Banks Are Failing To Capitalize On The Data Revolution

Is the data driven future simply passing them by?


Banks have access to an amount of consumer data that organizations in other industries would kill for. New digital platforms have meant an explosion in the amount of data available about people’s financial habits. The management of transactions and the nurturing of relationships over time have provided insights into customer behavior that has enabled them to maintain a competitive edge. Some banks have been mining, analyzing, and leveraging data for decades now. These banks are, however, in the minority, and most are nowhere near as mature as they should be in their data analytics capabilities.

This failure to keep up is having a hugely detrimental impact on their ability to operate successfully. According to a new survey by business and IT services provider NTT Data Inc, one in three consumers would consider leaving their bank for a better online and mobile experience, while 71% of consumers think their bank could better support their banking needs. The root cause of this is the neglect to analyze the data being generated, particularly that generated by new kinds of consumer-facing products, like apps.

What’s really surprising is that banks are still not prioritizing data analysis. Only the largest regional and national banks (over $10billion) rank improving data and analytics capabilities in their top three priorities (47%), and just 36% of organizations plan to increase their data analytics budgets by more than 10% in 2016. The data is there, the analytical models are there, and the talent to make the data meaningful is there, so excuses for not leveraging consumer insight is really difficult to justify. There are, however, a number of challenges unique to the banking sector that put them at a disadvantage.

Legacy systems and siloed data is the primary issue holding banks back. The influx of regulation and the cost of compliance has meant that, while many banks have invested heavily in front-end improvements, they are some way behind in improving the back end. The banking industry has far more problems with legacy data compared to other industries because of the complexities of their operations, and overcoming this has proved a laborious process for many.

One of the shining lights is JPMorgan, for example, which is investing heavily. JPMorgan CEO Jamie Dimon wrote recently that, 'To best utilize our data assets and spur innovation, we have built our own extraordinary in-house big data capabilities – we think as good as any in Silicon Valley – populated with more than 200 analysts and data scientists, which we call Intelligent Solutions.’ He may be right, but, in general, banking is still struggling to steal the best technical graduates away from Silicon Valley. Put frankly, banking is not always viewed as the most exciting career opportunity for graduates, particularly compared to the young, vibrant tech sector. Banks are trying to change this and adapt the culture to be more attractive. HSBC, for example, now has a separate office for tech staff that better suits the Silicon Valley mindset. There is still a stigma though, and they will struggle to overcome this.

The positive news is that money being spent on regulatory compliance is decreasing, which means funds are now available for data analytics initiatives. Banks are, however, going to have to start putting a greater emphasis on getting it right. FinTech firms are knocking at their door, and will exploit any gap they can find. 

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