Big data in banking: The barriers to better customer understanding part 1/2
Today's banks are sitting on a goldmine of exclusive customer data, but there are challenges to overcome before this can be put to use.
Perhaps more so than any other industry, today's banks are sitting on a goldmine of customer data. Think of a person's transactional history, their income, their financial commitments: it's possible to find out a lot about someone from this type of information, and this improved customer understanding could in turn help a bank to deliver a more relevant service.
And yet when it comes to big data, banks in the Nordic countries have major opportunities to be harvested. Their sales and marketing efforts often hinge on less sophisticated types of audience segmentation, with campaigns based on broader demographic data like age, family and education - they aren't always acting on insights drawn from that goldmine of user-specific information, despite their potential to improve hit rates and cut costs.
Here at Tieto, we're currently running a collaborative project called Mobile Financial Services, or MoFS, which is our contribution to the Finnish government-funded research programme Digital Services. A recent part of this was the ThinkBank initiative - a study of the uses of customer understanding in the banking industry today and the potential to expand on this in the future. In carrying out this research, we were able to determine exactly why banks are falling behind in the big data stakes, as well as some of the ways they might overcome their particular challenges.
Why aren't banks using their proprietary data?
There are a number of reasons that Nordic banks have yet to use their proprietary data as a primary source of customer understanding. One of them is that it requires technological transformation: many organisations are stuck with legacy systems that were never designed to be integrated or to generate real-time insights. This is actually a bigger problem in the Nordic countries than in some other places, because our banks were among the first to adopt modern technology. Their systems, in turn, are some of the oldest on the market.
Admittedly, this transformation isn't something that banks alone have to tackle. Their situation is unique, though - their data is very sensitive, so in the past they've put a lot of effort into making it hard to reach. The traditional mindset, in part informed by regulatory obligations, says that banks' data should be stored in a secure vault and never accessed unless it's specifically required to deliver a service to the customer.
As such, the skill base of the average bank isn't weighted towards data management - staff own roles related to products and regulatory compliance, but rarely is information itself the core focus of a specialist. Only recently have banks started to shift their recruitment focus towards data and algorithm experts, and these proficiencies are not yet common in the workforce.
Perhaps the bigger challenge that banks need to overcome, however, is regulation itself. Generally, using a single person's information as the basis of a sales or marketing campaign is forbidden - banks can collect anonymous data to target specific audience segments, but unless a customer states otherwise, they can't use transactional data to deliver a targeted service.
In the next part of this blog post I will focus on solutions, benefits and case-examples from the banking sector.
Customer Experience Management for Financial Services
Download our study which investigates CEM within the Finance Industry in the Nordic region, with emphasis on the generic CEM maturity and development actions on digital CEM. 98 Finnish, Swedish and Norwegian decision makers within Finance were interviewed in this quantitative study.