Balamurugan Baluswamy – författare

Big data – unstructured and/or structured data being used to influence underwriting, rating, pricing, forms, marketing and claims handling and incentivize risk reduction – is a relatively recent development in the insurance industry, the data sets previously being too impossibly great to analyse through traditional methods. However, with the global capacity to collect and store data growing alongside advancements in AI and machine learning technology, insurers need to seriously evaluate their technology stacks to ensure they can remain competitive and respond to growing customer demand.

Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional.

Providing high quality academic research, Emerald Studies in Finance, Insurance, and Risk Management provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale. Subjects of interest may include banking, accounting, auditing, compliance, sustainability, behaviour, management, and business economics.

Big data – unstructured and/or structured data being used to influence underwriting, rating, pricing, forms, marketing and claims handling and incentivize risk reduction – is a relatively recent development in the insurance industry, the data sets previously being too impossibly great to analyse through traditional methods. However, with the global capacity to collect and store data growing alongside advancements in AI and machine learning technology, insurers need to seriously evaluate their technology stacks to ensure they can remain competitive and respond to growing customer demand.

Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional.

Providing high quality academic research, Emerald Studies in Finance, Insurance, and Risk Management provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale. Subjects of interest may include banking, accounting, auditing, compliance, sustainability, behaviour, management, and business economics.

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

The insurance industry is largely 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.

This book an invaluable resource for any insurance professional from practitioners and policymakers working at insurance companies, to undergraduate and graduate students of economics management, and finance.

Providing high quality academic research, ESFIRM provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale.

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

The insurance industry is largely 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.

This book an invaluable resource for any insurance professional from practitioners and policymakers working at insurance companies, to undergraduate and graduate students of economics management, and finance.

Providing high quality academic research, ESFIRM provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale.

Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.

The traditional framework of Human Resource Management (HRM) primarily consists of four functions: Human Resource Planning, Recruitment and Selection, Training and Development and Performance Management Systems which help businesses in hiring, motivating and retaining employees. The introduction of Artificial Intelligence (AI) has changed all of these aspects.

The Adoption and Effect of Artificial Intelligence on Human Resources Management Series sets out a blended approach towards different functions of HRM and AI, reflecting upon: HR data privacy; data security; diversity and inclusion using AI; and sustainable AI-HR practices. This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.

Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.

The traditional framework of Human Resource Management (HRM) primarily consists of four functions: Human Resource Planning, Recruitment and Selection, Training and Development and Performance Management Systems which help businesses in hiring, motivating and retaining employees. The introduction of Artificial Intelligence (AI) has changed all of these aspects.

The Adoption and Effect of Artificial Intelligence on Human Resources Management Series sets out a blended approach towards different functions of HRM and AI, reflecting upon: HR data privacy; data security; diversity and inclusion using AI; and sustainable AI-HR practices. This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.

The Covid 19 pandemic has created chaos in the business world and forced leaders to rethink their operational status quo. Balancing the physical and virtual spaces of the global digital economy wherein economic, commercial, and professional transactions are enabled by information and communication technologies has called for additional support from data-driven technologies like smart analytics and artificial intelligence. Opportunities created within digital economies to leverage technologies to execute tasks better, faster, and often differently have found the desired prominence in the recent past. Though the benefits outweigh the risks, the challenges in digitalised economies are as sophisticated as the solutions they offer.

Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalized Economy presents various viewpoints on topics like artificial intelligence, blockchain technology, digitalisation in various sectors, technology issues like cybersecurity and financial inclusion, and technology-enabled banking issues like money laundering. The theme of sustainability forms the core of the book.

The Covid 19 pandemic has created chaos in the business world and forced leaders to rethink their operational status quo. Balancing the physical and virtual spaces of the global digital economy wherein economic, commercial, and professional transactions are enabled by information and communication technologies has called for additional support from data-driven technologies like smart analytics and artificial intelligence. Opportunities created within digital economies to leverage technologies to execute tasks better, faster, and often differently have found the desired prominence in the recent past. Though the benefits outweigh the risks, the challenges in digitalised economies are as sophisticated as the solutions they offer.

Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalized Economy presents various viewpoints on topics like artificial intelligence, blockchain technology, digitalisation in various sectors, technology issues like cybersecurity and financial inclusion, and technology-enabled banking issues like money laundering. The theme of sustainability forms the core of the book.

Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.

The traditional framework of Human Resource Management (HRM) primarily consists of four functions: Human Resource Planning, Recruitment and Selection, Training and Development and Performance Management Systems which help businesses in hiring, motivating and retaining employees. The introduction of Artificial Intelligence (AI) has changed all of these aspects.

This second volume in The Adoption and Effect of Artificial Intelligence on Human Resources Management Series reflects upon: the accuracy of using AI to nominate candidates; the change readiness of employees; impacts and challenges on HRM practices; effects on upskilling; and the effects of the pandemic; concluding with an overall state of industry trends.

This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.

Emerald Studies In Finance, Insurance, And Risk Management 7 explores how AI and Automation enhance the basic functions of human resource management.

The traditional framework of Human Resource Management (HRM) primarily consists of four functions: Human Resource Planning, Recruitment and Selection, Training and Development and Performance Management Systems which help businesses in hiring, motivating and retaining employees. The introduction of Artificial Intelligence (AI) has changed all of these aspects.

This second volume in The Adoption and Effect of Artificial Intelligence on Human Resources Management Series reflects upon: the accuracy of using AI to nominate candidates; the change readiness of employees; impacts and challenges on HRM practices; effects on upskilling; and the effects of the pandemic; concluding with an overall state of industry trends.

