Client Data: Powerful But Largely Untapped Asset

“Personal data can tell you so much more beyond just providing insights into individual client behaviors. You can take these streams of data, clean them up and extract valuable insights that look across the book of business to highlight trends and challenges that are not really visible on a case-by-case basis.”

The second day of the 2018 DataDisrupt conference included a timely panel discussion focused on the “New Era of Product Development with Personal Financial Data.”

Speakers included Craig Snodgrass, chief data officer of Cardlytics; Poulomi Damany, vice president of data products for Credit Karma; and Kevin Novak, chief data officer for Tala. While none of their firms are active in the retirement plan advisory space per se, they all agreed that their experiences integrating and leveraging personal client data should be valuable to pretty much any financial services business looking to boost its growth and client service capabilities in the years ahead.

“Personal data can tell you so much more than just providing insights into individual clients,” Snodgrass noted. “You can take these streams of data, clean them up and extract valuable insights that look across the book of business to highlight trends and challenges that are not really visible on a case-by-case basis.”

Novak agreed with that assessment and urged financial services firms to “think more about all the emerging ways they could build out and then leverage a composite view of their client data streams.”

“For example, at Tala, my team is constantly engaged in the work of searching out places where our assumptions are not in line with client behaviors,” Novak said. “One broad theme I would echo for the audience is that siloed data will never be as powerful as integrated data. That is just obvious, but it hasn’t been accepted as a reality quite yet. Centralization and coordination of your client data is crucial.”

Snodgrass shared another important point about client data that is particularly relevant for the retirement planning audience, warning that “aspirational and intent-driven data is not the same as data derived from real decisions.” Another way to put this, he said, “is that stated behavior is not always the same as demonstrated behavior, so it is important to understand how data was generated and what exactly it is telling you.”

Asked by the panel moderator whether it is better to “create data or wait for data,” the experts agreed that both approaches have merit.

“At Credit Karma, we are trying hard to listen to our customers and what they are telling us organically, but we are also mindful to be proactive and to think ahead about new ways to collect data form our clients and to leverage the data we already have,” Damany explained. “Each piece of client data deepens our understanding of our members and broadens our view to not only what they want but also what financial products they can get. For example, having data about all your car details including recall info, DMV record and the outstanding loan and insurance allows us to recommend a savings opportunity on the loan with greater certainty, and in the context of an auto assistant experience centered around your vehicle.”

Within financial services in particular, the experts agreed there is a lingering problem with “culture, funding and regulation,” when it comes to full utilization of client data.  

“These hurdles are tough to overcome, but it all starts with understanding the opportunity that exists and them from there finding ways to clean up and control the data,” Novak suggested. “Data stewardship is going to remain a challenge, even more so as the new data economy comes to the fore.”

The experts concluded that financial services firms (and businesses in many other industries) must improve their focus on “people, process and technology.”

“As we push for the democratization of data, we must allow our most analytical minds to be the analysts, and we must be sure to talk about big data in a way that does not scare off our clients and customers,” Snodgrass concluded. “Behavioral science and data analytics are coming together in new and powerful ways. It must be made clear to consumers that this is a good thing. We can’t allow concerns about fringe cases reported about in the media to scare people away from sharing data and embracing new data capabilities.”