COMPG007 - Operational Risk Measurement for Financial Institutions

This database contains 2017-18 versions of the syllabuses. For current versions please see here.

CodeCOMPG007 (also taught as COMPM007)
PrerequisitesStudents not on MSc FRM or MSc FM should check with the module tutor.
Taught ByAriane Chappelle (100%)
AimsThe module aims to familiarise students with key concepts in the measurement and management of operational risk in the financial services. It will help them to understand the current issues and challenges faced by the sector, from a methodological, regulatory and financial standpoint. By detailing the most current debates in the field, the course aims at allowing the students to subsequently become positive agents of solutions in the market place and in research in operational risk.
Learning Outcomes

Students will be able to select and apply the relevant methods to tackle issues in risk assessment, measurement and aggregation. On successful completion of the course, students should have a sound understanding of:

  • the applications of essentials of data analysis and statistical estimation to operational risk measurement;
  • the methods of scenario analysis, stress testing and regulatory capital assessment;
  • the limitations of operational risk modelling and the ways to address them;
  • some of the essential features of operational risk management in financial institutions and how quantification can support decision-making.


The course is intended to introduce applied statistics to operational risk measurement and management in the financial services. The course is primarily focused on the techniques, impacts and benefits of using relevant statistical and analytical methods to support effective risk management in banks and insurance companies.

The syllabus consists of the following parts:

  1. Operational Risk Scope and Regulation
    Regulation on operational risk, Capital and consequences for the financial industry. Large events and loss overview.
  2. Operational Risk data analysis
    Internal and External loss data, distribution, tail risk, reporting and threshold and cut-off mix between internal and external data for loss distribution.
  3. Scenario analysis and stress testing
    Scenario identification and assessment process; Probabilities of rare events; Fault trees and event trees; Mixing quantitative and qualitative data. Stress testing Capital and financial robustness. Bayesian Techniques in operational risk
  4. Risk correlations and indicators
    Identification and selection of risk drivers. Correlations and determinants of losses.
  5. Risk aggregation and diversification
    Aggregating data from different sources, loss generating mechanisms, scaling and filtering of data. Copula-based approach for risk diversification; extreme value theory. Remaining issues in operational risk modeling.
  6. Risk Reporting
    Communicating risk assessment outcomes. Supporting decision-making through risk reporting.

Method of Instruction

Course will be delivered through 30 hours of lectures. On occasions, scholars and top practitioners in the field will be invited as guest speakers for an hour in the course.

Besides the lectures, students will be asked to read additional references, academic articles and book parts. Those readings will be particularly useful to prepare their course work.

Students will get to work on real industry cases for class exercises and individual assignments.

Evaluation: 50% from 2 individual tests (25% each), 50% from coursework: 6,000 words essay on a chosen topic out of a list distributed in lecture 1. Coursework are individual or group work of two students maximum.


The course has the following assessment component:

  • Coursework (6000 words, 50%)
  • 2x In-class Test (25% each)

To pass this course students must:

  • Obtain at least an overall pass mark of 50%.


Reading list available via the UCL Library catalogue.