The Digital Journey of Banking and Insurance, Volume III

Gathers the most relevant methods used in the bank and insurance digitalization Showcases how to deal with data and data architectures including streaming technology

Addresses data regulatory requirements like GDPR or data lineage

Gathers the most relevant methods used in the bank and insurance digitalization Showcases how to deal with data and data architectures including streaming technology Addresses data regulatory requirements like GDPR or data lineage

Autorentext

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.

Inhalt

Part I. Big Data and Special Databases.- Chapter 1. Data Lineage.- Chapter 2. Digitization and MongoDB The Art of Possible.- Chapter 3. Graph Databases.- Chapter 4. Data Tiering Options with SAP HANA and Usage in a Hadoop Scenario.- Part II. Streaming.- Chapter 5. Kafka Real-Time Streaming for the Finance Industry.- Chapter 6. Architecture Patterns Batch & Real-Time Capabilities.- Chapter 7. Kafka A Practical Implementation of Intraday Liquidity Risk Management.- Part III. Data: A View on Meta Aspects.- Chapter 8. Data Sustainability A Thorough Consideration.- Chapter 9. Special Data for Insurance Companies.- Chapter 10. Data Protection Putting the Brakes on Digitalization Processes? - Part IV. Distributed Ledger.- Chapter 11. Digital Identity Management for Humans Only? - Part V. Machine Learning and Deep Learning.- Chapter 12. Overview Machine Learning and Deep Learning Frameworks.- Chapter 13. Methods of Machine Learning.- Part VI. Summary.