December 11, 2013

Banks generate data -- and lots of it. This data comes from a wide range of sources; from transactions and real-time market feeds, to customer-service records, to name just a few. Never before have banks been able to so comprehensively understand and manage their businesses by using data to enhance their customer experience, reduce risk and streamline operations for greater productivity and ultimately profits.

The customer relationship in consumer banking has profoundly shifted. Gone are the days when the primary interaction between banks and customers occurred through a teller or an ATM machine. Web and mobile banking are mainstream and money changes hands through a growing number of different channels. NFC payments, wearable computing and new, and as yet undiscovered, technologies will be driving the banking systems and consumer interactions of the future. With the deployment of new technology, comes the creation of massive new data sets that are growing bigger by the second and moving at a staggering velocity. Overall, mobile devices, social networks, the cloud and the Internet of Things are churning out 2.5 exabytes (2,500 petabytes) of data every day. Yet a lot of this data loses its value nearly instantaneously because analyzing and acting on it in real time can be a big challenge for many institutions. Banks are now faced with a critical choice: they can capitalize on the opportunity created by accessing, analyzing and acting on that data in real-time, or risk becoming non-competitive in the market. With the right Big Data tools, you suddenly have a real game-changing opportunity that can add millions to your bottom line.

What Can Big Data Do For Me?

Data and analytics offer transformational opportunities for banks. Similar to how investments in IT infrastructure transformed bank operations by substantially reducing costs, investments in data management and analytics technologies are transforming institutions, allowing them to not only enhance productivity through more efficient operations, but also to generate more revenue through deeper customer engagement, and save money by reducing risk through capabilities such as real-time fraud detection.

Customer Engagement: Today’s banks must offer their customers fast, comprehensive and easy-to-use online and mobile services to remain competitive. A single bad online experience can send customers to a major competitor. But that engagement doesn’t just stop at a website or mobile app with fast response times. Banks are actively courting customer loyalty and revenue growth with Big Data applications that allow personalized offers based on the specific account information and past practices of a particular consumer. New services, such as jpeg images of cancelled checks, are managed through Big Data applications. Even the scalability of those websites themselves, through the use of in-memory technologies, is enabling banks to conform to legal requirements for consumer access and service.

Risk and Asset Management: ‘In-memory’ Big Data solutions speed analytics and reporting for faster, more informed decisions on how to best deploy capital and mitigate risk. For example, with faster reporting, a higher volume of collateralized loans can be supported, allowing banks to meet guidelines for risk. The quicker they can process the loan, understand risk and exposure, the more profit the bank makes. In trading systems in the capital markets, banks need to understand their positions globally at any given time to ensure compliance with laws and risk thresholds. Using Big Data solutions allowed a Fortune 20 financial firm to slash its risk reporting time from 45 minutes to 45 seconds, and is now making faster, more responsive decisions.

Fraud Detection & Credit Card Processing: Credit card fraud alone costs banks millions in losses due to bad and fraudulent charges. With traditional systems, data on blacklisted cards comes in too late and the bank, under strict Service Level Agreements (SLAs) to process charges quickly, is left holding the bag. Big Data in-memory solutions can flag blacklisted credit cards instantly, enabling banks to decline a charge before the transaction is completed and still stay within those tight SLAs. And speaking of those SLAs, Big Data is helping banks improve SLA compliance to 99.999 percent -- dramatically reducing fees for non-compliance. By employing Big Data solutions, banks are accelerating the processing of online and mobile payments, boosting profits with the ability to instantly identify and reject blacklisted accounts.

Leveraging your company’s Big Data is a tremendous opportunity to change the game and truly differentiate using data and analytics. Many financial institutions are using their data to promote revenue growth, manage risk and reduce costs. Those that are not should ask themselves, can we afford not to?

Dr. John Bates is CTO for Intelligent Business Operations and Big Data, Member of the Group Executive Board at Software AG