Banking / Finance

6 guidelines to adopt big data for Finance

16th Oct `14, 06:11 PM in Banking / Finance

The big data revolution has dramatically changed the financial services industry. The following driving factors have motivated the…

BDMS
Guest Contributor
 

The big data revolution has dramatically changed the financial services industry. The following driving factors have motivated the need for financial sector companies to collect, store and analyze massive volumes of data:

1. Changes in the delivery of financial products and services. Customers no longer need to physically visit their local bank to make deposits, make investment decisions or complete their banking transactions. Buyers and sellers of stocks execute their trades online instead of relying on brokers. Individuals file their taxes using online tools versus meeting with a tax accountant to prepare and file. As the industry has increasingly moved online, it’s become faster, easier, and more affordable for consumers to handle their own banking and financial transactions.

2. The result of these trends is that financial services and products have become commoditized. Instead of establishing relationships with a local service provider, customers often choose the most convenient and inexpensive online offering available. Personal connections as a requirement for customer loyalty has changed dramatically. However, every action made by a customer can be captured and analyzed by organizations seeking to understand the behaviors and preferences of their customers as they would have traditionally done through in-person interactions—now however, the process has become digitized.

3. Increased volume of activity. The ease and affordability of executing financial transactions via online mechanisms has led to ever-increasing activity and expansion into new markets. Individuals can make more trades, more often, across more types of accounts, because they can do so with online tools in the comfort of their own homes, or on the go from a mobile device.

Read More
MORE FROM BIG DATA MADE SIMPLE