Data science and risk analytics in finance and insurance /

This book presents statistics and data science methods for risk analytics in quantitative finance and insurance. Part I covers the background, financial models, and data analytical methods for market risk, credit risk, and operational risk in financial instruments, as well as models of risk premium...

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Bibliographic Details
Main Authors:	Lai, T. L. (Author), Xing, Haipeng, SUNY, Stony Brook, New York, USA (Author)
Corporate Author:	Taylor & Francis
Format:	eBook
Language:	English
Published:	Boca Raton : CRC Press, 2025.
Edition:	First edition.
Series:	Chapman & Hall/CRC financial mathematics series.
Subjects:	Finance > Mathematical models. Finance > Statistical methods. Insurance > Data processing. Finances > Modèles mathématiques. Finances > Méthodes statistiques. Assurance > Informatique. BUSINESS & ECONOMICS / Finance Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

PrefacePart 1: Background and Basic Analytics 1. Risk management and regulation2. Basic concepts and methods in risk management3. Financial derivatives and their pricing theory4. Insurance risk and credibility theoryPart 2: Advanced Data and Risk Analytics 5. Supervised and unsupervised learning6. Bandit, Markov decision process and reinforcement learning7. Monte Carlo methods and rare event analytics8. Surveillance and predictive analyticsPart 3: Data and Risk Analytics in FinTech 9. FinTech ABCD and analyticsBibliographyIndex