The customer relationship in consumer banking has profoundly shifted, with the primary interaction between a bank and its customer no longer occurring through a teller or even an ATM. Online and mobile banking are now mainstream and money is changing hands through a growing number of channels.
Recent technological advancements such as near-field communication (NFC) payments, app banking and wearable computing technologies will be key drivers in transforming the banking systems and consumer interactions of the future.
With the deployment of new technologies come massive new data-sets that are growing bigger by the second and moving at a staggering velocity. Banks are now facing a critical juncture: they can capitalise on the opportunity created by accessing, analysing and acting on that data in real time, or risk becoming non-competitive in the market.
Yet the process of analysing and acting on data in real time can be a big challenge for many financial institutions. Alarmingly, most of the 2.5 exabytes (2500 petabytes) of data churned out every day by mobile devices, social networks, the cloud and the 'Internet of Things', will lose value nearly instantaneously if not managed efficiently.
So how can banks ensure they make the best use of the Big Data they have available in real time, and what are the benefits?
Data and analytics offer transformational opportunities for banks, similar to how investments in IT infrastructure transformed bank operations by substantially reducing costs. Specifically, Big Data analysis allows financial institutions to not only enhance productivity through more efficient operations, but also generate more revenue through deeper customer engagement, while also saving money by reducing risk through capabilities such as real-time fraud detection.
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 competitor. But engagement doesn’t simply end at a website or a mobile app with fast response times. Banks are actively courting customer loyalty and revenue growth with Big Data applications that allow personalised offers based on the specific account information and past practices of a particular consumer. New services, such as jpeg images of cancelled cheques, are managed through Big Data applications. Even the scalability of the 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 collateralised loans can be supported, allowing banks to meet guidelines for risk.
The quicker they can process the loan and 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 and credit card reporting
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. In addition, Big Data is helping banks improve SLA compliance to 99.999 per cent -- dramatically reducing fees for non-compliance. By employing Big Data solutions, banks are accelerating the processing of online and mobile payments and boosting profits with the ability to instantly identify and reject blacklisted accounts.
Leveraging your company’s Big Data is a tremendous opportunity to enhance the customer experience, boost profits through better fraud detection, intelligently mitigate risk and streamline operations for greater productivity and profits.
Many financial institutions are already using their data to promote revenue growth, manage risk and reduce costs. Those that are not, must ask themselves, "Can we afford not to?"
Stephen Keys is senior vice-president, Asia-Pacific and Japan, Middle East and Turkey at Software AG.