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).

Volker Liermann, Partner at ifb group,worked in the banking industry for over two decades, primarily focusing on financial risk management. Throughout his career, he has focused on developing integrated and comprehensive frameworks to help organizations correctly project risk at a strategic and tactical line of business and departmental level. He has also focused on developing frameworks to integrate stress testing and regulatory stress tests. In recent years, his focus has shifted to digitalization, machine learning and digital processes including improvements to classical financial and non-financial risk management. He has a background in economics and a degree in mathematics from the University of Bonn.

Claus Stegmann has as Co-CEO of ifb group an international consulting firm acquired extensive know-how over the last three decades in the financial industry regarding finance transformation, risk management and regulatory compliance. He is intensively engaged with the current challenges of the financial industry, which result from strong changes to customer behavior, a changing competitive environment and new technologies due to digitalization. He has also co-authored books on Stress Tests in Banks, Basel III as well as Digitalization in the Finance Industry, and graduated from Business School at the University of Passau, Germany.

Part I. Use Cases.- Chapter 1. Use Case Optimization of Regression Tests Reduction of the Test Portfolio Through Representative Identification.- Chapter 2. Use Case Nostro Accounts Match.- Chapter 3. Use Case Fraud Detection Using Machine Learning Techniques.- Chapter 4. Use case NFR HR Risk.- Chapter 5. Sentiment Analysis for Reputational Risk Management.- Chapter 6. Use Case NFR Using GraphDB for Impact Graphs.- Part I. High-Performance Applications.- Chapter 7. Distributed Calculation Credit Portfolio Models.- Chapter 8. BSDS Balance Sheet Dynamics Simulator.- Chapter 9. Dynamic Dashboards.- Chapter 10. High-Performance Applications.- Part III. Quantum Computing.- Chapter 11. Post-Quantum Secure Cryptographic Algorithms.- Chapter 12. Quantum Technologies.- Chapter 13. Categorical Quantum Theory.- Part IV. Process& Process Optimization.- Chapter 14. Processes in a Digital Environment.- Chapter 15. Process Mining.- Chapter 16. Hyperautomation (Automated Decision-Making as Part of RPA).- Chapter 17. RPA Use Case IFRS 9/SPPI.- Part V. Open Source.- Chapter 18. Open-Source Software.- Part VI. Summary.