Surf's Up: Take the Long View on FinTech Disruption
Have you ever watched surfers counting the waves, waiting for the “big one”? Surfers know that waves travel in sets and that the first wave in a set is not the biggest. In fact, the seventh wave is often the tallest and most powerful.
What does this analogy mean for financial services? My view, having advised both financial institutions and FinTech (i.e. financial technology) companies, is that we may currently be at the third or fourth wave of disruption of financial services, but the biggest wave is still out there on the horizon.
Consider marketplace lenders as an example. Zopa and Prosper were the first wave, offering true P2P lending. Lending Club was a second wave using institutions as its primary source of funds. SoFi represents a third wave, drawing upon the securitization markets for liquidity. But the evolution of this sector is far from complete.
What could the big wave of financial disruption look like? Physicist Niels Bohr said: “Prediction is difficult, especially about the future.” With that caveat, here is my short list of four disruptive innovations that have the potential to rock the boat of financial services:
Machine based learning (including AI in the cloud)
Core data processing in the cloud
Each of these four is potentially transformative in scope. Let’s briefly consider the possible impact of each.
Blockchain: Many feel blockchain is poised to displace traditional clearing mechanisms with its distributed ledger approach to transferring digital assets. However, blockchain will likely take time to evolve into practical market solutions. Experts such as R3 agree that key questions, including security, scalability and systems integration have yet to be fully resolved. As these issues are resolved, the question will then be which specific use cases make best use of blockchain’s capabilities and attributes. Mortgage title transfer is just one example of a prime candidate for blockchain disruption.
Machine Based Learning: This may be the biggest game changer of all. The financial services sector possesses more data than any business sector other than communications. However, most banks and credit unions do relatively little to extract value from the mountain of data they hold. This will change rapidly, and machine based learning will play a huge role in that shift. Raab Associates recently identified 23 active categories of machine learning and more than 140 expert systems seeking to break out in this space.
Core Data Processing in the Cloud: Two years ago Marc Andreesen tweeted: “I am dying to fund a disruptive bank.” His tweet sparked a firestorm in technology blogs about what a disruptive bank would look like. The consensus was that it would not utilize a traditional core data processor, but rather would build a new core from the inside out, both customer and mobile centric. Recently we’ve seen a wave of disruptors building cloud-based cores with very flexible API layers to interface with innovative financial apps. Start-ups following this model are emerging in Europe, and the U.K. in particular. I anticipate the incumbents will rapidly converge on core in the cloud via acquisition.
Robotics: Think about how dependent a typical credit union is on automobile lending. Then consider the possible impacts of self-driving cars on this critical lending category. What if self-driving cars significantly reduce the overall demand for new cars? This is very difficult to predict at this stage, but it’s probably wise to not ignore it. Moreover, self-driving cars are just one piece of a robotics field that is evolving at light speed. Just this month Toyota announced a small talking robot called “Kirobo Mini”, designed to ride as a passenger in your car. Kirobo, priced at $400, has the intelligence of a 5-year old, can learn phrases and recognize facial expressions, and can even warn you when you are driving erratically. Or consider how voice recognition in a device such as Amazon’s Alexa or Google’s new Assistant could provide access to all of a member’s financial information via automated voice recognition.
FinTech innovation will accelerate over the next 3-5 years. U.S. venture capital firms are flush with cash, having raised $12 billion in Q1 2016 alone, and they have identified FinTech as a top investment sector. As funding pours into the four areas described above, the magnitude of change within financial services may exceed anything we’ve seen thus far. Also, new sectors of interest will emerge. For example, PwC reports that the most popular new trend in FinTech funding is the “emergence of services and solutions for un(der)served customers.” That sounds remarkably similar to the original mandate of the U.S. credit union system.
WHAT SHOULD A CREDIT UNION DO?:
FinTechs recently have shifted away from competing head-on with banks and credit unions and towards building partner relationships with incumbents. An alert credit union can take advantage of FinTech innovation without having to invest in a FinTech or build new technology itself. We expect excellent partnering opportunities to emerge across all four of the key trends identified above. A critical requirement for success as we move through this transformation will be to take a long-term view. Remember, the next wave may not the “big one”.