Artificial Intelligence And Actuarial Science
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Artificial Intelligence And Actuarial Science
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Author : Sonal Trivedi
language : en
Publisher: C&h/CRC Press
Release Date : 2024-12
Artificial Intelligence And Actuarial Science written by Sonal Trivedi and has been published by C&h/CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12 with Business & Economics categories.
"This book aims to explore how to automate, innovate, design, and deploy emerging technologies in Actuarial work transformations for the insurance and finance sector. It examines the role of artificial intelligence with process automation in daily monitoring solvency, governance, compliance, data processes, etc. It also explores the usage of Machine learning, telematics system, AI- AI-enabled claim processing software, Big Data and Algorithms, Explainable AI, AI-enabled risk management tools in various actuarial processes. Presents case studies and best practices with real-world examples of successful and unsuccessful actuarial work transformation initiatives and transformation with emerging technologies Offers deployment solutions for different applications of AI in actuarial work Discusses how organizations can effectively incorporate AI into their current practices of Actuarial work Covers diverse emerging technologies, practices and processes of actuaries from around the globe Elaborates upon a framework for comprehending how big data and AI developments may affect insurance offers and their supervision Explains how insurance companies may review and modify their current Risk Management Framework (RMF) to take into account some of the significant differences while implementing AI use cases This reference book is for scholars, researchers and professionals interested in Artificial Intelligence and Actuarial Science"--
Artificial Intelligence And Actuarial Science
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Author : Sonal Trivedi
language : en
Publisher: CRC Press
Release Date : 2024-12-27
Artificial Intelligence And Actuarial Science written by Sonal Trivedi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Computers categories.
This book aims to explore how to automate, innovate, design, and deploy emerging technologies in actuarial work transformations for the insurance and finance sector. It examines the role of artificial intelligence with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of machine learning, telematics system, AI-enabled claim processing software, Big Data and Algorithms, Explainable AI, and AI-enabled risk management tools in various actuarial processes. This book: • Presents case studies and best practices with real-world examples of successful and unsuccessful actuarial work transformation initiatives and transformation with emerging technologies • Offers deployment solutions for different applications of AI in actuarial work • Discusses how organizations can effectively incorporate AI into their current practices of actuarial work • Covers diverse emerging technologies, practices, and processes of actuaries from around the globe • Elaborates upon a framework for comprehending how big data and AI developments may affect insurance offers and their supervision • Explains how insurance companies may review and modify their current Risk Management Framework (RMF) to take into account some of the significant differences while implementing AI use cases This reference book is for scholars, researchers and professionals interested in Artificial Intelligence and Actuarial Science.
Effective Statistical Learning Methods For Actuaries Ii
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Author : Michel Denuit
language : en
Publisher: Springer Nature
Release Date : 2020-11-16
Effective Statistical Learning Methods For Actuaries Ii written by Michel Denuit and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-16 with Business & Economics categories.
This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second 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.
Effective Statistical Learning Methods For Actuaries I
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Author : Michel Denuit
language : en
Publisher:
Release Date : 2019
Effective Statistical Learning Methods For Actuaries I written by Michel Denuit and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Actuarial science categories.
This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first 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.
Ai In Actuarial Science
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Author : Ronald Richman
language : en
Publisher:
Release Date : 2018
Ai In Actuarial Science written by Ronald Richman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Rapid advances in Artificial Intelligence and Machine Learning are creating products and services with the potential not only to change the environment in which actuaries operate, but also to provide new opportunities within actuarial science. These advances are based on a modern approach to designing, fitting and applying neural networks, generally referred to as “Deep Learning”. This paper investigates how actuarial science may adapt and evolve in the coming years to incorporate these new techniques and methodologies. After providing some background on machine learning and deep learning, and providing a heuristic for where actuaries might benefit from applying these techniques, the paper surveys emerging applications of AI in actuarial science, with examples from mortality modelling, claims reserving, non-life pricing and telematics. For some of the examples, code has been provided on GitHub so that the interested reader can experiment with these techniques for themselves. The paper concludes with an outlook on the potential for actuaries to integrate deep learning into their activities.
Advances In Econometrics Operational Research Data Science And Actuarial Studies
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Author : M. Kenan Terzioğlu
language : en
Publisher: Springer Nature
Release Date : 2022-01-17
Advances In Econometrics Operational Research Data Science And Actuarial Studies written by M. Kenan Terzioğlu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Business & Economics categories.
