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Operational risk loss data is not easy to collect within an institution, especially for extreme loss data. Therefore, financial institutions usually attempt to obtain external data, but doing so may create biases in estimating loss distribution. Which of the following statements regarding characteristics of external loss data is incorrect?

A) External loss data often exhibits scale bias as operational risk losses tend to be positively related to the size of the institution (i.e., scale of its operations).

B) External loss data often exhibits truncation bias as minimum loss thresholds for collecting loss data are not uniform across all institutions.

C) External loss data often exhibits data capture bias as the likelihood that an operational risk loss is reported is positively related to the size of the loss.

D) The biases associated with external loss data are more important for large losses in relation to a bank’s assets or revenue than for small losses.

答案：D

解析：The biases associated with external loss data are important for all losses in relation to a bank’s assets or revenue.

Even though risk managers cannot eliminate model risk, there are many ways managers can protect themselves against model risk. Which of the following statements about managing model risk is correct?扫码咨询

A) Models should be tested against known problems.

B) It is not advisable to estimate model risk using simulations.

C) Complex models are generally preferable to simple models.

D) Small discrepancies in model outputs are always acceptable.

答案：A

解析：One way to protect against model risk is to test a model against known problems. It is always a good idea to check a model against simple problems to which one already knows the answer, and many problems can be distilled to simple special cases that have known answers. If the model fails to give the correct answer to a problem whose solution is already known, then this indicates that there is something wrong with it.

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