BNY Mellon is taking on a major IT project that's reimagining everything about how the $1.4 trillion-asset bank stores, crunches, uses and delivers data - perhaps the second most important four-letter word in banking after cash.
The bank's IT executives have realized that strong data management and analytics are no longer a nice-to-have, but a must-have.
"If you log into Amazon, there's the ability [at Amazon] to understand who you are and what you have done in the past," says CIO Suresh Kumar.
Kumar is speaking glowingly about Amazon's ability to drive experience based on what it has learned about users - something the bank hopes to accomplish. In a new global tech initiative, BNY Mellon will leverage elements of what's called "big data" - or what Kumar says is the greater use of larger volumes of nontraditional unstructured data and search analytics. But more than that, the bank will challenge its employees to see their own business and relationship with the larger bank differently, in a more collaborative manner in which information gathered for a single purpose can be crunched to help decisions enterprise wide. When a customer accesses the bank through any channel, all of the information about the interactions the bank has had with that client can be made available. That will drive what the user - either a client or a employee -hears and sees next from the bank.
"It's really a different mind set. It's not that we didn't keep the data to accomplish this before. For example, for regulatory purposes we had to keep certain transaction and customer information that could help serve clients in other ways. But for the most part, we would only use the data if a regulator asked for that information. But why can't we use that for other purposes?" Kumar says. For example, the bank hopes to repurpose trade data to efficiently search cost basis information - or the original value of an asset for tax purposes adjusted for splits, dividends and return of capital distributions - which is used to determine the capital gain. By obtaining this information, the bank plans to determine and provide intelligence about what a client is likely to look for in an effort to expand customer service for the person that's executing the trades. "There's a lot of insight you can get from looking at a history of trades...It's not necessarily that we need more data, it is a matter of gaining insight into the data we have," Kumar says.
BNY Mellon is embarking on its project at a time when almost all banks are sorely behind when it comes to collecting and crunching customer and market information to be an informed partner with its customers and staff. Entire retail industries are moving ahead of banking when it comes to reaching customers where, when and how they want to be reached - with the right message at the right time on the right device - with suggestions that actually resonate with consumers. It's a holy grail that still eludes almost all traditional financial institutions, and it's why you hear so much about PayPal, Square, Movenbank, Google and even Walmart doing the innovative work in user experience that banks should be doing.
"The customers and employees have great tech at home...Twitter, Facebook, Google, and they expect the same from us," Kumar says. "That experience is what we have to compete with for our portal. Our challenge is, 'What can we do to improve user experience for clients when they log in? What can we learn about them to give them what they need at the right time?'"
Big data is still a vague concept that generally starts with an exceptionally large data store, sometimes supplemented by added data sources, such as social networking sites, mobile commerce and web-enabled financial management tools that aggregate financial and payment information.
The bank's goal is to make BNY Mellon's web analysis work "more like Google" in the sense that when people log into the bank's site from a PC or mobile device, or a more traditional channel, the bank is ready with a full picture that leverages all of this new data to anticipate a service query or a need. For example, Google's analytics program provides marketers with information on a consumer's web visits, the visits' geographic origin, time of day, amount of time spent on site and what parts of a site that consumer visited.