• EH14 4AS

    United Kingdom

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Neural network embeddings of univariate and mutlivariate actuarial regression models for capturing the stylized characteristics of structured, semi-structured and unstructured insurance data.

20142021

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Research interests

Mixture Models, Distribution Theory, EM Algorithm, Univariate, Multivariate and Copula-Based Claim Frequency and Severity Regression Models, Integer Valued Autoregressive INAR(1) Regression Models, Combined Actuarial Neural Network (CANN) models, Classification of Green Bonds using Statistical Learning Methods, Decarbonization.

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Biography

I am an Associate Professor in the Department of Actuarial Mathematics and Statistics at Heriot Watt University in Edinburgh.

I am also the Academic Director of the Scottish Financial Risk Academy and the Academic Chair of the IFoA’s Data Science Research working party Statistical Learning in Actuarial Applications.

I previously held a tenured position in the Department of Statistics of the London School of Economics and Political Science, where I also served as Programme Director for the BSc in Actuarial Science and was the Liaison Officer with the IFoA. Previous to this I was a Lecturer in the Department of Statistics of University College Cork in Ireland.

My research interests lie on the interface between applied statistics, computational statistics, actuarial science and actuarial data science. My articles have appeared in world leading journals. In particular, my research primarily, but not exclusively, focuses on statistical learning applications, via estimation methods, such as the Expectation- Maximization (EM) algorithm, and computational aspects of deep learning in insurance and finace, including insurance ratemaking, setting appropriate levels of reserves and reinsurance, classification of green bonds and decarbonization. 

Finally, my professional activities include a membership of the American Risk and Insurance Association,  a fellowship of the Royal Statistical Society and I am a member of the reviewer board of  MDPI's Risks journal.

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