BOOKS - Data Science and Risk Analytics in Finance and Insurance
Data Science and Risk Analytics in Finance and Insurance - Tze Leung Lai, Haipeng Xing 2025 PDF CRC Press BOOKS
ECO~18 kg CO²

1 TON

Views
80742

Telegram
 
Data Science and Risk Analytics in Finance and Insurance
Author: Tze Leung Lai, Haipeng Xing
Year: 2025
Pages: 464
Format: PDF
File size: 10.1 MB
Language: ENG



Pay with Telegram STARS
Book Description: Data Science and Risk Analytics in Finance and Insurance In today's fast-paced digital world, the ability to analyze and interpret vast amounts of data is crucial for success in the financial and insurance industries. Data science and risk analytics have become essential tools for businesses and organizations looking to make informed decisions and mitigate risks. This book provides a comprehensive overview of the latest statistical and data science methods for risk analytics in quantitative finance and insurance, as well as an introduction to four key areas in financial technology: Artificial Intelligence, blockchain, cloud computing, and big data analytics.
Наука о данных и аналитика рисков в финансах и страховании В современном быстро развивающемся цифровом мире способность анализировать и интерпретировать огромные объемы данных имеет решающее значение для успеха в финансовой и страховой отраслях. Наука о данных и аналитика рисков стали важными инструментами для предприятий и организаций, которые хотят принимать обоснованные решения и снижать риски. В этой книге представлен всесторонний обзор новейших статистических и дата-научных методов для аналитики рисков в количественных финансах и страховании, а также введение в четыре ключевых направления в финансовых технологиях: искусственный интеллект, блокчейн, облачные вычисления и аналитика больших данных.
Science des données et analyse des risques dans la finance et l'assurance Dans le monde numérique en évolution rapide d'aujourd'hui, la capacité d'analyser et d'interpréter d'énormes quantités de données est essentielle au succès dans les secteurs de la finance et de l'assurance. La science des données et l'analyse des risques sont devenues des outils importants pour les entreprises et les organisations qui veulent prendre des décisions éclairées et réduire les risques. Ce livre présente un aperçu complet des dernières méthodes statistiques et data-scientifiques pour l'analyse des risques dans la finance quantitative et l'assurance, ainsi qu'une introduction à quatre domaines clés dans les technologies financières : intelligence artificielle, blockchain, cloud computing et big data analysis.
Ciencia de los Datos y Análisis de Riesgos en Finanzas y Seguros En el mundo digital en rápida evolución de hoy, la capacidad de analizar e interpretar enormes cantidades de datos es crucial para el éxito de las industrias financiera y de seguros. La ciencia de los datos y el análisis de riesgos se han convertido en herramientas importantes para las empresas y organizaciones que desean tomar decisiones informadas y reducir los riesgos. Este libro ofrece una amplia visión general de las últimas técnicas estadísticas y de datos para el análisis de riesgos en finanzas y seguros cuantitativos, así como una introducción a cuatro áreas clave en tecnología financiera: inteligencia artificial, blockchain, computación en la nube y análisis de big data.
Scienza dei dati e analisi dei rischi in finanza e assicurazione In un mondo digitale in continua evoluzione, la capacità di analizzare e interpretare enormi quantità di dati è fondamentale per il successo nel settore finanziario e assicurativo. La scienza dei dati e l'analisi dei rischi sono diventati strumenti importanti per le aziende e le organizzazioni che vogliono prendere decisioni ragionevoli e ridurre i rischi. Questo libro fornisce una panoramica completa delle più recenti tecniche statistiche e data-science per gli analisti dei rischi in termini di finanza e assicurazioni quantitative, nonché l'introduzione di quattro ambiti chiave nelle tecnologie finanziarie: intelligenza artificiale, blockchain, cloud computing e analisi dei big data.
Data Science und Risikoanalyse in Finanzen und Versicherungen In der heutigen schnelllebigen digitalen Welt ist die Fähigkeit, riesige Datenmengen zu analysieren und zu interpretieren, entscheidend für den Erfolg in der Finanz- und Versicherungsbranche. Data Science und Risikoanalyse sind zu wichtigen Werkzeugen für Unternehmen und Organisationen geworden, die fundierte Entscheidungen treffen und Risiken reduzieren möchten. Dieses Buch bietet einen umfassenden Überblick über die neuesten statistischen und datenwissenschaftlichen Methoden für die Risikoanalyse in quantitativen Finanzen und Versicherungen sowie eine Einführung in vier Schlüsselbereiche der Finanztechnologie: künstliche Intelligenz, Blockchain, Cloud Computing und Big Data Analytics.
Data Science and Risk Analytics w finansach i ubezpieczeniach W dzisiejszym szybko rozwijającym się świecie cyfrowym zdolność do analizy i interpretacji ogromnych ilości danych ma kluczowe znaczenie dla sukcesu w branży finansowej i ubezpieczeniowej. Nauka o danych i analiza ryzyka stały się ważnymi narzędziami dla przedsiębiorstw i organizacji, które chcą podejmować świadome decyzje i ograniczać ryzyko. Książka ta zawiera kompleksowy przegląd najnowszych metod statystycznych i naukowo-badawczych dotyczących analityki ryzyka w finansach ilościowych i ubezpieczeniach, a także wprowadzenie do czterech kluczowych obszarów technologii finansowych: sztucznej inteligencji, blockchain, chmury obliczeniowej i analizy dużych danych.
''
Finans ve gortada Veri Bilimi ve Risk Analitiği Günümüzün hızla gelişen dijital dünyasında, çok miktarda veriyi analiz etme ve yorumlama yeteneği, finans ve sigorta endüstrilerindeki başarı için kritik öneme sahiptir. Veri bilimi ve risk analitiği, bilinçli kararlar vermek ve riski azaltmak isteyen işletmeler ve kuruluşlar için önemli araçlar haline gelmiştir. Bu kitap, kantitatif finans ve sigortacılıkta risk analitiği için en son istatistiksel ve veri bilimi yöntemlerinin yanı sıra finansal teknolojideki dört temel alana giriş niteliğindedir: yapay zeka, blockchain, bulut bilişim ve büyük veri analizi.
علم البيانات وتحليلات المخاطر في التمويل والتأمين في عالم اليوم الرقمي سريع التطور، تعد القدرة على تحليل وتفسير كميات هائلة من البيانات أمرًا بالغ الأهمية للنجاح في الصناعات المالية والتأمينية. أصبحت علوم البيانات وتحليلات المخاطر أدوات مهمة للشركات والمنظمات التي ترغب في اتخاذ قرارات مستنيرة وتخفيف المخاطر. يقدم هذا الكتاب لمحة عامة شاملة عن أحدث الأساليب الإحصائية وعلوم البيانات لتحليلات المخاطر في التمويل الكمي والتأمين، بالإضافة إلى مقدمة لأربعة مجالات رئيسية في التكنولوجيا المالية: الذكاء الاصطناعي، و blockchain، والحوسبة السحابية، وتحليلات البيانات الضخمة.
在當今快速發展的數字世界中,分析和解釋大量數據的能力對於金融和保險業的成功至關重要。數據科學和風險分析已成為希望做出明智決策並降低風險的企業和組織的重要工具。本書全面概述了用於量化金融和保險風險分析的最新統計和數據科學方法,並介紹了金融技術的四個關鍵領域:人工智能,區塊鏈,雲計算和大數據分析。

