model results can be highly sensitive to assumptions.
 Defining what an Operational Risk (OR) loss is. An OR event can impact many aspects of an insurance company’s operations, particularly claims and expense experience. It is not easy to separate out how much of the experience variations are as a result of OR events.
 It is not always easy to identify what the impact is or has been once an OR event has been identified. Therefore the data that one might want for rigorous statistical analysis and modeling of OR is not currently

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