Digital Transformation in Banking and Finance Industry Course
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Digital Transformation in Banking and Finance Industry Course
Course Overview:
In the Digital Transformation in Banking and Finance Industry course, an in-depth analysis is offered of how technology has been affecting the banking and finance operations.
Learners will appreciate how digital transformation is defined today, and what new technologies such as AI, robotics, and distributed ledger technologies would be bringing to the financial services of tomorrow.
It is expected that those enrolled in the course will be able to anticipate how technology within the banking sector will progress in the subsequent ten years, appreciate the threats and benefits brought about by such progress and supervise processes of digital transformations in their organizations.
This program is most suitable for the top management and professionals in the banking and finance sector especially those who are engaged in professional practice in regard to change management.
Course Objectives:
At the end of this Digital Transformation in Banking and Finance Industry Course you will be able to:
- Learn what technology can and cannot achieve in banking and finance, and the implications for costs, employment and profitability
- Build a realistic forecast of the use of technology in the banking and finance industry over the coming decade
- Deliver perspectives on digital transformation from a management and technical standpoint
- Understand the opportunities and management challenges posed by Artificial Intelligence, robotics and distributed ledger technologies in the next decade
- Dramatically improve capacity to understand, select, deliver and then manage digital technology in a bank or other financial institution
Who Should Attend?
This Digital Transformation in Banking and Finance Industry Course ideal for:
- The course is designed to provide a comprehensive overview for executives working in, responsible for, or interested in changing banking models.
Course Outlines:
The transformation of the banking industry
- Statistics on key banking variables (employment, skills, branch numbers, internet usage et al)
- Recent developments in banking and finance
- Digital transformation and its significance
- The structure of scientific revolutions – models of how change happens
The transformation of the banking industry 2
- Problems faced by banks
- Social media and brand at banks and financial institutions
- Technology governance in banks and financial institutions
- Deconstructing the bank value chain between product and customer
- The insurance industry and DigiTech
- Fund management digital interfaces
- Case Study: Modelling cost savings from digital transformation
Organization analysis and technology
- Human resources implications
- It skill-sets and relevant qualifications
- Training and development: what technical skills do front-line staff need?
- Management teams and examples of transformation
- Organizational culture and technology
Banking technology
- Enterprise Architecture and its importance
- Payment’s technology and third-party software
- Digital Technology in Practice
- Neural computing
- Non-card payments, mobile devices and payments
- Trends in internet use
- Third-party payment software
- Ocular and voice recognition technologies
Breaking down barriers to entry in banking and finance?
- Problems faced by legacy organizations
- Examples of banking and finance legacy companies
- Rise of the challenger banks
- Face and voice recognition technology
Using data in banking and finance
- How do machines learn?
- What is big data and how can it be harnessed?
- Behavioral economics and profitability – analyzing the connection
- The role of the Internet of Things (IoT) in improving pricing and risk analysis
- Case Study: Improving the accuracy of insurance pricing using real-time vehicle analytics and big data processing
The use of Artificial Intelligence (AI)
- Neural networks and AI as a forecasting tool
- Case Study: Comparing neural and parametric forecasting techniques’ success in financial markets
- Robotic Process Automation (RBA)
- The RBA output at bank board level
- Algorithm-driven corporate bank marketing and sales
- Alignment with EU GDPR and other data protection regimes
- Case Study: Building a real-time client-specific smart dashboard – components and benefits
Cybersecurity
- Data safety, privacy and security management
- Global Accessibility
- Deep learning and AI for security
- Case Study: Evaluating Cognizant’s contribution
The banking landscape in 2030
- What is ‘fast forward forecasting’ and how far does it explain technology forecasting error?
- Review of forecasts for 2020 from 2010 – what went wrong?
- How to conduct technology forecasting
- Measured views of the banking and finance industry in 2030
Conclusion
- Potential obstacles to measured digital transformation
- Probable achievements of distributed ledger, robotics and AI by 2030
- Implications for skill sets, employment, profitability and shareholder value in banking and finance
- Strategizing the bank and finance industry with 2030 technology
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