Generative AI for Finance

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

whurley: Introduction (5 minutes) - 9:00am PT | 12:00pm ET | 4:00pm UTC/GMT

• whurley welcomes you to Generative AI for Finance.

Srini Indla and Jason Webb: Building a GenAI-Powered Development Experience to Drive Velocity (30 minutes) - 9:05am PT | 12:05pm ET | 4:05pm UTC/GMT

• Learn how Intuit is leveraging AI to improve development velocity across every stage of the product development lifecycle, and how it’s enabling Intuit’s development teams to deliver value to customers faster. From UX experiences to coding to smart observability, AI is already making developers’ lives easier and allowing them to focus on the most important things. Srini Indla and Jason Webb discuss AI in the day-to-day developer experience, share key ideas that directly impact development velocity, and demonstrate what this looks like in action.
• Srini Indla is a product management leader for the developer platform at Intuit. He leads platform strategy for API platform, UI frameworks, and conversational experiences transforming application development at Intuit. He’s passionate about building awesome products for developers. In his spare time, enjoys hiking and spending time outdoors.
• Jason Webb is a Distinguished Engineer at Intuit, where he works on building tools and platforms to enable Intuit’s microservices ecosystem. He’s passionate about cloud native infrastructure, developer tools and experience, and open source. In his free time, he enjoys spending time with his family.

Kristin M. Gilkes: The Battle Is On Between Financial Institutions and Fraudsters in the Age of AI-Generated Deepfakes (30 minutes) - 9:35am PT | 12:35pm ET | 4:35pm UTC/GMT

• Join Kristin Gilkes to discover how sophisticated AI technology is challenging traditional fraud detection methods and how deepfakes are rapidly evolving. Learn about the growing scale and volume of data that financial institutions face and the limited access to training data for building robust deepfake detection models. Kristin explores a multifaceted approach to combating deepfake threats, including AI-based fraud detection, collaboration, and knowledge-sharing among institutions; user education; and the potential of blockchain technology for secure transactions. You’ll get insights into staying ahead in the fight against financial crime and protecting the integrity of financial systems.
• Kristin Gilkes is global innovation quantum leader at Ernst & Young and oversees its Global Quantum Computing Lab. In addition, she oversees EY’s alliances to deliver quantum-related products to help clients solve problems and protect their businesses. She has led projects involving advanced analytics and automation to optimize anti-fraud approaches and has been a leader in EY’s financial crimes and fraud analytics work. Kristin led multiple financial crime projects to develop and deliver information technology and data analytics solutions to support anti-money laundering, cyber, fraud, insider threat, know-your-customer, sanctions, and trade surveillance programs.
• Break (5 minutes)

Gaurav Bhatnagar and Lisa Weaver-Lambert: Maximizing Value in M&A with Generative AI (30 minutes) - 10:10am PT | 1:10pm ET | 5:10pm UTC/GMT

• Private equity firms know how to build and manage a mergers and acquisition pipeline where building scale is critical to winning. Generative AI has the potential to materially impact the M&A deal lifecycle by streamlining processes, providing data-driven insights, and augmenting more informed decision-making. Gaurav Bhatnagar and Lisa Weaver-Lambert provide an overview of how PE investors are currently thinking of applying GenAI in investment and back-office processes as well as in a selection of post-deal, high-impact value creation use cases.
• Gaurav Bhatnagar previously built and led the advanced analytics team for a leading global private equity firm focused on driving value creation using analytics and AI. He also led commercial and product teams at Amazon and advised large corporate and private equity clients on strategy and technology all over the world. His focus is on leveraging data assets and AI to improve customer experience and accelerate commercial, product, and operational impact. Gaurav has worked with a variety of PE-owned and publicly listed companies across sectors including software, internet, brands, advertising, services, and healthcare.
• Lisa Weaver-Lambert works at Microsoft with private equity firms across diverse sectors to modernize technology, data, and AI capabilities to generate attractive investor returns. The presentation is independent of her role at the company. Previously, she worked for Accenture’s strategy and architecture practice, and in private equity as a data and digital director. She’s a respected advisor in the investment community for technology and data and is recognized as a leading woman in technology. She’s also cohost of the Private Equity Technology Podcast and an advisory board member of the Private Equity International Operators Forum.

Pahal Patangia: Generative AI—The Savior Financial Services Was Waiting For (30 minutes) - 10:40am PT | 1:40pm ET | 5:40pm UTC/GMT

• The generative AI revolution has inevitably become the cornerstone for accelerating the adoption of AI in financial services. This impacts every function and every line of business, including banking, capital markets, payments, insurance, and Fintech. Pahal Patangia discusses how financial firms are leveraging generative AI models to delight customers, enhance productivity, improve their bottom line, and gain a competitive edge in the industry. You’ll learn how to train, fine-tune, and deploy SOTA GenAI models using open source frameworks such as NeMo and the Triton Inference Server to serve downstream FSI use cases such as market research, wealth management and advisory, customer experience, claims processing, algorithmic trading, and report summarization.
• Pahal Patangia is global developer relations lead for consumer finance at NVIDIA where he focuses on driving AI adoption within the Fintech industry and helps enterprises accelerate their machine learning models at scale. Previously, he helped retail banks and financial institutions make smarter credit decisions using machine learning at FICO. Pahal holds a master’s degree in business analytics from the University of Minnesota and a bachelor’s degree in electrical engineering from the National Institute of Technology, Trichy, in India.
• Break (5 minutes)

