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- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 296
- ISBN-10: 1041107102
- ISBN-13: 9781041107101
- Kalba: Anglų
AI-Driven Decision-Making in Finance (el. knyga) (skaityta knyga) | knygos.lt
Atsiliepimai
Aprašymas
This book explores the deep impact of AI and digital transformation on finance, its practices and decision intelligence processes. The book and its practical, analytical chapters present further insights regarding ways to effectively utilize AI, potentially even beyond the existing theoretical and practical knowledge. Regulatory, ethical, security and moral challenges and concerns associated with the use of AI in finance are thoroughly analyzed.
Readers will take away a conceptual and practical understanding of AI and digitalization as well as real-world practical case studies, so that they can be applied appropriately in a workplace setting. It aims to differentiate itself by focusing more specifically on the practical realities of AI and digital transformation in decision-making processes within finance, offering actionable guidance and real-world case study or implications, which are less emphasized in most other competitors.
The book is appropriate for experts and professionals interested in deployment of AI, digitalization and their implementation in finance. No doubt, academics, professionals, students and finance experts will find this book an informative practice resource. The book would suit anyone interested in AI and its broader applications in finance or its uses in decision-making processes.
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 296
- ISBN-10: 1041107102
- ISBN-13: 9781041107101
- Kalba: Anglų
This book explores the deep impact of AI and digital transformation on finance, its practices and decision intelligence processes. The book and its practical, analytical chapters present further insights regarding ways to effectively utilize AI, potentially even beyond the existing theoretical and practical knowledge. Regulatory, ethical, security and moral challenges and concerns associated with the use of AI in finance are thoroughly analyzed.
Readers will take away a conceptual and practical understanding of AI and digitalization as well as real-world practical case studies, so that they can be applied appropriately in a workplace setting. It aims to differentiate itself by focusing more specifically on the practical realities of AI and digital transformation in decision-making processes within finance, offering actionable guidance and real-world case study or implications, which are less emphasized in most other competitors.
The book is appropriate for experts and professionals interested in deployment of AI, digitalization and their implementation in finance. No doubt, academics, professionals, students and finance experts will find this book an informative practice resource. The book would suit anyone interested in AI and its broader applications in finance or its uses in decision-making processes.
Atsiliepimai