Statistical Machine Learning Analysis of Cyber Risk Data: Event Case Studies

28 Pages Posted: 20 Jun 2018

See all articles by Gareth Peters

Gareth Peters

Department of Actuarial Mathematics and Statistics, Heriot-Watt University; University College London - Department of Statistical Science; University of Oxford - Oxford-Man Institute of Quantitative Finance; London School of Economics & Political Science (LSE) - Systemic Risk Centre; University of New South Wales (UNSW) - Faculty of Science

Pavel V. Shevchenko

Macquarie University; Macquarie University, Macquarie Business School

Ruben Cohen

Independent

Diane Maurice

Central Bank of Tunisia

Multiple version iconThere are 2 versions of this paper

Date Written: January 27, 2018

Abstract

This work explores the common attributes of different types of cyber risk with a view to better understanding the key attributes that contribute to each type of cyber risk category. In doing so we explore event studies on a range of different market sectors, different countries, different demographics over time and categories of cyber risk event type. To perform this study we explore a modern machine learning clustering method to investigate the attributes of cyber risk and how they can be categorised via a statistical method. We then explore the properties of this statistical classifi cation and interpret its implications for the current taxonomies being developed for cyber risk in areas of risk management. In the process we will interpret and analyse the implications our analysis has on both operational risk modelling of cyber risk data, as well as the implications the fi ndings have for cyber risk insurance products. On a broader level, this analysis informs risk behaviour of both traditional and emerging financial institutions such as financial technology (fi ntech).

Keywords: cyber risk, cyber crime, operational risk, cyber insurance, machine learning, k-means clustering method

Suggested Citation

Peters, Gareth and Shevchenko, Pavel V. and Cohen, Ruben and Maurice, Diane, Statistical Machine Learning Analysis of Cyber Risk Data: Event Case Studies (January 27, 2018). Macquarie University Faculty of Business & Economics Research Paper. Available at SSRN: https://ssrn.com/abstract=3200155 or http://dx.doi.org/10.2139/ssrn.3200155

Gareth Peters

Department of Actuarial Mathematics and Statistics, Heriot-Watt University ( email )

Edinburgh Campus
Edinburgh, EH14 4AS
United Kingdom

HOME PAGE: http://garethpeters78.wixsite.com/garethwpeters

University College London - Department of Statistical Science ( email )

1-19 Torrington Place
London, WC1 7HB
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

University of Oxford Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

London School of Economics & Political Science (LSE) - Systemic Risk Centre ( email )

Houghton St
London
United Kingdom

University of New South Wales (UNSW) - Faculty of Science ( email )

Australia

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Ruben Cohen

Independent ( email )

No Address Available

Diane Maurice

Central Bank of Tunisia ( email )

1080 Tunis
Tunisia

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