This book, one of three volumes, showcases the effective transformation of companies providing banking and insurance services. This first volume gives a business-oriented introduction to the setting and the current challenges of fintech, regtech, and insurtech and provides an outlook on what will be needed in the future. Specific sub-departments in financial services are examined with a view to accounting, risk, and regulatory segments. The book also addresses the importance of cultural aspects of the coming digital transformation with an eye to requirements that will enable a digital bank or insurance company to thrive in 2025. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between.

This book, the third one of three volumes, focuses on data and the actions around data, like storage and processing. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. In the last volume of the series, "Data Storage, Processing and Analysis", the shifts in the way we deal with data are addressed.

This book, the second one of three volumes, gives practical examples by a number of use cases showing how to take first steps in the digital journey of banks and insurance companies. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. This second volume mainly emphasizes use cases as well as the methods and technologies applied to drive digital transformation (such as processes, leveraging computational power and machine learning models).

This book demystifies the developments and defines the buzzwords in the wide open space of digitalization and finance, exploring the space of FinTech through the lens of the financial services professional and what they need to know to stay ahead. With chapters focusing on the customer interface, payments, smart contracts, workforce automation, robotics, crypto currencies and beyond, this book aims to be the go-to guide for professionals in financial services and banking on how to better understand the digitalization of their industry. The book provides an outlook of the impact digitalization will have in the daily work of a CFO/CRO and a structural influence to the financial management (including risk management) department of a bank.

This book, one of three volumes, showcases the effective transformation of companies providing banking and insurance services. This first volume gives a business-oriented introduction to the setting and the current challenges of fintech, regtech, and insurtech and provides an outlook on what will be needed in the future. Specific sub-departments in financial services are examined with a view to accounting, risk, and regulatory segments. The book also addresses the importance of cultural aspects of the coming digital transformation with an eye to requirements that will enable a digital bank or insurance company to thrive in 2025. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between.

This book, the third one of three volumes, focuses on data and the actions around data, like storage and processing. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. In the last volume of the series, "Data Storage, Processing and Analysis", the shifts in the way we deal with data are addressed.

This book, the second one of three volumes, gives practical examples by a number of use cases showing how to take first steps in the digital journey of banks and insurance companies. The angle shifts over the volumes from a business-driven approach in "Disruption and DNA" to a strong technical focus in "Data Storage, Processing and Analysis", leaving "Digitalization and Machine Learning Applications" with the business and technical aspects in-between. This second volume mainly emphasizes use cases as well as the methods and technologies applied to drive digital transformation (such as processes, leveraging computational power and machine learning models).

This book demystifies the developments and defines the buzzwords in the wide open space of digitalization and finance, exploring the space of FinTech through the lens of the financial services professional and what they need to know to stay ahead. With chapters focusing on the customer interface, payments, smart contracts, workforce automation, robotics, crypto currencies and beyond, this book aims to be the go-to guide for professionals in financial services and banking on how to better understand the digitalization of their industry. The book provides an outlook of the impact digitalization will have in the daily work of a CFO/CRO and a structural influence to the financial management (including risk management) department of a bank.