Understanding Technology, Big Data and AI
More Technology, Big Data and AI Content
Agentic AI For Finance: Workflows, Tips, and Case Studies
Explore how autonomous AI agents are transforming finance in this practical guide from the Automation Ahead series. Discover foundational building blocks, real-world workflows and case studies to help investment professionals implement agentic systems responsibly.
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.
Featured Content
Decision Architecture: The Real AI Edge
AI's greatest value may lie in enhancing, not replacing, human judgment. Markus Schuller, Michelle Sisto, PhD, Wojtek Wojaczek, PhD, Franz Mohr, Patrick J. Wierckx, CFA, Jurgen Janssens, and Leonardo Fabbri explain why effective decision architecture is essential to realizing AI's potential.
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.
Risk, Models, and Financial Decision‑Making
Petter Kolm, PhD and Gordon Ritter, PhD, join Lotta Moberg, PhD, for a conversation on quantitative models, risk, and financial decision‑making.The discussion examines how models are constructed and evaluated, the assumptions that underpin them, and the trade‑offs involved when applying theory to real‑world financial problems. Kolm and Ritter share perspectives on model risk, uncertainty, and the role of judgment alongside data, offering insights relevant to both researchers and practitioners working at the intersection of finance and analytics.
Quantum in Practice: Real Use Cases Reshaping Investment and Risk Workflows
A practitioner-focused breakdown of quantum’s first real financial applications. Clarifies which optimisation, pricing, and risk problems are tractable with hybrid quantum-classical methods today, which remain aspirational, and what the transition to post-quantum secure infrastructure requires.
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.