To mark Enterprising Investor’s 10th anniversary, we have compiled retrospectives of our coverage of the most critical themes in finance and investing over the last decade.
The next big thing is always elusive.
When the first Enterprising Investor post with fintech in the title was published almost exactly six years ago, little did we know that artificial intelligence (AI) and big data would become that “next big thing” in the financial services industry and in our research efforts in the years since.
It has been a fascinating journey.
The Pre-AI Years
Despite all the buzz about fintech replacing the financial industry, we quickly realized that peer-to-peer (P2P) lending, mobile payments, and robo advice prospered mostly in underserved markets. So in that sense, early-stage fintech complemented the established financial services industry.
Another foregone conclusion today that was far from consensus when we first anticipated it is that successful fintech tends to embrace the Fin plus Tech model. The applications with the best prospects, in other words, are those that emphasize collaboration between finance and technology in order to overcome the inherent weaknesses of each in isolation.
Looking for Information: How Does AI in Investing Work Conceptually?
Beyond fintech, as we looked around for other potential disruptors, AI and big data quickly came onto our radar as well. Our series of articles on the subject in February and March 2018 was propitiously timed: It coincided with peak interest in AI over the last decade according to Google Trends. Installments in the series quickly scaled the list of most popular articles for the month and the year, and remain among the most-read EI posts in this area today.
We compiled this series along with additional EI contributions and content from external authors into Fintech in Asia-Pacific: 2018 Edition. This collection gives investment professionals the basic information on how AI and big data in investment work. Indeed, it yielded an important finding: The Fin plus Tech model has evolved into a new development stage. It is now AI plus HI, or human intelligence, in this emerging age of AI investing.
Looking for Proof: How Does AI in Investing Work in Reality?
Having sampled the benefits of these innovations, the pioneers in this business grew convinced that AI and big data had transformative potential. The vast majority of the industry, however, still had doubts or faced practical hurdles.
What our stakeholders needed at that juncture was not only information but proof, proof that these fancy technologies had useful real-world applications. We tested that hypothesis in May 2019 and received a warm reception. So we went to work, and several months later produced a series of case studies from 11 firms. The collection explored how these firms, spread across three continents and four business lines, applied AI and big data to improve their investment processes.
Our summary of the key findings from the report was featured on EI. We followed that up with a post addressing frequently asked questions we had encountered from readers and from the audiences to whom we presented the report around the world.
These questions still come up often today, so the writeup remains a good resource. Meanwhile, other contributors have filled out our coverage with compelling case studies of their own.
Looking to Try: How Can My Firm Apply AI in Our Business?
This is where the rubber hits the road and is perhaps the most exciting part of the AI and big data journey. It’s also becoming one of the more difficult areas on which to offer advice. After all, each firm is unique and each individual situation is different.
With that in mind, we provide readers with high-level frameworks they can leverage as they develop their own roadmap. The first framework is organizational and is the subject of our recent “T-Shaped Teams” report. You’ll continue to find related content as well as forecasts from luminaries on the cutting edge of fintech, AI, and big data here on EI. So stay tuned!
It’s been an incredible experience supporting readers as they navigate this new AI- and big data-driven world. We hope you’ve enjoyed the trip as much as we have. Above all, we hope that the content has been informative and helpful to your career development.
Below are some of the most important EI articles in this area.
Six Years of Fintech, AI, and Big Data on Enterprising Investor
In his seminal contribution to the CFA Institute Research Foundation, BlackRock’s Ronald N. Kahn identified big data as one of the seven major trends shaping the investment industry today. At the CFA Institute Annual Conference in 2019, he went further and narrowed down the most important trends to big data and smart beta. This post by Paul McCaffrey considers Kahn’s analysis.
Machine Learning for Asset Managers by Marcos M. López de Prado earned high praise for its quantitatively minded analysis of machine learning applications in investing. The barriers to entry are high though. Practitioners need at least basic programming and machine learning knowledge to benefit from this book, according to reviewer Mark S. Rzepczynski.
Fintech is revolutionizing the financial planning industry and forcing a change in how wealth is managed. The drive toward efficiency and agility in practice management benefits both clients and advisers. Marguerita Cheng, CFP, RICP, provides an overview on the changes that Robinhood and other fintech startups have brought to the wealth management business.
We are witnessing the beginning of the artificial intelligence (AI) era, Larry Cao, CFA, observes in the first installment of this three-part series on the topic. He lays out what investment managers need to know about AI, deep learning, and machine learning.
Artificial intelligence (AI) is coming to the investment world, Larry Cao, CFA, reports. Given AI’s superior computing power and lack of behavioral biases, some in the investment industry and academic circles believe it will come to dominate the sector. Will it?
In the final installment of his three-part series exploring the impact of AI on investment management, Larry Cao, CFA, explains why AI and big data will not actually replace human investors. Rather the AI plus HI (human intelligence) model will rule the future of investment management.
Artificial intelligence may be among the latest buzzwords in finance, but applying it to investment decision making will disrupt the industry and benefit those investors who harness its power, Dan Philps, CFA, explains.
Will computers completely replace humans in financial management? Raphael Douady, PhD, Milind Sharma, and Paul McCaffrey explore that question as they consider the implications machine learning may have on the investment industry.
Larry Cao, CFA, breaks down some of the essential findings from his AI Pioneers in Investment Management research report.
The AI Pioneers in Investment Management report inspired some compelling questions — and answers. Larry Cao, CFA, addresses several of the big ones.
How can AI transform how investment products are distributed? Alon Bochman, CFA, outlines a case study that demonstrates that when properly harnessed and guided by human judgment, AI can create more efficient and effective processes.
Andrew W. Lo and Ajay Agrawal focused on three principal concepts that they expect will shape the future of AI and big data in a conversation with Mary Childs at the inaugural Alpha Summit by CFA Institute. Larry Cao, CFA, distills their main insights.
For more from Larry Cao, CFA, sign up to receive The Handbook of Artificial Intelligence and Big Data Applications in Investments from the CFA Institute Research Foundation.
If you liked this post, don’t forget to subscribe to the Enterprising Investor.
All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
Image credit: ©Getty Images / MR.Cole_Photographer
Professional Learning for CFA Institute Members
CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker.