David Snitkof, Head of Analytics & Data Strategy, Kabbage
Small and intimate vs. large and impersonal. Is it really that simple? In the past decade, this contrast has begun to break down and, in some industries, has been upended completely. In financial services, this transformation is only just beginning to take place. Today’s FinTech companies have an opportunity to radically personalize the experience of financial services for consumers and businesses. Accomplishing this transformation will require combining a unique and somewhat tricky set of ingredients.
For most of human history, the concept of scaling wasn't compatible with humanity. Emerging from our roots as hunter-gatherers, there came the rise of villages and towns, each of which needed a butcher, a cobbler and a builder, and life was fundamentally local. Next came the industrial revolution and the rise of global mega-corporations driving rapid economic growth. Highly standardized processes allowed for vast efficiency and scale, but at the cost of becoming increasingly impersonal. In only the past five to 10 years, we have been entering a new phase which allows us to be highly personal, but at a global scale—thanks to technology.
In the 3rd “industrial/global” period, the dominant cultural impression of certain technologies was around standardization and mechanization. At its most extreme, the pop-culture imagination of that period was rife with dystopian visions of a bleak future, where humans would become more like machines than the other way around. This of course was an artifact of an earlier level of technological development, when the only way to achieve scale was to eliminate the variation that lends humanity its rich uniqueness. Thankfully, that future has not come to pass. Rather, an incredible increase in computing power has allowed us to reject the tempting efficiency of homogeneity. Technology allows today’s human to communicate and interact with more people than ever before, to express one’s individuality for the world to see, and to acquire knowledge from all corners of the earth.
Who knows you better, your local supermarket or Amazon? Your local radio station or Spotify? Your favorite local clothing store or Rent the Runway or Stitch Fix? Suddenly, scale and personalization are not in opposition. Moreover, the availability of vast data and computing power unlocks tremendous opportunity for personalization.
This phenomenon has lagged, however, in financial services. If you open your favorite mobile banking app, you will most likely see a re-implementation of core branch banking experiences on your phone. Of course, this is a welcome innovation. The ability to monitor activity, transfer funds, open new accounts, deposit checks, take a loan, etc. without having to be physically present is fantastic, but it does not fully harness the personalization potential that exists when every one of your customers has a globally-connected pocket supercomputer.
Today’s FinTech companies have an opportunity to radically personalize the experience of financial services for consumers and businesses. Accomplishing this transformation will require combining a unique and somewhat tricky set of ingredients.
So why hasn’t the world’s greatest enabler of scale and volume – the internet – driven personalized experiences to customers in financial services the way it has in other markets? There are a number of enabling factors that are critical to this transformation.
Unique and Proprietary Data
In order to offer a unique and personalized experience, companies need to have some source of data that sets them apart. Too often, firms make the erroneous assumption that simply hiring a team of data scientists or implementing a leading-edge technical solution will yield the novel insights they seek. Any company looking to personalize its offering must first consider if they have data that provides insight into their customers and the environment in which they live and work, if those datasets are rich and not widely available, and if customers and partners explicitly consent to the sharing of this data. In the world of machine learning, it is generally the case that if given the choice between more data and more sophisticated models, it is the data that will have greater impact. Ideally, if you are looking to build a powerful personalization system, you have access to large quantities of unique data, and its accumulation yields an improved experience for all your customers.
Personalization at massive scale is only possible with the diligent application of technology. The mere existence and possession of data is not the same as having that data in the right structure to enable its most valuable use. Too often, companies that excel at data consumption end up with data indigestion, as information gets fragmented throughout the enterprise, and it becomes harder to construct a unified view of all data pertaining to any particular customer. While some of this entropy is unavoidable in organizations of rapid scale, there are ways to mitigate the complexity. Investing in data engineers who focus on data pipelines, data integrity, and data structure is of utmost importance and will multiply the productivity realized by a data science or modeling team. At the same time, building the learning systems – in terms of both process and technology – to rapidly iterate and deploy new innovations is crucial.
Brand Point of View
In building experiences that appreciate the uniqueness of each of its customers, a company must not forget to do so in its own unique voice. Few companies do particularly well on this dimension, and there is some risk that all computational personalization will sound alike, even if the message itself is tailored. While creating personalized experiences at scale with a unique editorial voice is a significant challenge, brands that are able to do this are likely to enjoy greater success.
The historical opposition of scale and personalization is deeply embedded in human psychology, and overcoming this legacy requires a clear and compelling use case. Offering customers real value from personalization will offset the inherent privacy concerns and provide a lasting incentive to continue making available the data that enables personalization. Moreover, as the core technologies for delivering bespoke experiences become commoditized, the differentiating factor will be the ability to pair technical capability with compelling customer value.
Many of the financial product structures being offered by today’s banks and non-bank financial technology firms are relatively well-established – checking accounts, loans, credit cards, investments – even if the packaging has changed. The most interesting developments are at the intersection of technology, information, and humanity. For financial services, personalization at scale offers incredible opportunity, and the most exciting developments are yet to come.