State of Big Data in the Financial Industry

A 2013 SAS Financial Services Executive Summit provided the following conclusions from a panel discussion that took place at the summit. The thesis of the conclusion reiterates the case for Big Data, and underscores the importance close collaboration between Finance and IT. The authors postulate that “Organizations have to align technology and business departments to answer a larger question: How can we get the most value from data across the enterprise?” They highlighted six steps to improve awareness between IT and business:

1. Make data responsibility core to the business – Regulatory compliance is a fundamental business requirement. As an example, banks and risk companies are subject to rigorous data quality thresholds by the Federal Reserve. The industry at large was eager to establish these requirements.
2. Build bridges between the business and IT – The panel agreed that the business decision-makers need to understand IT, which needs to be considered early in strategic planning. Adequately equipping the IT infrastructure to support anticipated future business needs would enable dynamic response to changing market demands and opportunities.
3. Think iteration and collaboration – Historically, a “waterfall” approach was implemented, which requires a comprehensive specification matrix at the outset, mandating that all requirements must be gathered before development can begin. This antiquated approach was bogged down by excessive over-specification to ensure all relevant information was considered. A newer “agile” approach utilizes quicker evaluate-change-tweak-improve loops to more quickly incorporate improvements. The conclusion has been “The more you know sooner, the better off you are.”
4. Start small and build incrementally – The panel concluded that the most effective way to implement data governance was to identify a critical pain point and work tactically to solve that problem before expanding. Executing incremental improvements is a way to capture progress sooner, and should relieve pressure of implanting a more broad-scale change.
5. Promote your success – It is useful for business executives to understand quantifiable business gains realized from data governance. Accurately reporting profitable improvements can help justify future requests for added resources or facilities to further the financial efficiency of improving the way data is communicated.
6. Establish an analytics center of excellence – Similar to the help desk approach taken by many corporations for desktop support, the panel noted that decision-makers should consider a similar solution for analytics, a “center of excellence”. Such a solution would aim to address the following:

• Develop and promote analytics best practices, talent and resources across the organization, sharing and reusing analytical work as appropriate
• Educate decision-makers on the value of analytics as a competitive advantage, and help them use analytics to support their decision-making process
• Experiment with the art of the possible by developing and testing advanced applications
• Work to gradually change the internal culture to embed analytics as a natural part of the decision-making process.

Like most industries, the financial sector is poised for a shift in the traditional business model with the rise of big data. Companies who embrace the movement will position themselves for long-term success by changing their culture to accept, utilize and apply the myriad of information to which they now have access.