Augmented Intelligence in the Finance Industry: AI, Big Data and Robo-Advice
Last month, the Financial Times reported that the CFA Institute is updating its Certified Financial Analyst (CFA) exam so that starting in 2019, it will include questions about artificial intelligence (AI), big data and robo-advice, reflecting the growing impact of machine learning on the finance industry. Steve Horan, managing director of credentialing at the CFA Institute, wrote in an email to Training Industry that “some data analysis methods associated with large, unstructured data sets is migrating from specialist knowledge to generalist knowledge,” necessitating some of these changes.
The CFA Institute’s 2017 “Future State of the Investment Profession” report describes an industry that sounds like a scene from a science fiction novel: “The new work model is essentially cyborg in nature (person plus machine), with human skills being critical in soft skill areas” like “situational fluency, social intelligence, innovation, creativity, and social media savvy.”
Huy Nguyen Trieu, co-founder of the Centre for Finance, Technology and Entrepreneurship (CFTE), distinguishes between automation and artificial intelligence. Software that can download and store annual reports is automation, but software that can find anomalies in reports and compare them with other companies is “closer to AI.” Trieu has worked in both tech and finance for 20 years and says that “the increase in tech capabilities is unlike anything we’ve seen before – and that has happened in the last [four or five] years.”
In fact, a new sub-industry has developed around this phenomenon. Financial technology, or fintech, is, according to FinTech School, “one of the fastest growing sectors of technology powered innovation,” with more than $50 billion in global investments since 2010. Trieu says that a financial professional’s goal shouldn’t be to keep their job; rather, it should be “evolving [their] job into tomorrow’s job.”
Lifelong learning is no longer optional, and having a CFA is no longer enough; it’s now “the foundation skills on which [professionals] need to build to adapt to new opportunities.” New fintech education programs include online training, bootcamps, and custom enterprise training programs and certificates. Training professionals at financial organizations must encourage ongoing internal or external learning in order for CFAs and other financial professionals to successfully leverage new technologies. “Learning to learn,” Trieu says, “will be the next big skill that’s in demand.”
Big data, or large, complex data sets, are playing a larger role in finance, as they are in other industries. Analysts alone can no longer work with the large amounts of financial data organizations can collect, thanks to technology, and machine learning is now required. In May, the Wall Street Journal published a series of articles on the impact of technology on the finance industry – specifically the popularity of quantitative traders, who use “algorithmic-driven trading” and who control about one-third of the trading taking place on the U.S. stock market today. Tried-and-true investment strategies are losing favor; investment firms are hiring more mathematicians and statisticians, and some “are pushing into machine learning.”
How are professionals in the finance industry adjusting to these changes? The Wall Street Journal reports that many financial analysts are taking data science classes to learn the basics and that Matthew Granade, chief market intelligence officer at Point72, recently recommended to students at the London School of Economics that they learn programming languages to improve their competitiveness after graduation.
Robo-advisers, which the “Future State of the Investment Profession” report defined as “basically a class of financial advisor/intermediary that provides portfolio management with minimal human intervention,” are automating tasks that once required financial professionals. The Wall Street Journal predicts that soon, artificial intelligence may be answering simple client questions, recommend communications by advisers and use predictive analytics “to tackle complicated tasks such as setting personalized goals.” While these tools will take over some tasks, financial analysts will need to know how to work with those tools successfully.
A recent CFA Institute survey of 1,145 investment leaders ranked “knowledge of science, engineering, and mathematics” and “sophisticated knowledge of IT” as two of the top 10 skills needed for chief investment officers, portfolio managers, CEOs of asset managers and CEOs of asset owners, noting that the latter skill is also one of the hardest to find.
The Bottom Line: What Training Professionals Need to Know
However, “leaders of investment organizations need to become more human, not less, in order to compete,” and over 60 percent of respondents said that “ethical decision making” was a training priority. Many clients still value relationships with people, and soft skills will continue to be vital. “The future of the branch,” according to Citi’s 2016 report, “is about advisory and consultation rather than transaction,” and as automation takes over transactional roles, advisory skills will be more important.
As the PwC Financial Services Institute wrote in a report on artificial intelligence, “augmented intelligence, in which machines assist humans, could be the near-term answer.” In CFTE’s first blog post after launching last month, Trieu wrote, “artificial intelligence and automation are rapidly transforming finance … For finance professionals, this could be seen as a threat to their jobs, but we think that there are great opportunities for those who acquire the right skills.” It’s up to training organizations to help make sure those skills are developed effectively.
Taryn Oesch, CPTM, is an editor at Training Industry, Inc.