Understanding Technology, Big Data and AI
More Technology, Big Data and AI Content
Explainable AI in Finance: Addressing the Needs of Diverse Stakeholders
The report underscores that transparent, explainable AI is vital in finance — not only for regulatory compliance but also for institutional trust, ethical standards, and risk governance. Although automated tools help, human oversight and organizational alignment are indispensable.
Synthetic Data in Investment Management
Explore how generative AI-powered synthetic data can solve data scarcity, boost model training, and transform investment management workflows.
AI Washing: Signs, Symptoms, and Suggested Solutions for Investment Stakeholders
This report addresses the ethical concerns and risks of AI washing in finance, providing crucial questions for stakeholders to evaluate managers’ AI claims and ensure transparency, integrity, and the genuine application of AI in investment strategies.
Featured Content
The Automation Ahead Content Series
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
Creating Value from Big Data in the Investment Management Process: A Workflow Analysis
This report examines the increasing adoption of AI and big data technologies in investment management, highlighting their transformative role in workflows and decision making. It explores risks, challenges, opportunities, and global usage patterns.
Pensions in the Age of Artificial Intelligence
This report highlights how AI technologies, including generative AI and machine learning, are being implemented across the pension value chain to enhance efficiency, personalization, and governance while promoting sustainable retirement security.
Policy in Action
Response to FCA - DP25.1 — Regulating Cryptoasset Activities
CFA Institute responded to UK FCA DP25.1 regarding cryptoasset actitivies.
An Investment Perspective on Tokenization — Part I & II
This report examines the legal and regulatory changes needed for tokenization to grow responsibly while ensuring investor protection and market integrity. It analyzes global regulatory regimes, international standards, and the need for legal clarity.
Response to IOSCO Artificial Intelligence in Capital Markets
CFA Institute’s Public Comment re: IOSCO – Artificial Intelligence in Capital Markets: Use Cases, Risks, and Challenges
Be Informed
How GenAI-Powered Synthetic Data Is Reshaping Investment Workflows
Real-world data is often expensive, incomplete, or misaligned with investors’ needs. James Tait explores how generative AI is advancing synthetic data techniques by enhancing training sets, filling gaps in sentiment coverage, and simulating asset correlations and volatility. With a hands-on case study and clear evaluation methods, this post offers a practical look at how data-driven investment workflows are evolving.
Rethinking Research: Private GPTs for Investment Analysis
Baridhi Malakar, PhD, introduces a fully local, open-source GPT toolkit that lets analysts securely query research documents. No cloud, no API, no risk of data leakage. Learn how to build your own offline chatbot to analyze earnings calls, internal reports, offering memos, and more, all from your own machine.
Conversations with Frank Fabozzi, CFA
Join us for an engaging panel discussion that brings together three leading experts in asset management and financial modeling to explore the transformative trends shaping the industry.
Driving Digital Transformation: CFA Institute Research and Policy Center Explores Machine Learning and AI Advancements in Investing
CFA Institute Research and Policy Center is addressing how big data, machine learning and advancements in natural language processing, understanding, and generation will accelerate the digital transformation of the investment industry.
The theme Understanding Technology, Big Data and AI tracks the evolving opportunity set for investment firms and professionals stemming from artificial intelligence (AI), big data, and new analytical tools and technologies.
Our research recognizes that the future of the investment industry is one where big data and AI, smart machines and systems, and data analytics will play a more central role in how the world of finance evolves.