Ditch Excel, Embrace AI: Why Python is the Future for Finance Pros - Stephanie Mertz | Ep.063
Feb 28, 2024
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Stephanie Mertz, Co-founder and CTO of Eisen, discusses leveraging AI tools, moving beyond Excel in finance, automation platforms, prompt engineering in AI, and the future of generative AI. She emphasizes the importance of foundational knowledge and building resilient systems to level up technical skills.
AI tools like Python notebooks empower finance professionals to explore beyond traditional tools.
Understanding foundational principles is crucial in utilizing AI effectively for tasks like sentiment analysis.
Balancing automation convenience with robustness is key in finance to mitigate risks and ensure long-term sustainability.
Deep dives
Empowering Tool Diversity in Tech with AI Integration
AI tools like Python notebooks provide accessible alternatives, empowering users to explore beyond traditional tools. Stephanie Mertz's journey from medical research to fintech highlights the benefits of leveraging technology in finance.
Understanding Machine Learning Through Practical Applications
The conversation delves into Layla Garani's quest to apply machine learning for sentiment analysis. Her journey from seeking AI-generated code to personally grasping the underlying principles showcases the importance of foundational knowledge.
Security Awareness in the Age of Deep Fakes and Tech Advancements
The discussion reveals the vulnerabilities posed by deep fakes, emphasizing the need for security awareness. Real-world examples like the CFO deep fake scam underscore the critical balance between embracing tech advancements and mitigating risks.
Use of Automation Platforms in Financial Analysis
Automation platforms like Python are critical in finance for their ability to enhance data analysis and prediction accuracy. By automating processes through tools like Python algorithms, financial professionals can add significant value beyond traditional financial modeling. The discussion highlights the importance of considering different levels of automation tools based on the complexity and scalability of tasks.
Balancing Automation Efficiency and Long-Term Viability
The conversation delves into the trade-off between quick automation solutions and long-term sustainability. While tools like Zapier and Power Automate offer immediate benefits, relying solely on them without considering future scalability and support could lead to challenges. Emphasizing the need to assess the criticality of tasks and have backup plans, the episode stresses the importance of balancing automation convenience with robustness.
In this episode of Tech for Finance, we interview Stephanie Mertz, co-founder and CTO of Eisen, an innovative fintech platform aiming to transform dormant account management. With deep expertise in computer science and financial technology, Stephanie shares her perspectives on leveraging AI tools to solve problems, building resilient systems, the requirement for foundational knowledge, and more. Tune in to hear Stephanie's thoughts on moving beyond traditional finance tools like Excel, considerations around automation platforms, prompt engineering in AI, and the future of generative AI. Whether you're a seasoned finance pro or just starting out, you'll come away with fresh ideas to level up your technical skills.
------ SHOW NOTES ------
- Connect with Steph on LinkedIn - https://www.linkedin.com/in/stephmertz/
- Check out Eisen - https://www.witheisen.com/
------ CHAPTERS ------
Here is a summary of the key chapters in the transcript:
(00:00:00) - Introduction to Stephanie and Aizen
(00:01:41) - Stephanie's background and experience
(00:03:30) - Stephanie's approach to solving problems
(00:05:37) - Starting the development process
(00:08:29) - Using AI tools versus Excel
(00:10:40) - Criticality levels for automation
(00:12:00) - Understanding code from AI assistants
(00:16:07) - Backup plans for critical systems
(00:20:23) - Version control and documentation
(00:26:29) - Case study on using ML for sentiment analysis
(00:29:07) - The need for foundational knowledge
(00:31:35) - Training machine learning models
(00:35:09) - Security risks from deepfakes
(00:38:15) - Using Python for analytics
(00:40:00) - Levels of automation tools
(00:42:17) - Engineering principles for critical systems
(00:49:46) - Advice on starting coding projects
(00:52:31) - The future of prompt engineering
(00:54:01) - One-shot vs. two-shot prompting
(00:58:27) - Explaining dormant accounts and Eisen
(01:00:14) - Favorite productivity tools
For more goodies, check out www.techforfinance.com
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