How to Get and Stay Ahead in the Robo Race
In the face of disruption, there are steps that financial professionals can take to stay at the top of their game.
Does it mean the financial services industry must embrace fintech as an inevitable and important component of the industry’s future? It most certainly does.
Clearly, the innovators need not be concerned. Visionaries, data scientists, entrepreneurs, computer programmers, and those specializing in analytics will flourish. With new frontiers come new opportunities.
Advice, financial products, and client solutions are more than data and computing power, however. The talent of the future will need to harness artificial intelligence to supplement human intelligence — not replace it.
Robo platforms are projected to exceed $1 trillion in assets under management in the next few years –- with one estimate at $4 trillion by 2022. And robo advisers are striving to deliver goals-based advice tied to asset allocation decisions.
This has typically been the purview of advisers, both retail and institutional. It is also a vision of the future that fits perfectly with what we, at the CFA Institute, believe in an investment industry that is geared towards providing solutions to clients rather than one that sells products to customers.
Robo Benefits
I have met with many firms behind robo advisers over the last few years, and many are using computer power to better help underserved groups — female investors, for instance.
These are incredibly positive developments as they are increasing our industry’s market penetration, furthering investor education, and deepening the range of financial tools available for the average client.
These platforms provide tools that can assist people who might lack access to human advice. Many young investors and small account holders are not “profitable” enough to warrant personal advice in face-to-face interactions. Indeed, some larger wealth managers have pushed such accounts to call centers and technology platforms.
Financial services firms remain under cost pressures. The challenge for them is to use fewer people to achieve more by changing the roles played by people and technology.
Tough decisions therefore lie ahead. Where can investment management professionals make the most impact? Should firms “write off” certain accounts and let them migrate to new fintech homes?
How will wealth and asset management firms combine both people and technology in their business models? Will certain client segments prefer human interaction and will this preference change with the generations?
While the rise of fintech may look like a shiny new thing, computer models and asset allocation tools have existed for decades: plug variables into a model and an asset allocation plan emerges -– be it for small investors or multi-billion dollar portfolios.
Monte Carlo simulations, powerful computer models used to predict price movements and thus enhance investment decisions, arose out of the Manhattan Project and were later applied to finance in the 1960s.
What’s different is that while the models of the past were tools for Ph.Ds and MBAs, today’s fintech brings computer modeling to the fore in a dramatically simplified fashion for the end user.
Industry Challenges
The rise of the machines poses many questions for those in the investment management industry: Where and how can humans flourish in this new paradigm? Will human advice become a thing of the past? What are the skill sets professionals will need going forward, not just to survive but to thrive?
For many clients — both retail and institutional — the combination of technology and advice holds the key to the most productive and trusting relationships.
The CFA Institute recently conducted a global survey entitled “The Next Generation of Trust.” In it, we found that increased trust cannot be achieved solely via more sophisticated technological offerings. Yet the survey showed that technology can be an important component for raising trust.
Many investors said they rely on humans for advice but see technology as a complementary tool. The smart use of technology, therefore, increases trust when combined with a human touch.
For those in the business of delivering advice, the so-called “soft skills” — listening, empathy, understanding — further help build trust and take on increased importance in a fintech-driven world.
Artificial intelligence and machine learning do not yet have the capacity to apply those skills. And they cannot explain their decisions, either.
What AI and machine learning can do — and do well — is to remove emotional and behavioral biases from the equation; they provide consistency of advice across clients and across strategy. Eliminating the impact of emotions and biases leads to better investment decisions.
The skills of the future are likely to migrate from working on projections and models on an Excel spreadsheet. Humans will need to be able to interpret the numbers, not just calculate. Insights culled from data, rather than Excel skills, will rule the day.
The industry is already awash in a tsunami of data, and the water is still coming in. Humans need to make sense of it all.
Education for Humans
At the CFA Institute, our curriculum now includes a survey of the fintech landscape — including the basics of artificial intelligence, machine learning, robo-adviser platforms, blockchain and cryptocurrencies — and applications of big-data analytical techniques to unstructured data sets, and, perhaps most importantly, fintech and cryptocurrency case studies.
Our fintech curriculum content is also in high demand from existing CFA charterholders so that they can continue to develop to be the best professionals they can be.
The status quo will not hold. It’s a losing game to fight looming disruption. Just look to the taxi industry in major cities around the world where Uber and Lyft have moved in.
Financial firms must continue to evolve and adapt. Human judgment, coupled with all the data-crunching, inputs, and analysis that fintech can provide, will be the way forward.
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Paul Smith, CFA, is President and CEO of the CFA Institute.