Effective Statistical Learning Methods for Actuaries III: Neural Networks and Extensions

✍ Scribed by Michel Denuit, Donatien Hainaut, Julien Trufin

Publisher: Springer International Publishing
Year: 2019
Tongue: English
Leaves: 258
Series: Springer Actuarial
Edition: 1st ed. 2019
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible.

Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting.

Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning.

This is the third of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

✦ Table of Contents

Front Matter ....Pages i-xiii
Feed-Forward Neural Networks (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 1-41
Bayesian Neural Networks and GLM (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 43-61
Deep Neural Networks (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 63-82
Dimension-Reduction with Forward Neural Nets Applied to Mortality (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 83-109
Self-organizing Maps and k-Means Clustering in Non Life Insurance (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 111-145
Ensemble of Neural Networks (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 147-166
Gradient Boosting with Neural Networks (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 167-192
Time Series Modelling with Neural Networks (Michel Denuit, Donatien Hainaut, Julien Trufin)....Pages 193-248
Back Matter ....Pages 249-250

✦ Subjects

Mathematics; Actuarial Sciences; Statistics for Business/Economics/Mathematical Finance/Insurance; Mathematical Models of Cognitive Processes and Neural Networks

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