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Applied Data Science in FinTech - Juraj Hric, Yiping Lin

Applied Data Science in FinTech

Models, Tools, and Case Studies

, (Autoren)

Buch | Softcover
390 Seiten
2026
Routledge (Verlag)
978-1-032-76257-9 (ISBN)
CHF 81,95 inkl. MwSt
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This text offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts.
This textbook offers a comprehensive introduction to data science and financial technology, with a focus on advanced tools, data modeling, and their applications in FinTech. Adopting an inquiry-based approach, it integrates detailed case studies, clear definitions of financial terms, and practical examples to guide readers through core concepts and methods.

Step-by-step illustrations demonstrate how programs are developed, making the material accessible for students. Dedicated chapters explore cutting-edge applications such as AdviceTech, AgTech, PropTech, chatbots, and sentiment analytics. To support hands-on learning, the book also provides sample code and data sets, enabling readers to experiment, practice, and ultimately design their own programs.

Designed for those with a basic foundation in programming, this book is an ideal companion for applying data science techniques to financial and technological contexts. It is particularly valuable for postgraduate and advanced students in FinTech, Business Analytics, and Data Science programs.

Juraj Hric is Co-Founder and Chief Executive Officer at Zyanza Technologies. He is a course convenor for banking, finance and financial technology modules at the University of New South Wales, Australia. Yiping Lin is Co-Founder of Alt Data Tech, a leading provider of alternative data. He is also the director of undergraduate and postgraduate FinTech programs at the University of New South Wales, Australia.

Section 1. Data Science for FinTech

Chapter 1. Data Science in FinTech

Chapter 2. Data Management for FinTech

Chapter 3. Data Visualization

Chapter 4. Data Modeling in FinTech

Section 2. Advanced Tools for Finance and FinTech

Chapter 5. Bitcoin and Tokenization

Chapter 6. Machine Learning Tools for Finance and FinTech

Chapter 7. Language Analytics for Finance and FinTech

Chapter 8. Chatbots for Sentiment Analytics

Section 3. FinTech Applications

Chapter 9. FinTech Application: AdviceTech

Chapter 10. FinTech Application: AgTech

Chapter 11. FinTech Application: PropTech

Chapter 12. Data Frontiers in FinTech

Erscheint lt. Verlag 19.3.2026
Zusatzinfo 154 Halftones, color; 154 Illustrations, color
Verlagsort London
Sprache englisch
Maße 174 x 246 mm
Themenwelt Mathematik / Informatik Informatik
Wirtschaft Betriebswirtschaft / Management
Wirtschaft Volkswirtschaftslehre Finanzwissenschaft
ISBN-10 1-032-76257-8 / 1032762578
ISBN-13 978-1-032-76257-9 / 9781032762579
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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