Alexander McNeil
Professor in Actuarial Science, Accounting & Finance

Profile

Biography

Alexander McNeil has been Professor of Actuarial Science at the University of York since September 2016. Educated at Imperial College London and Cambridge University, he was formerly Assistant Professor in the Department of Mathematics at ETH Zurich and Maxwell Professor of Mathematics in the Department of Actuarial Mathematics and Statistics at Heriot-Watt University. He founded and led the Scottish Financial Risk Academy (SFRA) between 2010 and 2016.

His research interests lie in the development of quantitative methodology for financial risk management and include models for market, credit and insurance risks, financial time series analysis, models for extreme risks and correlated risks and enterprise-wide models for solvency and capital adequacy. He has published papers in leading actuarial, statistics, econometrics and financial mathematics journals and is a regular speaker at international risk management conferences.

He is joint author, together with Rüdiger Frey and Paul Embrechts, of the book "Quantitative Risk Management: Concepts, Techniques and Tools", published by Princeton University Press (2005/2015). He is also an Honorary Fellow of the Institute and Faculty of Actuaries and a Corresponding Member of the Swiss Association of Actuaries.

Departmental roles

Programme Leader

• BSc Actuarial Science
• BSc Finance, Operations Research, Management & Statistics

Joint Head of Accounting and Finance Group

Research

Overview

My research interests lie in the development of mathematical and statistical methodology for financial risk management in banking and insurance. Sound methodology has gained in importance due to the increasing regulation of the financial service industry, in particular the Basel Accords in banking and the Solvency II process in insurance, both of which set out capital standards based on the measurement of risk.

I am particularly interested in market and credit risk models, financial time series analysis, models for extreme risks and correlated risks, models for the valuation and risk management of insurance liabilities, and techniques for backtesting and validating models.

Publications

Full publications list

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