Understanding Technology, Big Data and AI
More Technology, Big Data and AI 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.
Investment Model Validation: A Guide for Practitioners
As the investment landscape evolves, proactive model validation is critical for the reliability and effectiveness of any investment process. This monograph provides a practical, detailed overview of validation tools available to practitioners.
Unstructured Data and AI: Fine-Tuning LLMs to Enhance the Investment Process
Access to powerful LLMs like ChatGPT is reshaping roles in the investment profession. This report discusses how to ethically build investment models in the open-source community. It defines alternative data and presents an ESG investing case study.
Featured Content
How Much Does ChatGPT Know about Finance?
Finance applications of large language models (LLMs) have implications for practitioners and researchers. Analysis shows that some models and methods are associated with higher levels of accuracy, making use of LLMs task specific, not job specific.
Dangers and Opportunities Posed by the AI Skills Gap in Investment Management
AI is more than just another technology. It is a transformative force with the potential to redefine investment management. The industry's most significant barrier to harnessing this power is the widening AI skills gap, cautions Dan Philps, PhD, CFA.
Ken Laudan: Investing in the Age of AI
Join Mike Wallberg, CFA, and Ken Laudan, portfolio manager of Buffalo Fund's Blue Chip Growth Fund, for a thought-provoking discussion on the future of AI in investing. Ken shares his contrary view on AI's transformational potential, drawing on his extensive experience as a sell-side analyst and buy-side portfolio manager.
Policy in Action
AI’s Game-Changing Potential in Banking: Are You Ready for the Regulatory Risks?
As AI and big data transform the financial services sector, investment professionals face new opportunities and challenges. Md Nasim Akhtar, FDB, makes his Enterprising Investor debut with a focus on banking. He identifies six key regulatory concerns and actionable steps to mitigate them. As regulators continue to refine their understanding of AI and big data, financial institutions have an opportunity to shape the regulatory landscape by participating in discussions and implementing responsible practices, he recommends.
AI in Investment Management: Ethics Case Study Part II
In this post, Jon Stokes reveals how well you applied the Codes and Standards to analyze the case study presented in Part 1.
AI in Investment Management: Ethics Case Study
As with any cutting-edge investment practice, managers must be diligent in ensuring new practices do not run afoul of the fundamental ethical principles of integrity, transparency, competency, diligence, and protecting clients. Jon Stokes presents a case study of AI in the investment management process and related client communications. Can you identify the ethical issues that arise?
Be Informed
Utilizing Data Science and AI in the Investment Process
Register to hear investment professionals explore practical applications of data science and AI in investing. Learn essential skills, challenges, and future trends shaping AI-driven investment strategies.
Conversations with Frank Fabozzi, CFA, featuring Manish Chakrabarti, Arpit Narain, CFA, and Anil Sood
In this episode, Frank Fabozzi, CFA, speaks with three technology leaders in the investment industry about developing and implementing artificial intelligence (AI) responsibly.
How Machine Learning Is Transforming Portfolio Optimization
Using machine learning (ML) algorithms in portfolio optimization is a growing trend to which investors should pay attention. Investors will benefit from a basic understanding of ML algorithms and the impact these algorithms have on their portfolios, writes Jordan Doyle. His article aims to provide an overview of the role ML algorithms play in the portfolio optimization process.
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.