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Banking 2.0: Embracing AI, Legal Challenges and Efficient Development

Hosts and Presenters

Summary

1) Adam’s Presentation on AI Overview and Industry Impacts

Introduction and Structure:

Adam opened the webinar, titled “Baking 2.0,” by highlighting its unique focus on AI technology, the accompanying legal challenges, and efficient solution development. He welcomed attendees and shared his screen to begin the presentation.

Historical Context:

Adam provided a brief history of AI, starting with theoretical discussions in the 1940s by Alan Turing and Isaac Asimov. He traced the formal beginning of AI as a research field to the Dartmouth summer research project in the mid-1950s. He noted the fluctuating interest and progress in AI over the decades, with significant milestones like IBM’s Deep Blue defeating world chess champion Garry Kasparov in 1997.

Current AI Landscape:

Adam explained the resurgence of AI, driven by advancements in deep learning, data availability, and computational power. He illustrated this with Google’s AlphaZero, which learned to play chess in just four hours and defeated the reigning computer champion, Stockfish. Adam highlighted the importance of large language models (LLMs) and the widespread acceptance of AI, catalyzed by the pandemic and services like ChatGPT.

Future Impact and Organizational Change:

Adam discussed AI’s potential to revolutionize various sectors, emphasizing its role in automation, innovation, and organizational restructuring. He stressed the need for businesses to start gaining AI experience and align IT with business strategies. He touched on the challenges of AI integration, including biases, deepfakes, and societal impacts like job losses.

Industry-Specific Insights:

He provided examples from the financial sector, mapping out AI use cases based on risk and benefit. He categorized changes into non-core, core, and differentiating areas, explaining that while most current AI implementations are in non-core and core areas, future innovations will likely focus on differentiating areas such as personalized banking and automated financial advisory.

Regulatory Environment:

Adam concluded his segment by discussing the regulatory landscape. He compared the EU’s proactive approach with the AI Act to the more industry-specific regulations in the UK and the cautious stance of Switzerland. He emphasized the importance of considering data regulations like GDPR when implementing AI solutions.

Selected Use Case: Chat-bot support for Sales / Relationship Managers

One notable example discussed was the use of chatbots to support sales and relationship managers. These AI-driven tools can enhance customer service by:

• Providing instant, accurate responses: Based on predefined templates and continuous learning from interactions.

• Ensuring compliance: Adhering to regulatory standards in all communications.

• Integrating sales strategies: Supporting cross-selling and up-selling initiatives.

• Reducing workload and stress: Allowing managers to focus on strategic tasks by handling routine inquiries.

The business benefits of such AI applications include increased efficiency, consistency, compliance, and customer satisfaction.

2) Tom’s Presentation on Legal Implications of AI

Introduction:

Tom, a partner at a Zurich law firm specializing in data protection and AI-related issues, began by acknowledging the growing relevance of AI in legal discussions. He aimed to provide an overview of the most pertinent legal aspects of AI.

AI in Financial Markets:

Tom noted that AI is increasingly adopted in financial markets to support internal processes, risk management, pricing, and customer interaction through tools like chatbots. He highlighted the autonomy and complexity of AI systems, which introduce various legal risks.

EU AI Act:

Tom detailed the EU AI Act, the first comprehensive regulation on AI by a major regulatory authority. He explained its risk-based approach, categorizing AI applications into minimal, limited, high, and unacceptable risks, each with corresponding compliance requirements. He emphasized the importance of understanding which AI applications are prohibited and the complexities involved in implementing high-risk applications.

Relevant Laws:

Tom discussed several legal domains impacted by AI:

• Data Protection Law: Focused on who handles personal data, the importance of data processing agreements, international data transfer, transparency, and the rights of data subjects.

• Copyright Law: Addressed issues like using protected third-party content for AI training and the challenge of copyrighting AI-generated content due to the lack of human creation.

• Banking Secrecy:Highlighted the need for stringent data security measures, ensuring compliance with confidentiality, and safeguarding against unauthorized access by foreign authorities.

Practical Implementation:

Tom provided practical advice for implementing AI projects, such as ensuring quality and adequacy of AI output, testing rigorously, and considering human intervention in automated processes. He emphasized the importance of addressing potential biases and legal disclaimers in AI outputs.

Regulatory Expectations:

He outlined the Swiss Financial Market Supervisory Authority’s (FINMA) expectations for AI in financial services, including robustness, reliability, governance, transparency, and non-discrimination. These principles align with those of other European supervisory authorities.

3) Carly’s Presentation on Builder.ai’s Approach to AI in Software Development

Introduction to Builder.ai:

Carly introduced Builder.ai, emphasizing their composable software approach, which uses pre-built features to streamline development and minimize repetitive coding. She highlighted Builder.ai’s global presence and strategic partnerships with companies like Microsoft, which enable continued AI innovation and investment.

AI Integration:

Carly explained how Builder.ai integrates AI into their software development process, using AI to understand client needs and ensure clear timelines and costs. She mentioned their capability to build production-ready large language models (LLMs) and their commitment to integrating AI into their own intellectual property to enhance client project management.

Company Overview:

She provided a high-level overview of Builder.ai, including their headquarters in London, a global team of over 1,000 employees, and significant funding raised to date. Carly stressed their ability to access top talent and invest in research and development to stay at the forefront of AI technology.

4) James’s Demonstration of Builder.ai’s AI Product, Natasha

Introduction to Natasha:

James, a product manager at Builder.ai, demonstrated Natasha, an AI product manager that assists clients in building software applications. He explained the difference between assistants and agents, with Natasha being an agent capable of taking actions.

Live Demonstration:

James conducted a live demo, showing how Natasha interacts with users to understand their project requirements. He illustrated how Natasha uses natural language processing to create a software blueprint by asking questions and interpreting user inputs. Natasha can understand text from documents and generate project specifications, adding design elements and features based on user needs.

Application Use Case:

James used an example of a web-based conversational agent designed to assist sales representatives by providing answers to customer queries. Natasha guided the process of defining features, creating a design, and estimating costs. James highlighted Natasha’s ability to generate summaries and detailed project specifications, making the software development process more efficient and user-friendly.

AI-Driven Features:

James showcased how Natasha leverages AI to generate code, test it, and provide documentation. He demonstrated the flexibility of the platform, allowing users to refine their project over time and interact with Natasha to get detailed insights into the development process.

Conclusion:

Carly and James emphasized the practical applications of Builder.ai’s technology, offering a seamless software development experience. They highlighted the ability to integrate AI-driven tools into client projects, enhancing efficiency and innovation.

Closing Remarks and Q&A:

Adam wrapped up the session by acknowledging the detailed presentations and the importance of the topics covered. He noted the limited time for questions but encouraged attendees to reach out for further information. He promised to send out the presentation slides and transcript for attendees to review at their own pace.

The full presentation can be downloaded here:

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