Data is created at every financial transaction, and as datasets expand beyond what a single database can hold, big data is born. As complex as these datasets can be, they hold valuable information for financial institutions and are spurring financial services investments.
A report from the technical consulting firm SNS Telecom & IT, published July 1, forecasts that the financial services industry will invest $9 billion in big data services this year.
This investment represents the industry as a whole, but as a subset, business and personal banking will make up the largest share of this investment at 29%. There are numerous uses cases in this sector for big and/or alternative data. Be it mobile financial transaction data to underwrite loans and access creditworthiness or to calculate risk models, big data is already reshaping the way financial services work.
The SNS Telecom report also indicates that insurance services will have the second highest distribution of big data investments. This year insurance services will account for 28% of big data investment among financial services.
Big data is facilitating the creation and success of innovative fintech startups, notably in online lending, regtech, and alternative insurance. Among the innumerable use cases for big data in banking, one is predictive marketing.
“One reason that personal and business banking are definitely high areas of investment is because of the high but hidden cost of customer attrition,” Nate Derby, CEO of Stakana Analytics, a predictive marketing firm for banks and member of INV Fintech, told Bank Innovation via email. “The cost of acquiring a new customer is 3-5 (or more) times the cost of retaining an existing customer.”
Derby says big data can provide a two-fold value for banks, marketing to consumers.
“With big data, we can find which customers have the highest risk of leaving and target our marketing to them,” he said. “Once we build the data infrastructure for that, it’s easy to tweak that infrastructure to also use it to serve customer engagement/cross-selling. So now our big data platform is twice as valuable (i.e., addressing both the attrition and the cross-sell problem).”
While data can unlock valuable insights and innovations for financial services processes some banks have taken a conservative approach to use data.
Kelly Colbert, U.S. Bank’s senior vice president of brand advertising and social media, previously told Bank Innovation that the bank hasn’t quite taken a liberal approach to use data.
“U.S. Bank tends to be more conservative than most banks, which can be frustrating for marketers,” said Colbert.
Datasets, especially those that have been aggregated, will continue to provide value for banks. Investment and what banks stand to gain will likely overshadow risk around compliance and see an increase.
Although the SNS report is behind a paywall, a summary can be found here.2 - Readers Like This Post