
Answer-first summary for fast verification
Answer: Using external data obtained from other banks with size adjustments.
## Explanation **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 need to be adjusted for size, based on the relative size of the banks' revenues, before being merged with the bank's internal data. **A is incorrect** because using distributions does not help resolve the issue of incomplete underlying data - it only provides a modeling framework but doesn't address the fundamental data scarcity problem. **B is incorrect** because: - Lognormal distributions (not Poisson distributions) are generally used for modeling loss severity - Poisson distributions are typically used for modeling loss frequency - Using distributions alone doesn't resolve the underlying data insufficiency issue **C is incorrect** because external data from other banks must be adjusted for size differences between institutions to be meaningful and comparable. The size adjustment is crucial because operational loss data from larger banks typically shows higher loss amounts, and these need to be scaled appropriately to be relevant for smaller institutions.
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What is a good way to increase the data set of historical operational losses when internal data is insufficient?
A
Using distributions to model the data gaps.
B
Using Poisson distributions for modeling loss severity.
C
Using external data from other banks without any adjustments.
D
Using external data obtained from other banks with size adjustments.
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