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RPC Labs 1

Welcome to RPC Labs

An Open Community at the Intersection of Finance and Technology Explore GitHub Repositories

What Is RPC Labs?

RPC Labs is a CFA Institute Research and Policy Center initiative designed to foster collaboration between finance professionals, data scientists, and developers.

Repository Showcase

  • This repository contains accompanying code for the CFA Institute's Research and Policy Center 'Synthetic Data in Investment Management' report.
    Active
    Last updated Jul 28, 2025 • View on GitHub
  • Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
    Active LLM
    Last updated May 08, 2026 • View on GitHub
  • An open-source platform for modeling systemic climate transition risks in financial systems. Developed by CFA Institute RPC & UK CGFI.
    Active Collaboration
    Last updated Jan 13, 2025 • View on GitHub
View All Repositories

Why It Matters

  • Practical innovation: RPC Labs provides tools, resources, and a community to address real-world challenges in portfolio management, risk analysis, and more.
  • Navigate change: Technology is transforming investment management. Tools such as AI, machine learning, and open-source collaboration are becoming essential.
  • A collaborative ecosystem: By connecting experts from finance and technology, RPC Labs accelerates innovation while helping members develop future-ready skills.

Why Should Investment Professionals Use These Platforms? 

  • GitHub

    • A modern workspace: GitHub is where today's innovation happens. From managing version control to collaborating on tools, it’s the backbone of open-source development.
    • Hands-on tools: Explore GitHub for ready-to-use financial models and open-source tools for portfolio analysis, AI applications, and more.
    • Learn and contribute: Even if you're not a coder, GitHub allows you to propose ideas, review tools, and learn how tech-driven workflows work.

  • Discord

    • Real-time engagement: Join discussions with peers and experts, ask questions, and share insights in a dynamic, interactive environment.
    • Bridging the gap: Discord makes complex topics approachable through structured channels, live events, and collaborative problem solving.

  • Why Now?

    • Stay relevant: As AI and technology redefine the industry, familiarity with platforms like GitHub and Discord will give you a competitive edge.
    • A safe learning space: RPC Labs is designed for finance professionals new to technology, offering tutorials and beginner-friendly resources.

Get Started

Github logo

Getting Started with GitHub

  1. Create your GitHub account if you don't have one already. 
  2. Learn the basics with the GitHub Introduction Guide. 
  3. Explore repositories, understand version control, and start navigating open-source projects.
Discord logo

Joining and Navigating Discord

  1. Log in or register for a free Discord account. 
  2. Join the Official RPC Labs Discord Server. 
  3. Complete the onboarding process, which covers communication etiquette and Discord usage tips.
  4. Start collaborating and participating in discussions.
RPC Logo for RPC Labs

Contributing to RPC Labs Projects

  1. Review our Code of Conduct to understand our community values.
  2. Follow the Contribution Guidelines for submitting ideas or code.
  3. Browse existing projects and issues to find areas where you can contribute.
  4. Start a discussion for new feature requests, bug reports, or opportunities to improve.

Research Related to RPC Labs

Featured

Brian Pisaneschi, CFA: Demystifying AI for Smarter Investing
Enterprising Investor Podcast

Demystifying AI for Smarter Investing

With Brian Pisaneschi, CFA

CFA Institute Research and Policy Center senior investment data scientist Brian Pisaneschi, CFA, breaks down the future of AI in investing—covering retrieval-augmented generation (RAG), agentic workflows, and why human creativity remains your strongest edge. Discover how to pair large language models with accurate data to cut through noise, reduce hallucinations, and make smarter decisions.
Listen now to sharpen your AI investing skills—and explore Brian’s in-depth articles on the CFA Institute Research and Policy Center website, rpc.cfainstitute.org.
RAG - Automation Ahead Series
Research

RAG for Finance: Automating Document Analysis with LLMs

By Brian Pisaneschi, CFA

This article explores how retrieval-augmented generation (RAG) enhances investment research by enabling LLMs to analyze unstructured documents like proxy statements. Through a detailed case study, it highlights RAG’s strengths in retrieving governance and compensation data—and its limitations with nuanced reasoning and quantitative precision. The piece offers practical guidance on structuring RAG workflows, enriching metadata, and combining RAG with agents and function calling for more robust automation.

 3D illustration Rendering of binary code pattern Abstract background.Futuristic Particles for business,Science and technology
Research Report

Synthetic Data in Investment Management

By James Tait

Understanding where automation can deliver the most value is a critical first step. This introduction and automation framework provide a foundation for developing an intuitive understanding of the technology, while identifying high-impact opportunities for GenAI-driven automation to help professionals think strategically about its applications

 Learning compass product image
Research Report

Practical Guide for LLMs in the Financial Industry

By Alex Spyrou and Brian Pisaneschi, CFA

This guide provides an overview of how financial professionals can select, evaluate, and deploy artificial intelligence (AI) models tailored to financial tasks, helping maximize efficiency, insight quality, and return on investment in adopting AI into their workflows.
Automation Ahead content series
Research

The Automation Ahead Series

By The Research and Policy Center

This series breaks down the reality of GenAI’s current state, guiding you through the innovations, possibilities, and risks of this new wave of automation.

CFA Institute AI Investment Challenge

question-that-quants-should-answer-for-single-trade

What is the Challenge?

The CFA Institute AI Investment Challenge is a global student competition where university teams apply artificial intelligence to real-world investment problems. It helps students build practical skills in investment analysis, data, and responsible AI use.
supply chain madness
Enterprising Investor

AI’s Role in Addressing Risk in Supply Chains at Scale

1st Place

What if AI could spot supply chain risk months before it shows up in a company’s financial results? Ebro Dossajee, Bradley McCann, and Connor O’Keeffe demonstrate how AI can analyze shifts in 10-K and 10-Q disclosures at scale, surfacing early signals across hundreds of suppliers. Their innovation illustrates how AI can enhance human judgment by directing analysts' attention to risks hiding in plain sight.

 trading volume
Enterprising Investor

Using AI to Develop Optimal Trade Execution Strategies

2nd Place - QuantFin Exeter

Even the right investment call can lose money through poor execution. A team of CFA Institute AI Investment Challenge finalists explores how reinforcement learning can adapt trades to changing market conditions, potentially cutting execution costs while keeping AI decisions transparent and explainable.

 EarningsIQ
Enterprising Investor

Can AI Decode Not Just What Management Says, but How They Say It?

3rd Place - EarningsIQ

Can AI detect what traditional earnings analysis misses? EarningsIQ analyzes both earnings call transcripts and executives' vocal tone to assess management confidence. Developed by a team of students from Heriot-Watt University and the University of Glasgow in the inaugural CFA Institute AI Investment Challenge, the platform demonstrates how explainable AI can help investors uncover deeper insights.