Collaboration to apply technology, as discussed earlier, involves human intelligence in training, explaining, and sustaining roles (ensuring the technology works safely and ethically). It involves the machine in amplifying, interacting, and replicating roles (reproducing human skills). The roles are complementary in all cases—their effectiveness is present only when there is some AI+HI combination.
Investment professionals of the future will increasingly differentiate themselves by their ability to work with technology to enhance their quality of work generally and performance levels more specifically. The need and ability to work with technology translate into different requirements for the three functions of investment, technology, and innovation highlighted in Exhibit 11.
The type of skills required for investment teams, which includes the majority of CFA charterholders, will remain predominantly investment skills. Professionals on investment teams who understand the basics of AI, data science, and technology can be expected to be far more effective than someone with similar investment skills but no exposure to such technologies. We must emphasize that we do not think this means that the majority of CFA charterholders will need to become programmers or statisticians. We also doubt that investment professionals in general are committed to such a development. Quite the contrary, we think professionals need to continue to sharpen their investment skills because routine tasks will increasingly be performed by machines. Experience and judgment will become more important in the more complicated tasks that often carry greater impact and higher risk.
THE BIG DATA OPPORTUNITY IN PORTFOLIO MANAGEMENT The big data opportunity in portfolio management is additive in nature. Unstructured data analysis today is the equivalent of going to where people have not been before (uncovering previously hidden information). In addition to annual reports and conference call transcripts, the explosion of data in today’s world has put a vast amount of new information at the disposal of investment professionals. This includes other alternative data including social media, satellite images, customer and cargo traffic information captured with sensors, web scraping, and so on, so that analysts can gain knowledge without physically being present. In other words, information is stored and transmitted in the form of images and written and spoken languages.
AI and big data technologies will enable analysts to have access to a vast amount of public information, much of which was not available to investors before. This is often referred to as going beyond the ‘data tap’ (think of Form 10-K of data being periodically dripped out) to the ‘data lake’ (think of access to always on and always growing publicly and privately accessible data). The challenge now is for the analyst to create value by making sense of this massively expanded data and integrating it into portfolio construction. This speaks to the human roles in relation to data in training, explaining, and sustaining; and roles for the machine in amplifying, interacting, and replicating.
Although our industry leader survey did not rank IT and computer science as top skills needed for investment professionals in the future, this finding is consistent with the consensus among roundtable participants that there will be high demand for professionals with advanced degrees in computer science and statistics—the two prerequisites for AI training—to work alongside the investment teams to engineer AI/big data applications in investment management. Although we are not seeing many finance majors looking to study for computer science degrees, science and engineering majors who want to work in finance are increasingly taking the CFA Program. As we learned from roundtable discussions in Mumbai, an IIT graduate with a CFA charter is often considered the hottest ticket in town—and a top prospect in the global investment industry job market.
TECHNICAL SKILLS
LEADERSHIP SKILLS
SOFT SKILLS
T-SHAPED SKILLS
|
Creativity/innovation skills
|
32% |
|
Ability to connect across disciplines
|
29% |
|
Solutions skills (i.e., understanding client needs and developing appropriate portfolios)
|
29% |
|
Empathy/relationship skills
|
20% |
|
Humility/self-awareness skills
|
20% |
|
Communication skills
|
19% |
|
Systems savvy/understanding larger context
|
19% |
|
Understanding and leveraging diverse perspectives
|
19% |
|
Situational fluency/adaptability
|
17% |
|
Instills an ethical culture
|
15% |
|
Ability to articulate mission and vision
|
13% |
|
Information technology and computer science
|
11% |
|
Crisis management
|
9% |
|
Governance
|
8% |
|
Foundational investment skills (as in the CFA Program)
|
7% |
|
Globally attuned, familiarity with multiple languages
|
5% |
|
Cultivating a valuable network of contacts
|
5% |
|
Science, engineering, math
|
5% |
|
Consultative/selling skills
|
5% |
|
Finance, economics
|
3% |
|
ESG analysis skills
|
2% |
|
Management science
|
2% |
The most important skills on a growth trajectory for innovation professionals are T-shaped skills. Innovation professionals are subject matter experts, but the key to success will be their readiness to adapt to changing environments and their ability to go beyond their own field and work across disciplines. We would argue innovation professionals in investment firms need to be grounded in both investment and technology, so they can communicate effectively with technology and investment professionals, respectively.
In practice, we expect investment teams and technology teams to collaborate closely in shared team space. We believe this is the most effective institutional approach to foster T-shaped skills across teams and for organizations to get the most out of professionals with T-shaped skills.