Description
Book SynopsisThis 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.
Table of Contents1. 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 Schärf4. Hyperledger composer: syndicated loans- Gereon Dahmen, Volker Liermann5. The concept of the best action/offer in the age of customer experience- Uwe May6. Using prospect theory to determine investor risk aversion- Constantin Lisson7. Leveraging predictive analytics within a value driver based planning framework- Simon Valjanow, Phillip Enzinger, Florian Dinges8. Predictive Risk Management- Volker Liermann, Nikolas Viets9. 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 Dittmar11. Real estate risk: Appraisal capture- Volker Liermann, Norbert Schaudinnus12. Managing internal and external network complexity: how digitalization and new technology influence the modeling approach- Stefan Grossmann, Philipp Enzinger13. 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 Bellon15. 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 Dobryashkina17. Deep learning: an introduction- Sangmeng Li, Volker Liermann, Norbert Schaudinnus18. Hadoop: A standard framework for computer cluster- Eljar Akhgarnush, Lars Broeckers, Thorsten Jakoby19. In-memory databases and their impact on our (future) organizations- Eva Kopic, Bezu Teschome, Thomas Schneider, Ralph Steurer, Sascha Florin20. MongoDB: The journey from a relational to a document-based database for FIS balance sheet management- Boris Bialek21. Summary and Outlook- Volker Liermann, Claus Stegmann
