Operational Risk: Definition, Data, and the Regulatory Landscape

Basel II introduced a formal capital charge for operational risk for the first time, forcing banks to measure and model a risk class for which data are sparse and extreme events are genuinely rare. The regulatory framework offers three approaches of increasing sophistication, ranging from the one-size-fits-all basic indicator (BI) approach to the bank-specific advanced measurement approach (AMA), where the capital charge is derived from the bank's own loss distribution model.

This note covers the regulatory structure, the Basel definition and event taxonomy, and the empirical challenges of operational loss data — the heavy tails, non-stationary frequency, and extreme data scarcity that make operational risk the most statistically challenging of the three Basel risk classes.

• state the Basel II definition of operational risk and name the seven event types and eight business lines;
• write the BI and standardized capital charge formulas and explain their limitations;
• describe the AMA/LDA structure and the data warehouse it requires;
• state the three empirical stylized facts about operational loss data and explain why each matters for modelling.

1. 1. The Basel II definition and taxonomy
2. 1. The elementary approaches
3. 1. The advanced measurement approach (AMA)
4. 1. Operational loss data: stylized facts