Tick Entrepreneurial Investor’n our tenth anniversary, we have compiled retrospectives of our coverage of the most critical topics in finance and investing over the past decade.
The next big thing is always elusive.
when the first Entrepreneurial Investmentr 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 the “next big thing” in the financial services industry and in our research efforts in the later years. .
It has been a fascinating journey.
The years before AI
Our more formal fintech coverage began in the spring of 2016. This included the Fintech Files series and many more submissions from external contributors.
Despite all the hubbub about fintech replacing the financial industry, we quickly realized that peer-to-peer (P2P) lending, mobile payments, and robotic advice mostly thrived in underserved markets. So in that sense, early-stage financial technology complemented the established financial services industry.
Another foregone conclusion today that was far from the 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. to overcome the inherent weaknesses of each separately.
Seeking information: How does AI in investing work conceptually?
Beyond fintech, as we searched for other potential disruptors, artificial intelligence and big data quickly appeared on our radar as well. Our series of articles on the subject in February and March 2018 was timely: it coincided with the highest interest in AI over the past decade according to Google Trends. The installments of the series quickly climbed the list of most popular articles of the month and of the year, and remain among the most read. NO publications in this area today.
We collect this series along with other NO contributions and contents of external authors in Fintech in Asia-Pacific: 2018 Edition. This collection provides investment professionals with the basics of how AI and big data work in investing. In fact, it yielded an important finding: the Fin plus Tech model has evolved into a new stage of development. Now it’s AI plus HI, or human intelligence, in this emerging era of AI investment.
Looking for proof: How does AI in investing work in reality?
After testing the benefits of these innovations, the pioneers in the business became convinced that AI and big data had transformative potential. However, the vast majority of the industry still had doubts or faced practical obstacles.
What our stakeholders needed at that time was not just information, but proof, proof that these sophisticated technologies had useful applications in the real world. We tested that hypothesis in May 2019 and received a warm welcome. So we got to work, and several months later produced a series of case studies of 11 companies. The collection explored how these companies, spread across three continents and four lines of business, applied AI and big data to improve their investment processes.
Our summary of the key findings of the report was presented in NO. We followed up with a post addressing frequently asked questions we had encountered from readers and audiences we report to around the world.
These questions still come up frequently today, so the report remains a good resource. Meanwhile, other contributors have rounded out our coverage with compelling case studies of their own.
Looking to test: How can my company 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 is also becoming one of the most difficult areas in which to offer advice. After all, every business is unique and every individual situation is different.
With that in mind, we provide readers with high-level frameworks that they can build on as they develop their own roadmap. The first framework is organizational and is the subject of our recent “T-shaped teams” report. You will continue to find related content as well as luminary forecasts on the cutting edge of fintech, AI and big data here at NO. So stay tuned!
It has been an incredible experience supporting readers as they navigate this new world powered by AI and big data. We hope you enjoyed the trip as much as we did. Above all, we hope that the content has been informative and useful for the development of your career.
Below are some of the most important NO articles in this area.
Six years of Fintech, AI and Big Data in Entrepreneurial Investor
Seven Trends in Investment Management: Ronald N. Kahn
In its fundamental contribution to the CFA Institute Research Foundation, BlackRock’s Ronald N. Kahn identified big data as one of the top seven 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.
Book Review: Machine Learning for Asset Managers
Machine learning for asset managers by Marcos M. López de Prado received high praise for his quantitative analysis of machine learning applications in investing. However, the barriers to entry are high. Professionals need at least basic knowledge of programming and machine learning to benefit from this book, according to reviewer Mark S. Rzepczynski.
Fintech: revolutionizing wealth management
Fintech is revolutionizing the financial planning industry and forcing a change in the way wealth is managed. The drive toward efficiency and agility in practice management benefits both clients and advisors. Marguerita Cheng, CFP, RICP, provides an overview of the changes that Robinhood and other fintech startups have brought to the wealth management business.
Artificial Intelligence, Machine Learning, and Deep Learning: An Introduction
We are witnessing the dawn of the era of artificial intelligence (AI), observes Larry Cao, CFA, in the first installment of this three-part series on the subject. He lays out what investment managers need to know about artificial intelligence, deep learning, and machine learning.
Portfolio Managers, artificial intelligence is coming to your jobs
Artificial intelligence (AI) is coming to the investment world, reports Larry Cao, CFA. Given AI’s superior computing power and lack of behavioral bias, some in the investment industry and academia believe it will come to dominate the sector. it will?
Artificial intelligence and the future of investment management
In the latest installment of his three-part series exploring the impact of AI on investment management, Larry Cao, CFA, explains why AI and big data won’t 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 affect the industry and benefit investors who harness its power, explains Dan Philps, CFA.
Rise of the Machines: Are Investment Jobs Now Redundant?
Will computers completely replace humans in financial management? Raphael Douady, PhD, Milind Sharma, and Paul McCaffrey explore that question by considering the implications machine learning may have for the investment industry.
That?in Can AI and Big Data do for finance?
Larry Cao, CFA, discusses some of the essential findings of his AI Pioneers in Investment Management Investigation report.
Application of AI and Big Data in investment: four frequently asked questions
He AI Pioneers in Investment Management The report inspired some compelling questions and answers. Larry Cao, CFA, addresses several of the most important ones.
Using Artificial Intelligence to Sell Mutual Funds: Three Phases
How can AI transform the way investment products are distributed? Alon Bochman, CFA, describes a case study demonstrating that when properly harnessed and guided by human judgment, AI can create more efficient and effective processes.
The future of AI and Big Data: three concepts
Andrew W. Lo and Ajay Agrawal focused on three main concepts expected to shape the future of AI and big data in a conversation with Mary Childs at the CFA Institute’s inaugural Alpha Summit. Larry Cao, CFA, distills the main insights from him.
To learn 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.
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All messages 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.
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