The Digital Journey of Banking and Insurance, Volume II (eBook, PDF)

Digitalization and Machine Learning
Redaktion: Liermann, Volker; Stegmann, Claus

• Format: PDF

Produktbeschreibung

Gathers the most relevant methods used in bank and insurance digitization

Includes cases on processes, leveraging computational power, and machine learning models

Provides machine learning and deep learning frameworks and examples¿

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 339
• Erscheinungstermin: 27. Oktober 2021
• Englisch
• ISBN-13: 9783030788292
• Artikelnr.: 62836940

Autorenporträt

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.

Inhaltsangabe

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.