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Summary of AI and You: Perceptions of Artificial Intelligence from the EMEA Financial Services Industry

Core Content

This report explores the perceptions of Artificial Intelligence (AI) within the EMEA Financial Services Industry (FSI), focusing on its current state, potential applications, and the challenges and opportunities it presents. It is based on a survey conducted by Efma and Deloitte in February 2017, involving over 3,000 respondents, primarily C-level executives from financial services firms.

Main Points

1. Definition and Evolution of AI

• AI refers to technologies capable of performing tasks that require human intelligence, such as understanding natural language, recognizing patterns, and making decisions.
• AI has evolved significantly since the 1980s, with advancements in data volume, algorithms (e.g., Deep Learning), and processing power (e.g., GPUs and cloud computing).
• AI is divided into three main domains: Cognitive Automation, Cognitive Engagement, and Cognitive Insights.

2. Cognitive Automation

• Involves the use of machine learning, RPA, and other tools to automate tasks traditionally done by humans.
• Examples include handwriting and character recognition, natural language processing (NLP), and document analysis.
• This domain helps reduce risk and cost in back-office and middle-office operations.

3. Cognitive Engagement

• Refers to systems that interact with people using natural language, voice, and image processing.
• These systems can provide personalized customer service, automate routine interactions, and assist in areas like HR and technical support.
• Cognitive agents are expected to play a significant role in improving customer engagement and creating new revenue streams.

4. Cognitive Insights

• Enables the extraction of meaningful patterns and relationships from large data sets.
• Provides real-time insights and predictive analytics, helping businesses make informed decisions and improve operational efficiency.
• In call centers, for example, AI can assist agents by providing relevant information from multiple data sources.

5. AI Capabilities

• AI systems can:
  • Recognize and Understand data (text, voice, images).
  • Identify semantics based on context.
  • Apply context and interact with users in a meaningful way.
  • Reason and make decisions tailored to specific environments.
  • Learn and improve through continuous feedback and data exposure.

6. AI Enablers and Technologies

• Key enablers include Machine Learning, Deep Learning, RPA, Natural Language Processing (NLP), Probabilistic Inference, and Semantic Computing.
• These technologies are crucial in enabling AI to perform complex tasks and deliver insights.

7. Current State of AI in FSI

• The survey shows that 86% of respondents had heard of AI by 2014, indicating its growing relevance.
• 91% of respondents believe AI will empower or support employees rather than replace them.
• 32% of firms are in the developing phase (building solutions or having a center of excellence), while 11% are not yet started.
• The most common AI leaders are the Head of Innovation (26%), CIO (12%), and CTO (5%).

8. Top Concerns About AI

• The main concerns include:
  • Hacking / Cybercrime (12%)
  • Scarcity of technical talent (12%)
  • Limited understanding of data technology (12%)
  • No ownership / accountability (29%)
  • Existential threat to humanity (9%)
  • Sustainability (9%)

9. AI Use Cases in FSI

• The most impactful AI use cases are:
  • Back office / operations (78%)
  • Risk Management (56%)
  • Customer service (65%)
  • Fraud detection (31%)
  • Compliance (22%)
• These applications are already being used in banking, insurance, and investment management sectors.

10. AI in the Investment Management Sector

• AI is being used in robo-advisors, pattern recognition, virtual agents, and intelligent automation.
• In the Hedge Fund sector, AI is used for quantitative investment strategies, leveraging data science and machine learning to produce better results in financial markets.

Key Information

• AI is seen as a transformative force in the financial services industry, offering opportunities for innovation, efficiency, and customer engagement.
• Despite its potential, AI implementation faces challenges such as cultural resistance, organizational readiness, and ethical and regulatory concerns.
• The report emphasizes the importance of education and training to address the AI skill gap and prepare the workforce for the future.
• AI is expected to become mainstream in 2 to 5 years by 49% of respondents, indicating a growing acceptance and integration of AI technologies.
• The European Parliament is considering regulations to govern AI, including the establishment of a European Agency for Robotics and a Code of Ethical Conduct.

Conclusion

The EMEA Financial Services Industry is at a pivotal moment in its journey with AI. While there are concerns about job displacement and ethical implications, the majority of respondents believe AI will enhance and support human work rather than replace it. The report underscores the need for strategic AI adoption, investment in talent, and the development of ethical and regulatory frameworks to ensure AI's positive impact on the economy and society.