The Impact of Digital Transformation and FinTech on the Finance Professional

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Liermann, Volker (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Stegmann, Claus (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Palgrave Macmillan, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Finance.; Bank marketing.; Management.; Industrial management.; Popular Science in Finance.; Financial Services.; Innovation/Technology Management.

 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. 

 1. Introduction- Volker Liermann, Claus Stegmann -- Part 1: Automation, distributed ledger and client related aspects -- 2. Batch Processing: Pattern Recognition- Volker Liermann, Claus Stegmann -- 3. Hyperledger fabric as a blockchain framework in the financial industry- Martina Bettio, Fabian Bruse, Achim Franke, Thorsten Jakoby, Daniel Schärf -- 4. Hyperledger composer: syndicated loans- Gereon Dahmen, Volker Liermann -- 5. The concept of the best action/offer in the age of customer experience- Uwe May -- 6. Using prospect theory to determine investor risk aversion- Constantin Lisson -- 7. Leveraging predictive analytics within a value driver based planning framework- Simon Valjanow, Phillip Enzinger, Florian Dinges -- 8. Predictive Risk Management- Volker Liermann, Nikolas Viets -- 9. Intraday liquidity: forecast using pattern recognition- Volker Liermann, Sangmeng Li, Victoria Dobryashkina -- Part 2: Bank Management Aspects -- 10. Internal credit risk models with machine learning- Markus Thiele, Harro Dittmar -- 11. Real estate risk: Appraisal capture- Volker Liermann, Norbert Schaudinnus -- 12. Managing internal and external network complexity: how digitalization and new technology influence the modeling approach- Stefan Grossmann, Philipp Enzinger -- 13. Big data and the CRO of the future- Richard L. Harmon -- Part 3: Regulatory Aspects- Introduction -- 14. How technology (or algorithms like deep learning and machine learning) can help to comply with regulatory requirements- Moritz Plenk, Losif Levant, Noah Bellon -- 15. New Office of the Comptroller of the Currency Fintech Regulation: Ensuring a Successful Special Purpose National Bank Charter Application- Alexa Philo -- Part 4: Methods, Technology & Architecture- Introduction -- 16. Mathematical background of machine learning- Volker Liermann, Sangmeng Li, Victoria Dobryashkina -- 17. Deep learning: an introduction- Sangmeng Li, Volker Liermann, Norbert Schaudinnus -- 18. Hadoop: A standard framework for computer cluster- Eljar Akhgarnush, Lars Broeckers, Thorsten Jakoby -- 19. In-memory databases and their impact on our (future) organizations- Eva Kopic, Bezu Teschome, Thomas Schneider, Ralph Steurer, Sascha Florin -- 20. MongoDB: The journey from a relational to a document-based database for FIS balance sheet management- Boris Bialek -- 21. Summary and Outlook- Volker Liermann, Claus Stegmann.