With more and With more and more non-banking companies offering banking products, data that was previously only accessible to financial institutions is now in the hands of fintechs and other companies launching integrated banking products. This data can provide a wealth of information about customers’ financial health, along with insights into how they spend their money and where.
The only question is what to do with all this?
This is a question banks have wrestled with for decades, but for newcomers – and especially non-traditional financial companies like X, Apple and Walmart that are joining the game – it can be difficult to even know where to start.
As a former chief architect of a large financial institution, former chief technology officer of an innovative bank, and advisor to a fintech investment firm, I’ve seen this question from all sides.
I’ve seen large banking institutions lose valuable revenue opportunities because their legacy systems and poor data architecture prevent them from getting the right data at the right time. I’ve also seen fintech newcomers struggle to fully understand how their customers use their product because they don’t know how to interpret the banking data in front of them.
The companies that really succeed are the ones that do both well. They structure your banking data in a way that allows your team to easily understand how customers use your product. They can then turn this understanding into actionable insights to improve their customer experience and mitigate fraud.
Proper data structure
The more you understand your customer, the better you can make product improvements and refine your marketing and sales strategy.
As a recovering chief banking architect, I still keep in touch with some of my friends who remain in that world. And he used to have a running joke with the chief architect of one of the world’s largest banks, based in the United States and whose name will remain anonymous. Every time I saw this friend, I asked him a simple question: “How many data systems do you have now?” It was a joke because I would never know the answer.
Forget about learning how to use data. If you don’t have a single source of truth for your customer data that is easily readable, you will never be in a position to properly leverage it to scale. Unfortunately, my friend’s dilemma is very common in the banking world, both in traditional institutions and emerging fintechs.
Resolving that dilemma can take years; I should know, because I had to. But getting your data structure right can make a big difference in the long run.
