On May 22, 2024, Tower Research Ventures co-hosted “AI x Wall Street Night” with Edge AI Research Lab, OpenBB, and Cohere. The event brought together professionals from leading financial firms to discuss state-of-the-art AI research, practical AI solutions in production on Wall Street, and top-of-mind opportunities for AI augmentation within financial services.
The night started with a panel hosted by Tower Research Ventures that featured Mike Kraslow, Head of US Venture at Mirae Asset Global Investment, Matthew Glickman, CEO of Genesis Computing, and David Teten, Venture Partner at Coolwater Capital. The main takeaways from the panel included:
- There are many “low hanging fruit” use cases for AI on Wall Street, such as analyzing data for investment decisions, analyzing policies to identify compliance issues, personalizing communications, and performing sentiment analysis.
- Financial firms are subject to strict information security and compliance requirements which leads most firms to deploy AI technology on premises or in a Virtual Private Cloud (VPC) environment.
- LLMs are being utilized to automate repetitive tasks such as note taking, reporting, and synthesis that are currently being performed by investment analysts.
Panelists discuss opportunities for AI applications within financial services.
After the panel there was a demonstration session that began with Didier Lopes of OpenBB presenting the OpenBB Terminal Pro and its latest AI features. Terminal Pro is an advanced AI-powered investment research tool which is part of the OpenBB open-source investment research software platform. The tool enables users to leverage proprietary data sets, private endpoints, RSS feeds, and publicly available datasets such as SEC Filings to generate analyses and visual outputs using natural language. Analyses include algorithmic and quantitative time-series analysis, current events and macro trend analysis, portfolio optimizations, and the ability to train models with any time-series data to create forecasts and analyze audio data.
Dider Lopes presenting his AI Financial Terminal, OpenBB
Next, Erik Bovee of MindsDB demonstrated the MindsDB platform, including its knowledge base functionality. A knowledge base is a RAG system that users can create and insert data into, and query as if it were a table. Internally, the knowledge base uses a vector store and an embedding model, which firms can define as they see fit. MindsDB integrates directly with a user’s database, data warehouse, or data stream, eliminating the need to build and maintain complex data pipelines or separate AI/ML deployment systems.
In the third demo session, Elliot Choi of Cohere presented Cohere’s state-of-the-art large language models and their comparison in a benchmark with GPT-4 turbo. His presentation of the foundation model highlighted the robust guardrails Cohere has engineered into its model, which focuses on enterprise deployments.
Finally, there were community demos. Matthew J. Glickman presented his new startup Genesis Computing, which can create new AI bots embedded within existing tools like Slack. Cordell Tanny presented TrendTrophets, which combines four ML models to cluster investment funds based on the fund manager’s behavior regarding factor exposures. Sean Austin shared his work with Markets EQ, which uses tone of voice to analyze earnings calls and investor presentations – he even shared how he analyzed the presentation of one of the preceding speakers on the spot. Michael Yuan concluded the session with WaverlyAI, which automates Excel workflows for investment bankers and private equity professionals.
If you are building in this space, we’d love to chat. Please reach out to Tower Research Ventures at ventures@tower-research.com!
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