Taneja / Ozen / Vardar Data Alchemy in Insurance: Revolutionizing the Insurance Industry through Big Data Analytics

1. Auflage 2025
ISBN: 978-981-5313-83-3
Verlag: Bentham Science Publishers
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 280 Seiten

Data Alchemy in Insurance: Revolutionizing the Insurance Industry through Big Data Analytics discusses cutting-edge technologies like machine learning and AI, transforming insurance into a dynamic, customer-centric industry. Spanning fifteen chapters, topics range from predictive analytics for customer retention to ethical dilemmas in data usage. Learn how big data enhances risk assessment, underwriting, and customer engagement, fostering innovation and operational efficiency. Insights into robo-advisors, automation, and sustainable insurance models provide a comprehensive view of industry advancements. Key Features: - The Data-Driven Renaissance: Innovate and grow strategically with big data. - Customer-Centric Transformation: Personalize engagement and satisfaction. - Operational Efficiency: Optimize claims, detect fraud, and assess risk effectively.

Autoren/Hrsg.

Taneja, Sanjay

Ozen, Ercan

Vardar, Luan

Leseproben

PREFACE

In the dynamic landscape of the 21st century, industries across the globe are experiencing unprecedented transformations, fueled by technological advancements that redefine the way we conduct business. Among these industries, the insurance sector stands at the forefront of change, undergoing a revolutionary evolution driven by the transformative power of Big Data Analytics.

“Data Alchemy in Insurance: Revolutionizing the Insurance Industry through Big Data Analytics” is a comprehensive exploration into the profound impact of data analytics on the insurance landscape. As we navigate through an era defined by data-driven decision-making, this book serves as a beacon, shedding light on the pivotal role that Big Data plays in reshaping the fundamental pillars of the insurance industry.

The integration of Big Data Analytics into insurance operations is not merely a trend but a necessity, as insurers strive to remain competitive, adaptive, and responsive to the ever-shifting demands of the market. This book delves into the intricate ways in which data analytics is reshaping risk assessment, customer engagement, underwriting processes, and claims management within the insurance ecosystem.

Through insightful case studies, expert analyses, and real-world examples, this book aims to demystify the complexities surrounding Big Data Analytics for readers from various backgrounds – be it industry professionals seeking to enhance their practices, scholars delving into the realms of InsurTech, or enthusiasts eager to understand the technological underpinnings of the insurance revolution.

As we embark on this journey through the pages of “Data?Alchemy?in Insurance: Revolutionizing the Insurance Industry through Big Data Analytics” readers will gain valuable insights into the challenges and opportunities that arise at the intersection of insurance and data. The chapters within this book are crafted to provide a holistic perspective on the ongoing transformation, offering a roadmap for industry stakeholders to navigate the evolving landscape with confidence and foresight.

It is our sincere hope that this book becomes a trusted companion for those seeking to unravel the mysteries of Big Data Analytics in the insurance sector. As we witness the revolution unfold, let this preface serve as an invitation to explore the future of insurance – a future where data is not just a commodity but the driving force behind a more resilient, efficient, and customer-centric industry. Following are the abstracts of the chapters included in this book:

Chapter 1

In the realm of motor insurance, customer retention has become a critical focus for companies, given the high cost of acquiring new customers. This study proposes a machine learning model to predict customer churn in the motor insurance sector. The objective is to develop a high-accuracy prediction model, identify significant factors for customer attrition, and create customer segments using machine learning algorithms. The literature review highlights the challenges faced by motor insurance providers, such as annual policy renewals and intense competition. Existing research emphasizes the importance of predicting customer churn to improve service quality and gain new users. Various methods, including under-sampling and neural network models, have been explored to address the issue. The study utilizes a hybrid classifier, GWO-KELM, to predict churn and evaluates its performance through confusion matrices and ROC curve analysis. The results demonstrate the algorithm's ability to characterize test data and its overall accuracy. Data processing involves the Expectation Maximization technique, enhancing decision-making transparency and outcomes.

