“Being too far ahead of your time is indistinguishable from being wrong.” — Howard Marks, CFA, The Most Important Thing Illuminated
In investment management, early is rarely a safe play. In a runaway bull market, going against the grain is lonely and unprofitable. However, getting in early on the artificial intelligence (AI) wave might buck this trend.
AI’s role in security selection and portfolio construction is well documented. Perhaps a better, albeit less sexy, use of AI is cultivating stronger corporate governance and leaders with a culture of better decisions and lifelong learning.
In a real sense, this very moment may have the slowest pace of change we will experience for the rest of our lives. Just as there’s never been this degree of change, there has never been this degree of opportunity. AI is quickly creating new approaches to business models, operations, and the deployment of people. If we no longer have the luxury of watching markets unfold before taking action — to generate new value and wealth management solutions — AI might just be the change agent we didn’t ask for but got anyway.
Sea of Change
Often it’s only after pausing and stepping back that we truly appreciate the current pace of financial, business, and economic change. Since 1955, 88% of the companies that composed the Fortune 500 have vanished. Over half have merged, been acquired, or gone belly up since 2000. Another 50% are forecasted to fall off the list within a decade.
Clearly, fintech is accelerating. When additional macro factors are added, the lines between traditional asset classes get ever blurrier, creating links and contagion across previously unrelated assets and business models — suggesting that managing systematic risk with asset allocation may no longer be enough.
Oddly, despite the torrent of change all around it, to date, the asset management industry has largely remained resistant to change. This may not be the case for much longer, as headwinds from unfavorable secular trends — moderation in long-term expected rates of return and aging demographics — are rapidly shifting competitive dynamics.
New research from McKinsey & Company’s financial services group shows that counter to conventional wisdom, the greatest predictor of success is not size and scale but focused execution to capture share in the most important pools of value in the industry. Financial institutions of all sizes are doing this by shifting from being faster to being smarter.
Artificial Intelligence: Asset Management’s New Strategic and Governance Imperative
If modern challenges require modern solutions, today’s finance professionals are wise to augment their decision-making capabilities with AI. The reality is business and investment strategy has become too complex and is moving too rapidly for asset managers to make good decisions without rethinking the very art and science of portfolio management.
While ceding greater control to machines won’t be easy, financial executives recognize the potential: Research reveals seven in 10 believe AI will bring a complete or substantial change in their own jobs over the next 15 years.
For the foreseeable future, humans will remain our primary decision makers. But there is room for improvement: “PWC’s 2016 Data and Analytics Survey 2016” finds asset management has an overreliance on human judgment in decision making. If enhanced strategic and operational decision capabilities are to become a deeper part of competitive advantage, the practice of corporate governance and strategy development is going to require some uncomfortable changes. This might include investment organizations finally making innovation a central process, rather than another virtue of marketing fluff.
As electricity was to the first industrial revolution, information flow and intelligent organizational structures will be the stuff of top-line growth in the information age. Whether robots automate our jobs or augment our skills, we need to focus less on machines doing what was once human and more on cultivating the capacity for workers to learn faster.
Almost without being noticed, corporate governance has morphed into a mixture of compliance and risk avoidance. This is interesting and troublesome at the same time, as the word “governance” actually comes from the Greek verb κυβερνάω [kubernáo], meaning to steer. Instead of worrying about automating leadership and governance, by augmenting decisions with AI, we can build a culture of learning and return corporate governance to its roots: a system of rules, practices, and processes by which a company or strategy is directed and controlled.
Kevin Kelly, founding executive editor of Wired magazine, best sums up AI’s role in the next Industrial Revolution: “The business plans of the next 10,000 start-ups are easy to forecast: Take X and add AI . . . everything that formerly electrified . . . will now cognitize.”
Designing a Culture of Sustainable Investment Performance
We know investment managers who establish clear and aligned values and processes consistently outperform those who do not. While a good strategy can deliver alpha, what often gets lost is how people and culture have a profound impact on shaping investment performance and the sustainability of an investment organization.
But what is culture? Despite our best efforts, the investment industry continues to struggle with the language of culture or the mechanics of managing something that is clearly everywhere but nowhere to be seen. It hasn’t gotten any easier with investment organizations growing in scale and complexity.
Although there are many definitions of culture, one thing remains undeniable: Without deliberate management, in cultures lacking the capacity to assimilate outside opinion, the primary check on behavior is authority. See Bernie Madoff, AIG, or Jerome Kerviel of Société Générale if you still don’t buy how culture shapes sustainable performance. Andrew W. Lo’s “Gordon Gekko Effect” is a fabulous and detailed account of the role of culture in financial markets.
Another element of culture is the willingness to innovate. By nature, financial services are conservative. As entities have grown in size and complexity, specialization, silos, and ultimately hierarchy have choked off the capacity to readily adapt and innovate.
The typical innovator’s dilemma story does not apply to investment management. While entrepreneurship, fail-fast, and digital transformation make the stuff of good investments, they need not apply to the management of assets. The real challenge is not computational, but one of imagination. With investment processes and strategies growing ever more indistinguishable, AI can help unlock machine-aided growth while balancing human desires with what’s technically feasible and financially viable.
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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.
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