I read an interesting article in the Wall Street Journal recently titled Prepare for a New Supercycle of Innovation. Just as all the fintech buzz was beginning to feel trite, the piece offered an interesting new perspective on what’s driving the trend of innovation in financial services and whether the hype has any longevity. The author explored a number of market crashes over the last century, from the Great Depression to the recession of the 1970s and found they share a common thread of post-crash hyper-innovation.
The same cannot be said of the crash of 2008. Why is that? The author hypothesizes that the natural order of innovation was stagnated by an unprecedented level of government interference. A collapse that should have washed out the old and brought in the new and was instead propped up by bailouts and cheap money (zero interest rates), extending the old order past its expiration date. We’re just now feeling the shakeout of this misalignment: the introduction of new technology was dammed for nearly ten years and a tidal wave of innovation now looms above us.
With all the hype saturating headlines, it’s difficult to understand whether this wave will touch down in full force or roll back when the media finds the next big thing. My take? We’re well overdue for disruption and with an increasing investment in data, we’ll be ready for it.
With active investment management under attack, it’s clear that competitive differentiation is more important than ever in portfolio management. Asset managers are playing in a crowded space, and uncovering alpha has grown bewilderingly complex. New investment vehicles, fund types, and technologies are helping asset managers gain an edge. As the fintech revolution has pushed through from the middle to the front office, these strategies are being bolstered through the use of structured and unstructured data, machine learning, predictive analytics, and near real-time investment portfolio information. What’s enabling this shift? Data.
An organization limping along on siloed technology and pockets of outsourcing can still keep up with the Joneses if they prioritize and govern their data appropriately. Undertaking a new enterprise data management strategy is not for the faint of heart but the future rewards are well worth the effort now. An oft-cited example of how we can use data to differentiate investment strategies is through the use of cognitive technology like IBM’s Watson. By leveraging “self-learning” algorithms and cognitive technology, predictive analytics can analyze factors, probabilities, and scenarios with speed and precision that continuously improves over time. If implementing this type of technology sounds intimidating, it is probably because your data house is not in order…yet.
With well-governed data, the sky is the limit in terms of possibilities for the use of data. And while some of the biggest players in asset management may grab headlines with their use of futuristic technologies now, trust that they too are working through their own data challenges. If you feel like you’re late to the fintech party, that’s far from the case. Seeing and understanding the possibilities of what you can accomplish with the tidal wave of innovation is the first step. The second step is laying the data foundation.