You may also be interested in:

Data Science and Risk Analytics in Finance and Insurance
Data Science and Risk Analytics in Finance and Insurance
Data Science and Risk Analytics in Finance and Insurance (Chapman and Hall CRC Financial Mathematics Series)
Data Analytics and Python Programming 2 Bundle Manuscript Beginners Guide to Learn Data Analytics, Predictive Analytics and Data Science with Python Programming
Big data A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining
Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale (Addison-Wesley Data and Analytics)
Python Data Science The Complete Guide to Data Analytics + Machine Learning + Big Data Science + Pandas Python. The Easy Way to Programming (Exercises Included)
Why Data Science Projects Fail: The Harsh Realities of Implementing AI and Analytics, without the Hype (Chapman and Hall CRC Data Science Series)
Data Analytics Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
Data Analytics: Practical Guide to Leveraging the Power of Algorithms, Data Science, Data Mining, Statistics, Big Data, and Predictive Analysis to Improve Business, Work, and Life
Getting Started with DuckDB: A practical guide for accelerating your data science, data analytics, and data engineering workflows
Essential Data Analytics, Data Science, and AI A Practical Guide for a Data-Driven World
DATA SCIENCE WITH PYTHON Complete Guide To Understanding Data Analytics And Data Science With Python Programming
Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics)
It|s All Analytics, Part III: The Applications of AI, Analytics, and Data Science (It|s All Analytics, 3)
Data Science 2 Books in 1 Python Programming & Python for Data Science, The Ultimate Guide to Learn Machine Learning and Predictive Analytics from Scratch with Hands-On Projects
Data Analytics for Absolute Beginners: Make Decisions Using Every Variable: (Introduction to Data, Data Visualization, Business Intelligence and Machine … Science, Python and Statistics for Begi
Programming Skills for Data Science Start Writing Code to Wrangle, Analyze, and Visualize Data with R (Addison-Wesley Data & Analytics Series) 1st Edition - Fiunal
Analytics in a Big Data World The Essential Guide to Data Science and its Applications
Agile Data Science Building Data Analytics Applications with Hadoop
Agile Data Science 2.0 Building Full-Stack Data Analytics Applications with Spark
Data Science and Big Data Analytics in Smart Environments
Business Intelligence An Essential Beginner’s Guide to BI, Big Data, Artificial Intelligence, Cybersecurity, Machine Learning, Data Science, Data Analytics, Social Media and Internet Marketing
Data Science and Analytics with Python (Chapman and Hall CRC Data Mining and Knowledge Discovery Series)
Learn Data Analytics For Beginners Data Analyst, Deep Learning, Neural Network, Python Data Analytics
Advanced Data Science and Analytics with Python (Chapman and Hall CRC Data Mining and Knowledge Discovery Series)
Python Data Science The Ultimate Crash Course, Tips, and Tricks to Learn Data Analytics, Machine Learning, and Their Application
Data Science and Data Analytics Opportunities and Challenges
Advanced Data Science and Analytics with Python (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Practical Data Analytics for BFSI Leveraging Data Science for Driving Decisions in Banking, Financial Services, and Insurance Operations
Python Data Science How to Learn Step by Step Programming, Data Analytics, and Coding Essentials Tools
Statistics for Data Science and Analytics
Statistics for Data Science and Analytics
Data Science and Analytics with Python
Video Data Analytics for Smart City Applications: Methods and Trends (IoT and Big Data Analytics)
Learn Python Programming A Beginners Crash Course on Python Language for Getting Started with Machine Learning, Data Science and Data Analytics (Artificial Intelligence Book 1)
Analytics, Data Science, & Artificial Intelligence
Audit Analytics: Data Science for the Accounting Profession (Use R!)
Python for Data Science Master Data Analysis from Scratch, with Business Analytics Tools and Step-by-Step techniques for Beginners. The Future of Machine Learning & Applied Artificial Intelligence