Chapter 2

In the changing corporate landscape, the combination of Artificial Intelligence (AI) and data analytics has altered the insurance industry, resulting in a customer-centric paradigm through data-driven operations. AI-powered data analytics plays a critical role in helping clients understand, engage with, and select insurance services. This chapter delves into the detailed uses of AI-powered data analytics in the insurance sector, including AI assessment, problems, and ramifications, with a particular emphasis on product customization. The goal is to demonstrate how AI-powered data analytics is altering the industry, meeting customer requests, and investigating disruptive implications. The process entails analyzing secondary sources such as research publications and industry reports to better comprehend the impact on customer choices and service provider tactics. Findings reveal a notable shift in the insurance landscape, emphasizing AI-powered data analytics' profound impact on personalized experiences, data-driven insights, risk assessment, claims processing, premium decisions, and policy customization. This technological evolution signifies a significant transformation in the insurance sector.

Chapter 3

Robo Advisors are ushering in a new era of automated health guardianship, which is ushering in a new era of automated health guardianship in the ever-evolving environment of healthcare, which has seen an explosion in the integration of technology. This article goes into the paradigm change brought about by these sophisticated algorithms in the field of insurance planning, specifically with regard to health coverage. The purpose of this paper is to investigate the revolutionary effect that Robo Advisors have had on the process of insurance planning. Specifically, the article will shed light on the functionalities of Robo Advisors as well as the consequences that these features have for consumers as well as the insurance sector. Additionally, the ethical and regulatory considerations that surround the use of Robo Advisors in insurance planning are covered in this article. Concerns around data privacy, bias mitigation, and openness in algorithmic capabilities become critical as the use of artificial intelligence in decision-making processes becomes more widespread. Also, the changing role of insurance experts in connection with Robo Advisors is investigated in this article. Although these automated technologies simplify and improve the decision-making process, there is still no substitute for the human element when it comes to reading preferences down to the most detailed level and offering individualized guidance.

Chapter 4

Insurance is a healing ointment for every person, but it’s better to go for insurance as a shock absorber for different types of shock in life.

People also take insurance to plan their lives, which helps them reduce tensions throughout life, but so many people also try to avoid taking insurance due to the long time and time-consuming operational procedures at various stages of their insured life. They need an assistant to reduce or resolve the operational problems related to buying policy, claim filing, and renewal of the policy. Traditional practices to resolve issues related to such problems include interaction with men either in the form of physical meetings or by communication through emails and telephones. The advent of the 21st century is the growth of automation in businesses, and the insurance industry is also adopting technology to reduce the issues related to claim settlement policy selling and understanding consumer behavior, which assists in policy selling. This chapter will visualize the growth of technology in the Indian insurance industry.

Chapter 5

The post-COVID era has accelerated the growth of the health insurance sector drastically. Nowadays, the public is focussing on taking health insurance to mitigate the sudden expenses of health services. However, finding the best health scheme for people is still considered challenging. Hence, the present study attempts to solve the issue by developing a framework that considers a range of essential factors of the health insurance plan. The identified factors were ranked by using the integrated Delphi and best-worst methods. The study helps consumers choose their policy effectively using the proposed framework.

Chapter 6

The landscape of the insurance industry is undergoing a profound transformation propelled by the integration of advanced data analytics. This paper explores the evolving role of data analytics in reshaping critical aspects of insurance, ranging from traditional risk assessment to customer-centric practices. Against the backdrop of exponential data growth and technological advancements, insurers are increasingly relying on analytics to inform strategic decision-making, enhance risk modeling, and optimize customer engagement. The abstract provides a concise summary of the primary themes covered in this paper, underscoring the pivotal role of data analytics in navigating the challenges and leveraging the opportunities that lie ahead for the insurance sector. The exploration encompasses current trends, technological advancements, ethical considerations, and regulatory landscapes, aiming to provide a comprehensive understanding of the dynamic future that awaits the intersection of data analytics and insurance.

Chapter 7

After the e-tail and the e-travel industries, the insurance industry has likewise begun its computerized development in India. The Web aggregators have reformed the web-based insurance industry under the permit of the Insurance Regulatory and Development Authority of India. There are currently around 16 authorized web aggregators in India, and some of them have moved forward to try and do online deals with...