Understanding Technology, Big Data and AI
More Technology, Big Data and AI Content
AI in Asset Management
Artificial intelligence is transforming how investment professionals analyze markets, build portfolios, and manage risk. AI in Asset Management: Tools, Applications, and Frontiers, explores how AI and machine learning are redefining every aspect of the investment process. The book brings together global experts advancing applied finance through intelligent systems and data-driven models.
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.
An Investment Perspective on Tokenization - Part 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.
Featured Content
When Information Is No Longer the Edge
As artificial intelligence transforms investment research, eroding traditional information advantages, what creates an edge? Boecyàn Bourgade explores why human judgment, industry context, scenario analysis, and independent thinking are becoming the defining skills of successful analysts in the AI era.
Big Data Meets the Turbulent Oil Market
Using topic modeling on millions of news articles, the paper creates novel NLP indicators that outperform standard variables in forecasting oil prices, volatility, production, inventories, and energy equity returns—both in-sample and out-of-sample.
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
Policy in Action
Response to UK FCA CP25/13: Cryptoasset Perimeter Guidance
CFA Institute and CFA UK respond to the FCA’s cryptoasset perimeter guidance, supporting a substance over form approach while recommending enhanced clarity on custody, conflicts of interest, discretionary style services, and retail risks in cryptoasset lending arrangements.
Consultation Response to UK FCA CP25/40: Regulating Cryptoasset Activities
CFA Institute and CFA UK respond to the FCA's proposed rules for cryptoasset trading platforms, intermediaries, staking, and DeFi — advocating structural conflict prohibitions, best execution without carve-outs, and phased retail access to higher-risk products.
Response to UK FCA Mills Review: AI in Retail Financial Services
CFA Institute responds to the FCA's review of AI's long-term impact on retail financial services
Consultation Response to UK FCA CP25/28 – Part I
CFA UK and CFA Institute welcome the FCA’s support for technological innovation, with fund tokenisation being a prime example of the tangible application of technology in the investment sector.
Consultation Response to UK FCA CP25/25 – Part II
CFA Institute and CFA UK welcome the opportunity to respond to Part II of the CP25/25. This response addresses Chapters 1–5 of the consultation and builds on our previous submission on Chapters 6–7.
Quantitative Investing
Petter Kolm, PhD, and Gordon Ritter, PhD, join Lotta Moberg, PhD, CFA, to continue their discussion on quantitative investing, focusing on model design, implementation, and real‑world application.
Conversations with Frank Fabozzi, CFA, Featuring Francesco Fabozzi
In this episode of Conversations with Frank Fabozzi, CFA, Francesco Fabozzi explores how large language models are transforming investment workflows, from discretionary research and quantitative strategies to portfolio construction and governance. He discusses where AI creates value, the risks firms must manage, and why the future of investing will depend on combining domain expertise with AI-driven insights.
Quantum Computing vs. AI: Real-World Applications
AI is already embedded in financial workflows. Quantum computing is still emerging. Genevieve Hayman, PhD, and Oswaldo Zapata, PhD, examine how financial institutions are beginning to test quantum computing’s potential in portfolio optimization, trade execution, and risk modeling.
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.