In a perfect world, financial analytics would be prophetic—accurately predicting the outcome of every capital market move, investment choice, and loan decision. Unfortunately, financial institutions aren’t quite so utopian. They cannot ignore the impact of Big Data in their financial world, especially when their audiences’ awareness and expectations are on the rise—for example, stakeholders expecting real-time response to market fluctuations or customers expecting higher levels of service.
The solution? A new kind of insight based on analytics platforms which converge, extract, and present actionable data to bank executives to drive more profitable decision-making.
Great Expectations
Banks have worked hard to roll out front-end service improvements such as mobile access and Web-based response, but still lag behind when it comes to improving back office procedures such as mortgages and loans. Part of the problem stems from privacy issues, and part from the overwhelming amount of structured and unstructured data generated—especially if factoring in social media data to evaluate loan application risk.
Business World, meanwhile, points out that analytics in banking has become a “key focus” in the last several years since up to 80 percent of cost servicing can be directly tied to data. In other words, there’s real impetus for banks to make better use of Big Data, since better decision-making means better returns and improved investor confidence. Many institutions are stuck, however, with voluminous amounts of data, but limited analytics scope—effectively putting the goal in sight but obscuring the road ahead.
Infrastructure Evolved
Banks are fully cognizant of the implications of Big Data. In fact, a large majority have already built the infrastructure necessary to handle the secure storage of raw data. But the challenge they now face is extracting value from all that data. Untapped, these storage containers are an inevitable loss essential to long-term success, but without a defined mandate.
Generating profit requires the ability to model disparate data from previous incompatible sources with the dual aims of enhancing risk management and generating new investment strategies. In effect, financial institutions have laid the groundwork to tap data at source and also clearly see the need for actionable Big Data at multiple endpoints. What’s missing is a bridge between necessary loss and the promise of profit—an analytics platform capable of transforming historically reticent organizations into event-enabled powerhouses ready to empower consumers and embrace investment decisions with equal facility.
Bottom line? New insight is equal parts prophecy and preparation, underwritten by the right infrastructure and ideal analytics platform.
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