DNB Bank Advances on 3-Year Big Data, Data Science Initiative

DNB Bank, Norway’s largest financial services group, is closing in on the final stage of its three-year big data and data science initiative. The strategy, which included the launch of its Big Data repository deployed on Amazon Web Service’s cloud last year, has since allowed the firm to leverage other new technologies such as AI, machine learning, natural language processing (NLP), and augmented robotic process automation (RPA) to drive better business practices, data governance, and customer insights.

Jumping straight into an advanced analytics, cloud-based platform for data scientists has landed the bank on the bleeding edge, says Aidan Millar, DNB’s chief data and analytics officer and EVP of group digital insights. Since beginning, the firm has created more than 50 data stewards and 50 data scientist roles—all positions were filled by upskilling and re-skilling existing staff—though Millar thinks those numbers have the potential to double.

“This had to be business-led,” Millar says. “Just getting the business to understand the value of data has been probably one of the biggest drivers, and then trickling that down through the layers…starting with the business architecture, to an information architecture, to an application architecture, to a data architecture, to an infrastructure architecture.”

In the last year, DNB has focused on using AI for algorithmic development, and using machine learning in tandem with RPA. Through a partnership with the Norwegian University of Science and Technology’s Ph.D. program, the bank has developed its NLP capabilities. One model the groups have developed interprets documents as a human would, understands what department to send them to for processing, and then automates that process.

Sometimes I can look back after six months, and [I think] ‘My goodness. All that stuff that we did six months ago has progressed so fast technologically.’ There are new solutions out there that supersede what we’ve done—it’s crazy.

Aidan Millar

Another focus area has been customer retention. When Millar first joined DNB at the end of 2017, he traveled to Trondheim, Norway, to visit the bank’s customer recovery center, which has about a headcount of 30 or so. What was crazy, Millar says, was that the job of those 30 people was to phone customers who had closed accounts and convince them to come back.

“I was like, ‘This doesn’t sound like a very efficient way to do this,’” he recalls. “It’s kind of like marrying someone you divorced, and it’s really not going to be a good outcome, I don’t think. So what we did was we built a predictive analytics model, which is now in place, that predicts with very good accuracy whether a customer will leave within the next 90 days. And then they phone them up preemptively and actually see if there’s anything they can do to support them better. And what we found is not only did we retain the customer, but we cross-solved for more products.”

Another area in which they struck value was gaining insights into what the bank’s competitors were doing well for their shared customers. The bank created an analytical review—which, Millar stressed, had to be done ethically and compliant with GDPR—of DNB customers that had, for example, credit cards, mortgages, or insurance premiums with other banks, to figure out how they could better meet those customers’ needs.

The first year of the project was “protect the bank,” says Millar, and it focused on compliance, organization, and data governance. The second year, which is wrapping up, has been a sort of stabilizing period—“Making things stick in an organization is actually the hardest part of change management”—in which he focused on pushing the new processes and frameworks throughout other areas of the business. The upcoming third year will be the fun part, Millar says, calling it a period to “grow the bank.” He and his team will use those established practices, underpinned by strong data governance, to drive further advanced analytics, find new customers, and maintain their rate of innovation.

“Sometimes I can look back after six months, and [I think] ‘My goodness. All that stuff that we did six months ago has progressed so fast technologically.’ There are new solutions out there that supersede what we’ve done—it’s crazy.”