This book is ideal for HR managers, senior managers, researchers, and students planning a career in this field.

In the digital age, data has become the cornerstone of effective marketing strategies. Data Engineering for Data-Driven Marketing explores the vital intersection of data engineering and marketing, providing a comprehensive guide to harnessing the power of data for successful and impactful campaigns.

Offering a thorough exploration of the symbiotic relationship between data engineering and modern marketing strategies, Data Engineering for Data-Driven Marketing uses a strategic lens to delve into methodologies of collecting, transforming, and storing diverse data sources. With real-world case studies actionable insights, the chapters within navigate the reader through the intricate process of building robust data pipelines, optimizing data quality, and implementing real-time processing techniques, all tailored to elevate marketing campaigns through precision targeting, customer personalization, and predictive modelling.

In the digital age, data has become the cornerstone of effective marketing strategies. Data Engineering for Data-Driven Marketing explores the vital intersection of data engineering and marketing, providing a comprehensive guide to harnessing the power of data for successful and impactful campaigns.

Offering a thorough exploration of the symbiotic relationship between data engineering and modern marketing strategies, Data Engineering for Data-Driven Marketing uses a strategic lens to delve into methodologies of collecting, transforming, and storing diverse data sources. With real-world case studies actionable insights, the chapters within navigate the reader through the intricate process of building robust data pipelines, optimizing data quality, and implementing real-time processing techniques, all tailored to elevate marketing campaigns through precision targeting, customer personalization, and predictive modelling.

The Covid 19 pandemic has created chaos in the business world and forced leaders to rethink their operational status quo. Balancing the physical and virtual spaces of the global digital economy wherein economic, commercial, and professional transactions are enabled by information and communication technologies has called for additional support from data-driven technologies like smart analytics and artificial intelligence. Opportunities created within digital economies to leverage technologies to execute tasks better, faster, and often differently have found the desired prominence in the recent past. Though the benefits outweigh the risks, the challenges in digitalised economies are as sophisticated as the solutions they offer.

Contemporary Studies in Economic and Financial Analysis publishes a series of current and relevant themed volumes within the fields of economics and finance. Both disciplinary and interdisciplinary studies are welcome.

The Covid 19 pandemic has created chaos in the business world and forced leaders to rethink their operational status quo. Balancing the physical and virtual spaces of the global digital economy wherein economic, commercial, and professional transactions are enabled by information and communication technologies has called for additional support from data-driven technologies like smart analytics and artificial intelligence. Opportunities created within digital economies to leverage technologies to execute tasks better, faster, and often differently have found the desired prominence in the recent past. Though the benefits outweigh the risks, the challenges in digitalised economies are as sophisticated as the solutions they offer.

Contemporary Studies in Economic and Financial Analysis publishes a series of current and relevant themed volumes within the fields of economics and finance. Both disciplinary and interdisciplinary studies are welcome.

Digitization of economic and management processes allows for the delivery of new value and higher efficiency in the implementation of strategic goals. This is due to the inclusion of digital technologies in the existing rules of functioning among partners involved in the flow of resources, and from their readiness for digital transformation.

A significant challenge, in practical, organizational, and scientific terms is to understand the opportunities and threats resulting from digital transformation, to identify optimal strategies for the development of business entities in new economic and management conditions, taking care to adopt collateral and proper management of new risks. Addressing this challenge to the readers - contributors indicate the latest theoretical advances, and practical examples in Moldova, Kosovo, and the BRIC countries, among others. This results in a synthetic look at the complex digital transformation processes of the modern world, both in terms of the underlying causes and the vast effects of the transformations and digitization of social and economic life.

Contemporary Studies in Economic and Financial Analysis publishes a series of current and relevant themed volumes within the fields of economics and finance.

Digitization of economic and management processes allows for the delivery of new value and higher efficiency in the implementation of strategic goals. This is due to the inclusion of digital technologies in the existing rules of functioning among partners involved in the flow of resources, and from their readiness for digital transformation.

A significant challenge, in practical, organizational, and scientific terms is to understand the opportunities and threats resulting from digital transformation, to identify optimal strategies for the development of business entities in new economic and management conditions, taking care to adopt collateral and proper management of new risks. Addressing this challenge to the readers - contributors indicate the latest theoretical advances, and practical examples in Moldova, Kosovo, and the BRIC countries, among others. This results in a synthetic look at the complex digital transformation processes of the modern world, both in terms of the underlying causes and the vast effects of the transformations and digitization of social and economic life.

Contemporary Studies in Economic and Financial Analysis publishes a series of current and relevant themed volumes within the fields of economics and finance.

Our economies currently encourage excessive consumerism, weakening social ties, and depleting natural resources. Unfortunately, this is just the way economies have been developing. However, it is neither inevitable nor necessary. It takes a fresh economic vision to address these issues: a Green Economy. The concept of a "green economy" does not supplant sustainable development but instead places a fresh emphasis on a region''s economy, investments pertaining to infrastructure, job and skill needs, and favourable social and environmental consequences.

Sustainability Development through Green Economics examines sustainable finance, green tourism, green marketing as a tributary towards sustainable development. The multidisciplinary chapters traverse the power of economic as well as financial policy, green investment, green insurance as well as green infrastructural development to ensure sustainable development.

Contemporary Studies in Economic and Financial Analysis publishes a series of current and relevant themed volumes within the fields of economics and finance. Both disciplinary and interdisciplinary studies are welcome.