Overview

MATH5995 is an honours and postgraduate mathematics course. 

Units of credit: 6

Prerequisites: There are no prerequisites for this course.

Cycle of offering: Not offered every year

Graduate attributes: The course will enhance your research, inquiry and analytical thinking abilities.

More information:  The Course outline will be made available closer to the start of term - please visit this website: www.unsw.edu.au/course-outlines

Important additional information as of 2023

UNSW Plagiarism Policy

The University requires all students to be aware of its policy on plagiarism.

For courses convened by the School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.

If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.

The online handbook entry contains information about the course. The timetable is only up-to-date if the course is being offered this year. 

If you are currently enrolled in MATH5995, you can log into UNSW Moodle for this course.

Course overview

To develop practical mathematical/statistical and relevant numerical computing skills in an important new area of quantitative operational risk modelling based on actuarial methods from insurance. Operational risk identification, estimation and prediction is a current issue and a central activity not only in banking, insurance and superannuation industries but also in areas such as health, IT, environmental safety, ecology, disaster management, and medicine.

Broadly speaking, operational  risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and system or from external events. The concept of operational risk is generic for organisations of all types.

This course will equip students with the necessary tools to undertake core quantitative risk modelling activities required from risk modellers/quantitative analysts in modern financial institutions and large corporations.