Loss Distribution Approach for Operational Risk Capital Modelling under Basel II: Combining Different Data Sources for Risk Estimation

TL;DR

This paper reviews methods for integrating internal, external, and scenario data sources in the Loss Distribution Approach for operational risk capital modeling under Basel II, addressing key methodological challenges.

Contribution

It provides a comprehensive review of existing techniques for combining diverse data sources in LDA, highlighting unresolved methodological issues.

Findings

Various data integration methods are discussed and compared.

Challenges in combining data sources are identified and analyzed.

The review informs best practices for operational risk modeling under Basel II.

Abstract

The management of operational risk in the banking industry has undergone significant changes over the last decade due to substantial changes in operational risk environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for banking Supervision has developed a regulatory framework, referred to as Basel II, that introduced operational risk category and corresponding capital requirements. Over the past five years, major banks in most parts of the world have received accreditation under the Basel II Advanced Measurement Approach (AMA) by adopting the loss distribution approach (LDA) despite there being a number of unresolved methodological challenges in its implementation. Different approaches and methods are still under hot debate. In this paper, we review methods proposed in the literature for combining different data sources (internal data, external data and scenario analysis) which is one of the regulatory requirement for AMA.