Comprehensive and Detailed In-Depth Explanation:
Scenario analysis in operational risk involves constructing hypothetical loss events to estimate potential impacts. Sampling bias occurs when the scenarios selected do not represent the full range of possible outcomes (e.g., over-relying on historical data or excluding rare events), skewing risk estimates. Optimism bias (A) involves underestimating risks, motivation bias (D) reflects personal incentives, anddeterminable bias (C) isn't a recognized term. Basel II's AMA encourages diverse data sources to mitigate sampling bias in scenario analysis.
Exact Extract from Official Source:
* BCBS, "Basel II: International Convergence of Capital Measurement and Capital Standards," June
2006, para. 672: "Scenario analysis should incorporate a range of plausible events... Banks must avoid biases such as sampling bias, which can arise from unrepresentative data selection."
* GARP FRR Study Notes, Operational Risk Section: "Sampling bias in scenario analysis occurs when the chosen scenarios fail to capture the full spectrum of operational risk events, leading to under- or overestimation of potential losses." Reference:BCBS, "Basel II," para.672; GARP FRR Study Notes, Operational Risk Section.