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
1 TON

Views
63690

Telegram
 
Data Science and Risk Analytics in Finance and Insurance
Author: Tze Leung Lai, Haipeng Xing
Year: 2025
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.
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.
''
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.

You may also be interested in:

Data Science: The Hard Parts: Techniques for Excelling at Data Science
Data Science The Hard Parts Techniques for Excelling at Data Science
Data Science The Hard Parts Techniques for Excelling at Data Science
Qlik Sense: Advanced Data Visualization for Your Organization: Create smart data visualizations and predictive analytics solutions
Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1 (Lecture Notes on Data Engineering and Communications Technologies, 90)
Data Analytics with Google Cloud Platform Build Real Time Data Analytics on Google Cloud Platform
Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers (Lecture Notes in Computer Science Book 13114)
Graph Data Science with Python and Neo4j Hands-on Projects on Python and Neo4j Integration for Data Visualization and Analysis Using Graph Data Science for Building Enterprise Strategies
Graph Data Science with Python and Neo4j Hands-on Projects on Python and Neo4j Integration for Data Visualization and Analysis Using Graph Data Science for Building Enterprise Strategies
Data Science With Rust A Comprehensive Guide - Data Analysis, Machine Learning, Data Visualization & More
Data Science With Rust A Comprehensive Guide - Data Analysis, Machine Learning, Data Visualization & More
Data Science With Rust: A Comprehensive Guide - Data Analysis, Machine Learning, Data Visualization and More
Big Data, Data Mining and Data Science Algorithms, Infrastructures, Management and Security
Web Analytics Blueprint: Unleashing Data Insights for Digital Success: Unlocking the Power of Data Analysis to Drive Business Growth and Optimization
Be Data Analytical: How to Use Analytics to Turn Data into Value
Smart Data Analytics: Mit Hilfe von Big Data Zusammenhange erkennen und Potentiale nutzen (De Gruyter Praxishandbuch) (German Edition)
Textual Data Science with R (Chapman & Hall/CRC Computer Science & Data Analysis)
Python Data Science: Deep Learning Guide for Beginners with Data Science. Python Programming and Crush Course.
Python Data Science An Ultimate Guide for Beginners to Learn Fundamentals of Data Science Using Python
Python Data Science The Ultimate Handbook for Beginners on How to Explore NumPy for Numerical Data, Pandas for Data Analysis, IPython, Scikit-Learn and Tensorflow for Machine Learning and Business
Ultimate Azure Synapse Analytics Unlock the Full Potential of Azure Synapse Analytics to Seamlessly Integrate, Analyze, and Optimize Complex Data for Enhanced Business Insights and Decision-Making
Ultimate Azure Synapse Analytics Unlock the Full Potential of Azure Synapse Analytics to Seamlessly Integrate, Analyze, and Optimize Complex Data for Enhanced Business Insights and Decision-Making
Stream Analytics with Microsoft Azure Real-time data processing for quick insights using Azure Stream Analytics
Data Analytics Using Splunk 9.x: A practical guide to implementing Splunk|s features for performing data analysis at scale
PYTHON FOR DATA ANALYTICS: Mastering Python for Comprehensive Data Analysis and Insights (2023 Guide for Beginners)
PYTHON DATA ANALYTICS: Mastering Python for Effective Data Analysis and Visualization (2024 Beginner Guide)
Predictive Safety Analytics Reducing Risk through Modeling and Machine Learning
Ultimate Azure Synapse Analytics: Unlock the Full Potential of Azure Synapse Analytics to Seamlessly Integrate, Analyze, and Optimize Complex Data for … and Decision-Making (English Edition)
Querying SQL Server. Run T-SQL Operations, Data Extraction, Data Manipulation, and Custom Queries to Deliver Simplified analytics
Data Analytics with SAS: Explore your data and get actionable insights with the power of SAS (English Edition)
The Modern Business Data Analyst: A Case Study Introduction into Business Data Analytics with CRISP-DM and R
Data Analytics and Big Data
Python for Data Science Comprehensive Guide of Tips and Tricks using Python Data Science
Python for Data Science Advanced and Effective Strategies of Using Python Data Science Theories
Data Science From Scratch Comprehensive Beginners Guide To Learn Data Science From Scratch
Practical Data Science with Jupyter Explore Data Cleaning, Pre-processing, Data Wrangling, Feature Engineering and Machine Learning using Python and Jupyter
Data Science Projects with Python: A case study approach to successful data science projects using Python, pandas, and scikit-learn
Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage
Data Analytics with SAS Explore your data and get actionable insights with the power of SAS
Data Analytics with SAS Explore your data and get actionable insights with the power of SAS