Improving Operating Leverage Using Hyperautomation
Apress (Verlag)
979-8-8688-0895-1 (ISBN)
Improving operating leverage is about operational resilience, structured operational efficiency, and sustainable revenue growth. Activity-based enterprise non-interest cost management is an important component of enterprise risk adjusted return management methodology. This book builds on the author Kannan Subramanian's earlier book, Event- and Data-Centric Enterprise Risk-Adjusted Return Management, delving in depth into enterprise non-interest operating cost management and operating leverage.
You'll learn that because operating leverage involves the management of a bank's capabilities and capacity to deliver its products and services efficiently, managing both costs and revenue is critical. Profit is an absolute measure that denotes the amount of money the bank makes after deducting all expenses revealing how efficient the bank is at utilizing its resources to generate risk-adjusted returns. This book explains how to improve your operating leverage to attain a competitive advantage.
You'll examine how some institutions have implemented activity-based costing and time-driven activity-based costing in a siloed environment and without enterprise process automation. Many other institutions do not have a scientific way of managing non-interest costs. The book explains why hyperautomation, a technology that creates multi-process systems, is a more advanced and comprehensive way to manage these factors in a holistic and integrated way.
Improving Operating Leverage using Hyperautomation is your complete guide to enhancing risk adjusted operational performance through a nuanced approach to performance, risk, control, and costs at the process level.
What You Will Learn
- Define and use the bill of resources to improve operating leverage.
- Implement activity-based enterprise non-interest cost management using hyperautomation
- Monitor performance, risk, control, and cost at the process level.
- Implement time-driven activity-based costing for an enterprise risk-adjusted return model.
Who This Book Is For
Most banking industry professionals, including senior management teams, consultants, central bankers, financial regulators, software vendors, and Business Process Management Suite/Hyperautomation technology vendors.
Kannan Subramanian R is a Chartered Accountant with 35+ years of experience in the banking and financial services industry and has experience with financial markets in USA, Europe, and Asia. He has worked for Standard Chartered Bank and for leading banking software solution companies, including the leading global risk management solution provider, Algorithmics, now part of IBM Risk Management & Analytics. Kannan He advises System Design Consulting Prospero AG on strategic matters and in the design of risk management and analytical solutions. He has successfully leveraged his academic and work experience to provide value to his customers. His passion for the subject motivates him to prioritize his time to write books on automation and risk-reward management in banks. www.BankERRM.org www.PBORM.org
1 Enterprise Operating Model.- Chapter 2: Non-interest cost management.- Chapter: 3 Enterprise Process Automation, TDABC.- Chapter 4: Operating Leverage.- Chapter 5: Improving Operating Leverage.- Chapter 6: Operating Leverage - Bank of the Future.
| Erscheinungsdatum | 18.12.2024 |
|---|---|
| Zusatzinfo | 516 Illustrations, black and white; XXV, 541 p. 516 illus. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Schlagworte | Banking Automation • Bank Profitability • Enterprise Operating Model • Enterprise Operating Model Efficiency • Operating Leverage • operational resilience • Process Automation in Finance • Time-Driven Activity-Based Costing |
| ISBN-13 | 979-8-8688-0895-1 / 9798868808951 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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