Session Presentations
PDF Downloads
Day 1
How LLMs are Transforming the Future of Fin-tech
Developing scalable and sustainable AI capabilities is no longer a nice-to-have advantage, but a must-to-have competency for companies to survive and thrive in the fast-evolving economy and meet ever-changing consumer expectations. Building AI capabilities successfully, from the ground up requires not only a deep understanding of the math and technologies, but also developing broad alignment with business strategy, stakeholders, and processes. In this session, Nan Li will share how to approach AI use cases and develop AI capabilities holistically and strategically. You will also learn about the common pitfalls to avoid.
- How can AI be leveraged to improve business strategy and production?
- What challenges may need to be considered and how can you reduce the impacts of such?
- What are the building blocks of a successful AI adoption to ensure that the strategy is holistic and achievable?
Speaker:
Karamjit Singh - Director, AI Products - Mastercard
From Hype to Production: The Blueprint to Deliver Gen AI Use Cases in Financial Services
While generative AI was the technology story of 2023, we expect 2024 will be the year when organizations shift from the art of the possible to real, tangible AI implementation. But only those who can navigate the complexities of this transformative technology will see major competitive advantage and value creation. During this session, attendees will learn:What are the data and AI trends that are top of mind for financial services executives in 2024
How organizations navigate through the complexities of gen AI and ensure that they do not fall behind
What are the critical challenges faced by technology and business leaders in the wake of concerns around data security, governance and risk.
How to Accelerate Software Delivery with Agent-Driven Development
We've all witnessed the capability of Large Language Models (LLMs) to write code. The majority of the teams have embraced LLM-powered tools like GitHub Copilot. Yet, they've only experienced marginal productivity improvements! This is primarily due to being constrained by the number of "pilots" available. Stride has innovated a groundbreaking method to transcend these limitations. We've developed asynchronous teams of LLM-powered agents that integrate seamlessly with your software development environment, adhering to your preferred practices and patterns. Tasks that could take a developer several hours to code, test, and deploy can now be ready in mere minutes. Join Stride for an exciting panel discussion where we will unveil case studies, share insights, and discuss best practices for implementing this revolutionary approach in your codebases and workflows.The Double-Edged Sword of AI in Finance
The stakes are especially high for companies working in fintech, insurance and financial services. Firms thoughtlessly rushing to deploy AI face a minefield of new risks including unintended biases, improper use of data and other issues that can lead to major regulatory consequences and impact individuals, families and society as a whole.No data, no AI: why innovation will only come from imperfect data in real-world settings
Keys to making Generative AI work for finance and insurance
Insights from my experience at Barclays, Yahoo! Microsoft Research, The Institute for Experiential AI and more.
What we’ve learned from partnering with finance and insurance companies
How a Responsible AI strategy drives business value.
RAG: 3 Letters For Faster and Smarter Financial Decisions
This session provides an overview of how Retrieval-Augmented Generation (RAG) can enhance financial decision-making by utilizing unstructured data. Attendees will explore the technology's fundamentals, its application in financial services, and its role in improving accuracy and speed in operations.
Anji Ismail is the CEO of Finnt, an AI-native financial analysis and research platform. Finnt specialized in extracting crucial data from large, unstructured, and complex documents—including OMs, PPMs, 10-Q/10-K, as well as prospectuses, reports, leases, loans etc. It then integrates these findings into templated memos, enriched with the company's existing data and real-time market insights.
Day 2
In this session, Zoiner Tejada will raise the alarm on compliance issues enterprises may not be considering in their excitement to unlock the potential of AI in their organization and what to do about it:
Empower and govern growth from one AI agent to one AI agent per employee
Ensure that an AI agent acting on behalf of an employee doesn't get more access to data than the employee would have directly
Establish a perimeter of what sensitive information (e.g., trade secrets, PII, etc.) gets sent to the underlying AI model, and what employees are allowed to see in AI model responses
- Discussion of the potential of machine learning and other AI-based techniques for detecting and preventing fraud
- Examination of the challenges and limitations of using machine learning for fraud detection and ways to overcome them
- Explore Use-Cases of how banks and financial services are combatting card and payment fraud
Download PDF Presentation
-What are the primary legal implications you should consider when designing an AI application?
-How do your design choices impact how quickly you can sign up new customers for your AI-related service?
-What changes may be on the horizon for the current legal landscape surrounding AI over the next year?
In the rapidly evolving landscape of Capital Markets, leveraging advanced data analytics and AI has become a cornerstone for front office innovation. This session aims to illuminate the path for investment professionals, portfolio managers, quants, and research analysts to harness the full potential of their data assets. With a focus on practical, high-impact use cases, we delve into how Generative AI is revolutionizing front office operations, from alpha generation to trade execution and risk management. Discover how best of breed technologies empower Hedge Funds, Asset Managers, and Banks to not only navigate the complexities of today's financial markets but to thrive by making more informed, data-driven decisions.