The data available to estimate the statistical distribution of bank losses is difficult to assemble for which of the following reasons?

The data available to estimate the statistical distribution of bank losses is difficult to assemble for which of the following reasons?

I. The needed data is vast in quantity.

II. The data requires bringing together significantly different measures of risk.

III. Some risks are difficult to quantify and hence the data might involve subjective elements.
A . I, II
B . I, III
C . II, III
D . I, II, III

View Answer

Answer: D

Explanation:

Estimating the statistical distribution of bank losses is challenging due to several factors:

I. The needed data is vast in quantity: Gathering comprehensive data covering all potential risk factors and historical loss events is extensive.

II. The data requires bringing together significantly different measures of risk: Banks face multiple types of risks (e.g., credit, market, operational) which need to be integrated into a single cohesive loss distribution model.

III. Some risks are difficult to quantify and hence the data might involve subjective elements: Certain risks, particularly operational and reputational risks, are inherently difficult to measure and may require judgment and subjective assessment.

All these factors make assembling the necessary data for accurate loss distribution estimation complex.

References: How Finance Works, discussions on risk measurement and data challenges in banking??.