Banking and Big Data will soon be inseparable. In 2014, financial institutions are investing more into their customers, and their organizations. New understanding of both structured customer data and unstructured data, is changing business strategy at some of the largest banks.
To keep pace with evolving consumer preferences such as mobile banking, financial institutions are making data-driven decisions to deliver more effective, targeted marketing and services. Big Data is also emerging as an effective tool for banks to fight fraud.
In a report, Bankers as Buyers, the William Mills Agency presents research and insights on data science technology solutions that U.S bankers will buy in 2014.
Key takeaways
“Managing Big Data is a big challenge. It is no surprise that financial institutions are investing heavily in data analytics technology to leverage their information and use it to enhance all facets of their business.”
– Steven J. Ramirez, CEO, Beyond the Arc, Inc.
(Source: “Bankers as Buyers”, Jan 2014)
- Customer Experience – Beyond the Arc CEO, Steven Ramirez, highlighted advantages for banks that deploy Big Data strategies: “Banks can now drill down to transactions by individual ATM. A high number of rejected transactions may indicate a problem with the specific ATM, a problem that would not have surfaced without a customer complaint with less granular information.” He added that leveraging social media can further help banks enhance their customer experience by allowing them to better target customers on a one-to-one, personalized basis.
- Marketing – Mobile banking will bring massive change, as it allows greater convenience for customers, and delivers real-time customer data insights to banks. The report notes that by keeping customers engaged longer, banks can deepen relationships and increase potential for cross-sell and up-sell.
- Fraud – Predictive maintenance is fast becoming a new growth area for Big Data. Banks can now gain insight into ATM problems and other glitches to identify emerging issues and strengthen their fraud prevention efforts. Using predictive analytics, banks can rapidly recognize fraudulent transactions or patterns, and react quickly to mitigate risk. In fact, studies estimate that bank spending on risk management will grow from $470 million in 2014 to $730 million in 2016 as tools mature across the financial industry.