Algo OpData

Nearly 12,000 publicly-reported operational risk losses populate the Algo OpData quantitative loss database, making it the most complete operational loss resource available today. Algo OpData is a key component of the capital modeling process, supplementing internal loss data in order to populate 'tail' (high severity, low frequency) events so that firms may gain insights into risks they have yet to experience.

Algo OpData is designed to supplement internal loss data for capital modeling purposes and serves as an important tool for validating capital results. Exposure data for the top 500 banks is available and includes total assets, total equity, total revenues, total deposits, and number of employees. Losses in the Algo OpData database are categorized according to the Basel Committee on Banking Supervision's (Basel II) definition of operational risk and its event type hierarchy. In most cases, losses are grouped at the activity level (Level 3), as well as according to the eight standard business lines.