The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential – yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business – but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data – but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets.

Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. A must for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance.

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. A must for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance.

Data is the insurance industry's single greatest asset. Yet many insurers radically underutilize their data assets, and are failing to fully leverage modern analytics. This makes them vulnerable to traditional and non-traditional competitors alike. Today, insurers largely apply analytics in important but stovepiped operational areas like underwriting, claims, marketing and risk management. By and large, they lack an enterprise analytic strategy -- or, if they have one, it is merely an architectural blueprint, inadequately business-driven or strategically aligned. Now, writing specifically for insurance industry professionals and leaders, Patricia Saporito uncovers immense new opportunities for driving competitive advantage from analytics -- and shows how to overcome the obstacles that stand in your way. Drawing on 25+ years of insurance industry experience, Saporito introduces proven best practices for developing, maturing, and profiting from your analytic capabilities. This user-friendly handbook advocates an enterprise strategy approach to analytics, presenting a common framework you can quickly adapt based on your unique business model and current capabilities. Saporito reviews common analytic applications by functional area, offering specific case studies and examples, and helping you build upon the analytics you're already doing. She presents data governance models and models proven to help you organize and deliver trusted data far more effectively. Finally, she provides tools and frameworks for improving the "analytic IQ" of your entire enterprise, from IT developers to business users.

The Impact of CLIMATE CHANGE and SUSTAINABILITY STANDARDS on the INSURANCE MARKET The book explores the role of the insurance industry in contributing and responding to the harms that climate change has brought. This book delves into the physical and logical impacts, both direct and indirect, on the insurance industry. Subjects discussed include new technology such as big data, artificial intelligence, machine learning, the growth of sustainable economics with foreign direct investments (FDIs), trustworthiness, and ethics. Related use cases of data science for claim processing, fraud detection and prevention, policy administration, pricing, and underwriting are discussed along with cyber security issues, data protection, and big data regulatory reforms. To promote ESG sustainability, the insurance industry plays a critical and significant role. Climate-related risks are being factored into underwriting and investing strategies. Through their own operations and business activities, insurers may promote the ESG agenda and move towards sustainability. Also discussed are promoting diversity and inclusion, lowering greenhouse gas (GHG) emissions, resolving gender inequality, and helping communities through charitable work, which all improve a company’s brand, reputation, and ESG credentials. Audience The book is specially designed for administrators, lecturers, researchers, students of insurance and sustainability, students in financial services, insurance practitioners, actuaries, loss adjusters, underwriters, regulators, facilities management, utility companies, voluntary organizations, government departments, business leaders, policymakers, decision-makers, investors, risk managers, compliance managers, and audit managers amongst many others.

Most businesses today are embracing digital transformation and automation, deploying the processes of data analytics in combination with advanced technologies for customer retention using such techniques as marketing automation, digital marketing, machine learning (ML), blockchain, generative AI, and robotics. This new book discusses a wide range of topics related to big data customer analytics and its application for customer retention. It covers important topics on the use of big data in business, including personalization and customization of products and services, segmentation, digital marketing, customer relationship management, loyalty programs, and customer loyalty and retention and more. The book provides examples and case studies that demonstrate how big data is changing the customer loyalty scenario in a highly digitalized world. The book also addresses using big data analytics in areas such as metaverse, government bodies, and fashion retail. Key features: Provides valuable insights on formulating customer retention strategies using big data analytics Discusses the application of big data for reducing churn rate Demonstrates strategies for using big data analytics to improve efficiency and customer service With its diverse and comprehensive coverage, this book offers academics, marketers, human resource managers, students, as well as industrial practitioners a guide to using the exciting technology of big data for customer retention.

This book focuses on the global landscape in which insurance is transacted, and where it is evolving, driven from within by transformative technologies and externally by the necessity to address risks like climate change and health crises, such as the COVID-19 pandemic. It discusses the dynamic challenges and opportunities that lie ahead for the industry in areas such as on-demand insurance, embedded insurance, parametric insurance, autonomous vehicles, the rise of fintech, the cyber risk landscape and through initiatives driven by distributed ledger technology or blockchain solutions. Moreover, it covers the major external challenges confronting the global insurance market, such as the growing insurance protection gap in relation to the affordability and insurability of natural catastrophes and climate change, and pandemics like COVID-19. This book examines innovations in insurance driven by the industry as well as externally imposed changes and dynamics impacting the industry. It describes these changes, the industry’s responses and the legal framework in which they occur. It canvasses additional regulatory and law reform initiatives that may be necessary to achieve an effective balance between the various competing interests. The book is the first to address these matters holistically with a particular focus upon insurance law, it will describe these changes and industry responses and the legal framework in which they occur. The Global Insurance Market will be directly relevant to legal professionals, insurers, insurtechs, fintechs, brokers, CEOs of insurance companies, risk managers, legal counsel, academics, researchers, the judiciary, and policy makers. It will also serve as a valuable resource for students of all levels.

This book is a unique guide to the disruptions, innovations, and opportunities that technology provides the insurance sector and acts as an academic/industry-specific guide for creating operational effectiveness, managing risk, improving financials, and retaining customers. It also contains the current philosophy and actionable strategies from a wide range of contributors who are experts on the topic. It logically explains why traditional ways of doing business will soon become irrelevant and therefore provides an alternative choice by embracing technology. Practitioners and students alike will find value in the support for understanding practical implications of how technology has brought innovation and modern methods to measure, control, and evaluation price risk in the insurance business. It will help insurers reduce operational costs, strengthen customer interactions, target potential customers to provide usage-based insurance, and optimize the overall business. Retailers and industry giants have made significant strides in adopting digital platforms to deliver a satisfying customer experience. Insurance companies must adjust their business models and strategies to remain competitive and take advantage of technology. Insurance companies are increasingly investing in IT and related technologies to improve customer experience and reduce operational costs. Innovation through new technologies is a key driver of change in the financial sector which is often accompanied by uncertainty and doubt. This book will play a pivotal role in risk management through fraud detection, regulatory compliances, and claim settlement leading to overall satisfaction of customers.

The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.