Released
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 Insights
Key takeaways from "Banking on a game-changer: AI in financial services" report published by The Economist
CFTE summarised “Banking on a game-changer: AI in financial services” report by The Economist. The report examines the growing adoption of AI in the financial services industry.

Key Aspects
- The report highlights how banks are leveraging AI for business priorities like back-office efficiency, product innovation, and new business models, while also addressing the increasing complexity and risks associated with AI.
- It focuses on how AI is being used innovatively in various areas such as fraud detection, IT operations optimization, digital marketing, and personalizing customer experiences. It also touches upon the challenges and strategic approaches banks are adopting to leverage AI effectively
Table of Contents
- Introduction to AI in Financial Services
- Adoption and Implementation of AI in Banking
- AI in Fraud Detection and IT Operations
- Enhancing Customer Experience through AI
- AI in Wealth Management and Investment
- Business Success and AI-First Business Models
- Regulatory Challenges and Risk Management
- The Importance of Skills and Culture in AI Adoption
Key Findings and Insights
This report will give you an insight into:
- Adoption of artificial intelligence (AI) in financial services is maturing as banks implement it across a range of innovative use cases. A new survey of IT executives in banking finds that 85% have a “clear strategy” for adopting AI in the development of new products and services.
- Diverse Applications of AI: AI is being used for a variety of purposes in the banking sector, beyond the initial low-risk applications. Fraud detection is a primary application, with banks leveraging AI to reduce losses and enhance customer experiences.
- AI in Wealth Management: In the wealth management domain, AI tools are being utilized for portfolio optimization, market sentiment analysis, and generating risk profiles for traders. This allows banks to offer more tailored investment products to their clients.
- Emerging AI-First Business Models: AI is promoting the emergence of new business models in banking, where services can be mass-customized at scale. Almost half of the banks surveyed believe that incorporating AI into their products and services will significantly help them achieve their business priorities.
- Regulatory and Risk Management Challenges: Banks are cautious in their AI adoption due to regulatory and risk management challenges. Issues such as bias, trust, and the need for explainable AI are prominent concerns. Banks are focusing on developing AI algorithms with stronger explanatory capabilities to ensure fairness and transparency.
- Cultural and Skill-Related Challenges: Successfully leveraging AI in banking also depends on company culture and skills. Banks need to foster a culture where AI is seen as an opportunity and not a threat. Additionally, securing the right talent for AI-driven business models is a challenge, especially for smaller banks with limited budgets.
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