This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.
Logic Based Artificial Intelligence
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Author : Jack Minker
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-12-31
Logic Based Artificial Intelligence written by Jack Minker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-12-31 with Computers categories.
The use of mathematical logic as a formalism for artificial intelligence was recognized by John McCarthy in 1959 in his paper on Programs with Common Sense. In a series of papers in the 1960's he expanded upon these ideas and continues to do so to this date. It is now 41 years since the idea of using a formal mechanism for AI arose. It is therefore appropriate to consider some of the research, applications and implementations that have resulted from this idea. In early 1995 John McCarthy suggested to me that we have a workshop on Logic-Based Artificial Intelligence (LBAI). In June 1999, the Workshop on Logic-Based Artificial Intelligence was held as a consequence of McCarthy's suggestion. The workshop came about with the support of Ephraim Glinert of the National Science Foundation (IIS-9S2013S), the American Association for Artificial Intelligence who provided support for graduate students to attend, and Joseph JaJa, Director of the University of Maryland Institute for Advanced Computer Studies who provided both manpower and financial support, and the Department of Computer Science. We are grateful for their support. This book consists of refereed papers based on presentations made at the Workshop. Not all of the Workshop participants were able to contribute papers for the book. The common theme of papers at the workshop and in this book is the use of logic as a formalism to solve problems in AI.
Artificial Intelligence Driven Transformation In Insurance Security Devops And Intelligent Advisory Systems
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Author : Balaji Adusupalli
language : en
Publisher: Deep Science Publishing
Release Date : 2025-05-07
Artificial Intelligence Driven Transformation In Insurance Security Devops And Intelligent Advisory Systems written by Balaji Adusupalli and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
The insurance industry is undergoing a radical transformation driven by the exponential growth of artificial intelligence (AI) and digital technologies. Once viewed as a traditional, paperwork-heavy sector, insurance is now embracing intelligent systems to streamline operations, enhance customer experiences, and manage risks more effectively. This book, AI-Driven Transformation in Insurance: Security, DevOps, and Intelligent Advisory Systems, explores the dynamic convergence of AI, cybersecurity, DevOps, and next-generation advisory platforms that are reshaping the insurance landscape. In a world increasingly defined by real-time data and digital interactions, insurance providers must adapt rapidly to stay competitive. AI is no longer a future ambition—it is a present-day imperative. From underwriting automation and fraud detection to personalized policy recommendations and predictive analytics, AI is enabling insurers to make smarter decisions faster. However, this transformation also introduces complex challenges related to data security, system integration, and regulatory compliance. This book takes a holistic view of the AI-powered insurance ecosystem. It discusses how secure DevOps practices—often referred to as DevSecOps—ensure that continuous integration and delivery pipelines are not only agile but also robust against evolving cyber threats. Additionally, it examines the rise of intelligent advisory systems that leverage natural language processing, machine learning, and contextual awareness to provide proactive and highly customized customer support. Through real-world case studies, industry insights, and a blend of technical and strategic analysis, readers will gain a deeper understanding of the tools and frameworks driving this new era of digital insurance. Whether you're a technology leader, insurance executive, data scientist, or researcher, this book offers a timely and practical guide to navigating the AI revolution in insurance. As the boundaries between technology and insurance continue to blur, the future belongs to those who can harness AI not just to automate, but to innovate. We invite you to explore the road ahead—where intelligent systems are not just supporting insurance operations, but redefining them entirely.
Biomedical And Business Applications Using Artificial Neural Networks And Machine Learning
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Author : Richard Segall
language : en
Publisher: Engineering Science Reference
Release Date : 2021-11
Biomedical And Business Applications Using Artificial Neural Networks And Machine Learning written by Richard Segall and has been published by Engineering Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11 with Medicine categories.
"This book covers applications of artificial neural networks (ANN) and machine learning (ML) aspects of artificial intelligence to applications to the biomedical and business world including their interface to applications for screening for diseases to applications to large-scale credit card purchasing patterns"--
Intelligent And Other Computational Techniques In Insurance
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Author : A. F. Shapiro
language : en
Publisher: World Scientific
Release Date : 2003
Intelligent And Other Computational Techniques In Insurance written by A. F. Shapiro and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting.