A great article appeared in Diginomica this week about Nordea combining Waterline Data’s information cataloging with data wrangling to drive the Swedish bank’s machine-led decision making.
Nordea, the largest financial group in Northern Europe with over 10M personal customers and a half million corporate customers, had a few big compliance-related headaches now common among banks. Namely: more personal data than they could manage, a bunch of disparate IT systems (the result of several mergers and acquisitions over the years), and locations in 16 countries, each with their own set of government regulations.
Executives began to fear they wouldn’t be able to meet GDPR’s May 2018 deadline in time to avoid massive financial penalties. They needed to implement a better analytic system.
So, as Diginomica’s Maxwell Cooter writes, they implemented Cloudera for improved data gathering. But to actually be able to use the data, they deployed Trifacta for data preparation and Waterline for data cataloging. With Waterline, Nordea could automatically tag data as it came in. Plus, thanks in part to Waterline’s use of machine learning algorithms to automatically tag and match data fingerprints to glossary terms, Nordea can make the move from human interaction to machine-led decision making for faster, deeper insight into their customer data.
We’re very proud of our role in the project. Read more about it yourself here!