Description
Book SynopsisThis 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).
Table of ContentsPart 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.
