A

问题如下：

An operational risk analyst is attempting to estimate a bank’s loss severity distribution. However, there is a limited amount of historical data on operational risk losses. Which of the following is the best way to address this issue?

选项：

A.

Generate additional data using Monte Carlo simulation and merge it with the bank’s internal historical data.

B.

Estimate the parameters of a Poisson distribution to model the loss severity of operational losses.

C.

Estimate relevant probabilities using loss information that is published by credit rating agencies.

D.

Merge external data from other banks with the bank’s internal data after making appropriate scale adjustments.

解释：

中文解析：

使用从其他银行获得的外部数据是增加历史经营损失数据集的一种好方法。其他银行的数据在与银行内部数据合并之前需要调整大小。所以D正确

D is correct. Using external data obtained from other banks is one good way to increase the data set of historical operational losses. Data from other banks needs to be adjusted for size before being merged with the bank's internal data.

A is incorrect. Using distributions does not help resolve the issue of incomplete underlying data.

B is incorrect. Lognormal distributions, not Poisson distributions, are generally used for modeling loss severity. Also, using distributions does not help resolve the issue of incomplete underlying data.

C is incorrect. Credit losses are generally much better documented than operational losses inside the bank. External credit ratings publish probability of default and expected loss data that provides additional data. Operational loss is generally documented much less rigorously, and regulatory initiatives are now pushing banks to document operational loss data.