The New Skills in Finance Report 2022
In a digital-transforming era, there is a widening skills gap for those who cannot adapt to the new digital world in finance.
CFTE and Elevandi published the report with the discussion with leading experts to help governments, organisations and individuals address the current skills gap in finance and build a digital-resilient workforce in the industry.
Key takeaways from "Emerging Risks and Opportunities of Generative AI for Banks: A Singapore Perspective" report published by MindForge
CFTE summarised “Emerging Risks and Opportunities of Generative AI for Banks: A Singapore Perspective” report by MindForge. This report explores the impact and potential risks of generative artificial intelligence (AI) technology in the financial services sector, particularly in Singapore.
Key Aspects
- Discusses the adoption of generative AI in the banking sector and its potential to improve customer satisfaction, enhance employee experience, reduce costs, and augment productivity.
- Evaluates specific risks posed by generative AI that extend beyond traditional AI challenges and explores the need for revised governance and regulatory frameworks.
Table of Contents
1. Introduction to Generative AI in Banking
2. Potential Benefits of Generative AI in Financial Services
3. Risks Associated with Generative AI
4. Governance and Regulatory Challenges
5. Strategies for Responsible Use of AI in Banking
6. Impact of Generative AI on Workforce and Operations
7. Future Outlook and Recommendations
Key Findings and Insights
This report will give you an insight into:
- 1. Transformational Potential of Generative AI:
- Generative AI is poised to significantly transform banking operations, particularly in enhancing efficiency, improving customer experiences, and augmenting productivity.
- The technology holds potential for various applications within the banking sector, such as improving decision-making processes, reducing costs, and mitigating risks.
- 2. Major Risks Associated with Generative AI:
- The report identifies several risk dimensions specific to generative AI, including Fairness and Bias, Ethics and Impact, Accountability and Governance, Transparency and Explainability, Legal and Regulatory challenges, and Cyber and Data Security.
- Specific risks highlighted include unrepresentative or biased data inputs, adverse impacts on individuals and groups, value misalignment, environmental sustainability impacts, and potential for dark patterns and toxic outputs.
- 3. Governance and Regulatory Challenges:
- Generative AI presents new governance challenges, such as intellectual property rights issues, vulnerability to new kinds of attacks, and the need for increased monitoring.
- The report suggests that while existing governance principles like the FEAT Principles are applicable to generative AI, there is a need for specific augmentations and extensions to address the unique implementation challenges posed by this technology.
- 4. Impact on Workforce and Operations:
- The adoption of generative AI in banking is expected to have a significant impact on workforce roles and operational processes. This includes the potential for job transformation and the creation of new roles that focus on AI management and ethics.
- The report emphasizes the importance of preparing the workforce for these changes through training and upskilling initiatives.
- 5. Strategic and Responsible Use of AI:
- For banks to harness the full potential of generative AI, a strategic approach that balances innovation with responsibility is essential.
- This includes integrating ethical considerations into AI deployment, ensuring transparency and fairness in AI applications, and maintaining strict cybersecurity measures to protect sensitive data.
Key infographics
