At a Future of Fintech conference in New York this summer, Anand Sanwal, CEO of CB Insights said that the idea of a “Bank of Amazon” was top of the list of 10 trends to watch in financial services over the next year.And in the last week, there has been a flurry of articles suggesting that the traditional banking sector is extremely concerned that the likes of Amazon Pay, Apple Pay, Facebook’s soon to be launched WhatsApp payment service and Google Wallet are moving in on the more profitable parts of banking, such as payment processing.
And its no wonder that the tech giants are keeping Britain’s senior bankers awake at night. Because what the tech giants have in glorious abundance is data. Lots and lots of valuable data on the day to day spending habits of millions of customers worldwide. Go onto your Amazon home page and you quickly see just how much the company knows about you. By developing its payment services business, Amazon is not only making transactions easier for its customers but is simultaneously adding to its vast bank of data on their spending preferences and patterns.
A Powerhouse of Data
Amazon, sitting on a powerhouse of data, knows exactly when it can successfully suggest I order more printer ink, sports socks and Kindle downloads. But now, with open banking coming into play in January 2018, it is also perfectly poised to use that data to develop and deliver the kind of financial products that meet or anticipate their customers needs.
But that doesn’t mean that traditional banks have to roll over.
They do, however, need to find their way back to knowing their customers better. The all-knowing bank manager model has been swept away but in its place banks, just like the tech giants, can use technology to get to know their customers better, build relationships and deliver the products they need.
Understand Your Customers’ Spending Habits
At Castlight, we have developed a tool to give lenders an unprecedented understanding of their customers’ spending habits.
Our “categorisation as a service” or CaaS product takes customers’ transactional data and processes it through the CaaS neural net. This neural net has been “trained”, by processing more than 80 million transactional records and currently sorts this data into 155 categories of discretionary and non-discretionary income and spending. For example, CaaS’s neural net can instantly identify and categorise salary, benefit payments, rental repayments, child care costs, the weekly grocery shop or how much is spent traveling to work.
Banks Still Have an Advantage
Traditional banks have a huge advantage over tech giants like Amazon. They’re not restricted to sourcing data from what an Amazon shopping history reveals. They can use CaaS to categorise every single transaction their customers make, process the data and identify exactly what they need to do to retain and support their customers. We aren’t walking into David and Goliath territory here – banks can be giants in this brave new world too.