Learnings From Our "AI in Finance & Investing" Webinar
"Educate, Experiment, Collaborate"
👋 Hi, I’m Andre and welcome to my newsletter Data-driven VC which is all about becoming a better investor with data & AI. Every Tuesday, I publish “Insights” to digest the most relevant startup research & reports. Every Thursday, I publish “Essays” that cover hands-on insights about data-driven innovation & AI in VC, and every Sunday, I publish “Picks” to spotlight the hottest Stealth, Early, and Growth Startups. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
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Last week, I had the chance to co-host an “AI in Finance and Investing” webinar with Nicolas Boucher. He is the founder of the AI Finance Club (get 50% discount via this link until 2nd August COB PT), the place where finance professionals learn and stay up to date on how to use AI in Finance. More than 1,5 million professionals follow Nicolas’ daily insights and he has trained over 5,000 finance professionals on how to properly use AI.
Nicolas initially reached out following my “Run the numbers” podcast interview with the one and only
. After jumping on a call and getting to know each other, we quickly figured that our interests perfectly complement each other.Some incredibly valuable conversations later, we thought it would be interesting for our communities to join us in exploring the intersection of AI in Finance and Investing. With 1k+ signups and professionals joining from all over the world, the learnings from this session might also be relevant for you, so I’m happy to share a summary below.
The Evolution and Current State of AI in Finance
To start off, Nicolas emphasized that AI's presence in finance is not a new phenomenon. While tools like GPT have recently democratized AI, making it more accessible to a broader audience, the technology has been in use for years.
He highlighted the necessity of understanding AI as a learning and evolving tool, similar to human cognition, capable of improving its performance over time.
Implementing AI for Investing
Switching sides, I shared some insights into how we leverage data-driven approaches and AI at Earlybird with our proprietary platform called “EagleEye”.
In terms of LLM uses cases, we already leverage them across large-scale data collection, deduplication and entity matching, competitive landscape and similarity mapping, drafting of investment memos, founder interaction, and a lot more.
The implementation of AI has not only increased the efficiency of our investors but also their effectiveness by enabling them to focus on high-potential opportunities.
Steps to Learning and Implementing AI in Finance
Nicolas provided a practical roadmap for finance professionals looking to integrate AI into their workflows. The three major items are: