TY  - BOOK
AU  - Wüthrich,Mario V.
AU  - Merz,Michael
ED  - SpringerLink (Online service)
TI  - Statistical Foundations of Actuarial Learning and its Applications
T2  - Springer Actuarial,
SN  - 9783031124099
AV  - HG8779-8793 
U1  - 368.01 23
PY  - 2023///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Actuarial science
KW  - Statistics 
KW  - Machine learning
KW  - Artificial intelligence
KW  - Data processing
KW  - Social sciences
KW  - Mathematics
KW  - Actuarial Mathematics
KW  - Statistics in Business, Management, Economics, Finance, Insurance
KW  - Machine Learning
KW  - Data Science
KW  - Mathematics in Business, Economics and Finance
N1  - Open Access
N2  - 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 tointerpret 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
UR  - https://doi.org/10.1007/978-3-031-12409-9
ER  -