Alessandro Recino: Tools and Techniques to Harness the Power of Generative AI in Finance (30 minutes) - 11:15am PT | 2:15pm ET | 6:15pm UTC/GMT

• Alessandro Recino discusses common techniques and tools used to enhance processes, augment agents, and build intelligent applications that use generative AI for finance use cases. He shares insights on grounding with retrieval-augmented generation (RAG), the use of orchestrators like LangChain for memory usage, and vector stores for embedding.
• Alessandro Recino is a principal technology specialist on data and AI at Microsoft, where he works for a worldwide group that focuses on digital natives. He started in the financial sector, working with enterprise customers on relational data and business intelligence and later moved into the big data and advanced analytics area. Alessandro has spent the recent past focusing on ML and AI, helping customers to define use cases and design architecture and solutions.

Devavrat Shah: Unveiling the Future of Banking Security—Real-Time Fraud Prevention with AI Powered by LGMs (Sponsored by Ikigai Labs) (30 minutes) 11:45am PT | 2:45pm ET | 6:45pm UTC/GMT

• Fraud is an ever-growing threat that drains billions of dollars from both customers and financial institutions. The business impact of unauthorized transactions, identity theft, and money laundering is immense. What if there were a way to spot fraudulent activities in real time, protecting your institution and customers? Devavrat Shah discusses how generative AI for tabular data powered by large graphical models (LGMs) is revolutionizing the way banks combat fraud. You’ll see how to create real-time risk profiles for each customer, connecting the dots between their transaction history, demographic data, and inter-customer relationships. You’ll also discover the game-changing concept of having an “expert in the loop” (EiTL), ensuring ongoing effectiveness in identifying and preventing fraudulent activities.
• Devavrat Shah is a professor and a director of MIT’s Statistics and Data Science Center as well as co-CEO and founder of Ikigai Labs. He also cofounded Celect, a predictive analytics platform for retailers, which he sold to Nike. Devavrat holds a PhD in computer science from Stanford University.
• This session will be followed by a 30-minute Q&A in a breakout room. Stop by if you have more questions for Devavrat.
• Break (5 minutes)

Jason Demby and Sovik Kumar Nath: Generative AI in Financial Services—Where Quants and Quals Unite (30 minutes) - 12:20pm PT | 3:20pm ET | 7:20pm UTC/GMT

• As financial services leaders determine the highest value propositions of generative AI, the intersection of natural language processing and quantitative machine learning insights unite. Users ranging from internal knowledge workers to external customers need the best insights provided from a mix of unstructured and structured data that may be best derived from fit-for-purpose, task-oriented AI services, custom-built quantitative machine learning models, and modes of foundation models including large language models and image generation. Multimodal agents are able to connect insights across diverse data types to gain a more comprehensive understanding and generate appropriate responses. Generative AI and multimodal agents can have several applications in financial markets. Jason Demby and Sovik Kumar Nath review the architectural patterns of multimodal agents that can understand and analyze unstructured text, structured text, and audio, and connect insights across data types to gain comprehensive understanding and generate responses.
• Jason Demby leads AI and ML business development at AWS for the US East region, focusing on the largest and most strategic enterprise customers in the financial services industry. He has deep experience in data and analytics and application modernization approaches. Jason spent most of his career in industry in product development and strategic roles at Morgan Stanley, UBS, and Credit Suisse. Jason has a bachelor’s degree in materials science and engineering from Cornell University and an MBA from the Stern School of Business at NYU.
• Sovik Kumar Nath is an AI and ML specialist solution architect at AWS and has extensive experience with end-to-end machine learning and business analytics solutions in finance, operations, marketing, healthcare, supply chain management, and IoT. Previously, he was a data scientist, an AI/ML architect, and a leader of machine learning teams for different enterprises, and he holds a patent in ML model monitoring. He has master’s degrees from the University of South Florida and the University of Fribourg, Switzerland, and a bachelor's degree from the Indian Institute of Technology, Kharagpur.

Deepak Kanungo: Generative Value at Risk (GVaR) (30 minutes) - 12:50pm PT | 3:50pm ET | 7:50pm UTC/GMT

• Two loss functions commonly used by risk managers and corporate treasurers are value at risk (VaR) and expected shortfall (ES). There are currently three methods for computing these measures: historical, variance-covariance, and Monte Carlo methods. Deepak Kanungo introduces a new method for computing these risk measures as an integral part of generative learning ensembles. He also discusses a third risk measure, generative tail risk (GTR), and discusses the advantages and disadvantages of all of these measures, including volatility and ensemble averages or expected values.
• Deepak K. Kanungo is an algorithmic derivatives trader, instructor, and CEO of Hedged Capital LLC, an AI-powered proprietary trading company that he founded in 2009. Since 2019, Deepak has taught tens of thousands of O’Reilly Media subscribers worldwide the concepts, processes, and machine learning technologies for algorithmic trading, investing, and finance with Python. Previously, Deepak was a financial advisor at Morgan Stanley, a Silicon Valley fintech entrepreneur, a director in the Global Planning Department at Mastercard International, and a senior analyst with Diamond Technology Partners. He was educated at Princeton University (astrophysics) and the London School of Economics (finance and information systems).

whurley: Closing Remarks (5 minutes) - 1:20pm PT | 4:20pm ET | 8:20pm UTC/GMT

• whurley closes out today’s event.