Statistical Foundations of Actuarial Learning and its Applications

This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statisti...

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Hlavní autoři: Wüthrich, Mario V, Merz, Michael
Médium: E-kniha
Jazyk:angličtina
Vydáno: Cham Springer Nature 2023
Springer International Publishing AG
Swiss Re
Vydání:1
Edice:Springer Actuarial
Témata:
Actuarial Modeling
Algorithms and data structures
Applied mathematics
Artificial intelligence
Artificial Neural Networks
Computer programming / software engineering
Computer science
Computer Technology
Computing and Information Technology
Deep Learning
Machine learning
Mathematics
Mathematics and Science
Nonfiction
Pricing and Claims Reserving
Probability and statistics
Regression Modeling
ISBN:303112409X, 9783031124099, 9783031124082, 3031124081
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Shrnutí:This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.
Bibliografie:Electronic reproduction. Dordrecht: Springer, 2022. Requires the Libby app or a modern web browser.
ISBN:303112409X
9783031124099
9783031124082
3031124081
DOI:10.1007/978-3-031-12409-9