Program Overview

Quantitative Operational Risk Modelling (STAT0020)

Key Information

• Faculty: Faculty of Mathematical and Physical Sciences
• Teaching department: Statistical Science
• Credit value: 15
• Restrictions: This module is also open to students from the MSc Financial Mathematics and MSc Financial Risk Management degree programmes and, subject to the availability of places, is offered as an elective to students specialising in other fields.

Alternative Credit Options

There are no alternative credit options available for this module.

Description

This module aims to develop a practical understanding of operational risk modelling in both the banking and insurance sectors under the Basel II/III and Solvency II regulatory frameworks. It is primarily intended for third and fourth year undergraduates and taught postgraduates registered on the degree programmes offered by the Department of Statistical Science (including the MASS programmes).

Intended Learning Outcomes

• Be able to understand the fundamentals of risk modelling with a specific focus on practical applications in operational risk and insurance contexts.
• Be able to gain insight into regulatory frameworks, including Basel II/III and Solvency II, while applying basic indicator, standardized, and advanced measurement approaches.
• Be able to apply advanced techniques, including loss distribution approach (LDA) models for tail risks, truncation and splicing methods for accurate risk assessment, and parameter estimation techniques using real-world insurance examples.
• Have a deeper theoretical understanding of the LDA modelling techniques (Level 7 only).

Applications

An integral part of modern financial risk involves operational risk, the third key risk type that financial institutions must model and hold capital for according to the international banking regulations of Basel II/III. The key set of concepts and mathematical modelling tools developed in this module will equip students with the appropriate mathematical and statistical background to undertake core modelling activities required in risk management, capital management and quantitative modelling in modern financial institutions.

Indicative Content

• Basic indicator, standardized, and advanced measurement approaches.
• Loss Distributional Approach (LDA): quantiles, moments, frequency and severity distributions, heavy-tailed models, convolutions, characteristic functions, truncated and censored data modelling.
• Measures of risk: coherent and convex risk measures, comonotonic additive measures, value-at-risk, expected shortfall, spectral risk measures.
• Modelling dependence: dependence in the LDA framework, frequency and severity dependence.
• Loss aggregation: calculation of annual loss distribution. The module will use programming or readily available packages where possible within the operational risk framework to make theoretical concepts more practical and applicable.

Module Deliveries for 2026/27 Academic Year

Intended Teaching Term: Term 2

Undergraduate (FHEQ Level 6)

Teaching and Assessment

• Mode of study: In person
• Methods of assessment:
  • 80% Exam
  • 20% Group activity
• Mark scheme: Numeric Marks

Other Information

• Number of students on module in previous year: 34
• Module leader: Dr Niloufar Abourashchi

Postgraduate (FHEQ Level 7)

Teaching and Assessment

• Mode of study: In person
• Methods of assessment:
  • 80% Exam
  • 20% Group activity
• Mark scheme: Numeric Marks

Other Information

• Number of students on module in previous year: 21
• Module leader: Dr Niloufar Abourashchi

Undergraduate (FHEQ Level 7)

Teaching and Assessment

• Mode of study: In person
• Methods of assessment:
  • 80% Exam
  • 20% Group activity
• Mark scheme: Numeric Marks

Other Information

• Number of students on module in previous year: 1
• Module leader: Dr Niloufar Abourashchi

Last Updated

This module description was last updated on 10th March 2026.