Big Data—A Banking Boom or Bust?

Location-based insight

Business data is growing at such a rate that many organizations can become overwhelmed by the big data problem. A recent McKinsey, IDC, and Department of Labor Statistics analysis [PDF] of data in business found that financial/securities organizations have 3.8 petabytes per firm—that’s more than 400 million gigabytes, or about 12.5 million iPads, per company! Banking comes in a distant second with 1.9 PB. This puts big data found in financial services companies into perspective since this is even greater than most communications and media companies’ average of 1.8 PB.
What does this mean? Your bank has more data than that cable news show you watch, the media service you stream into your office, or all the words the national financial journal you read has ever printed—combined. Big data in banking is really, really big. In fact, it is equivalent to a quarter of the entire global hard disk capacity manufactured in 1995.
Financial services companies are trying to make sense of what they have—to get to the facts, connect the dots, and get some actionable business intelligence. Yet the very nature of big data makes it hard to understand. Financial institutions store almost everything, including financial transactions, social media messages, customer histories, demographic trends, and economic indicators. The whole sector is trying to get better answers and shorten the business cycle. However, for many companies, the answers just lead to more questions; business intelligence becomes just another data point, and the whole cycle starts again.
Location analysis and GIS are a powerful way to connect people to place, transactions to actions, responses to trends, and customers to both where they do business and what kinds of business they do. Location analysis is converting big data into packets of insight, gaining understanding from intuition, and demystifying questions so they may be properly understood for the first time. From fraud detection to branch optimization, and customer loyalty to product segmentation, location analysis is helping shift the advantage of big data in favor of financial services companies. The only question now is how many will seize the opportunity and put location analysis and GIS on the front line of the big data battlefield.

Where do you think location analysis and GIS can best help the financial services sector overcome the scourge of big data?

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2 responses to “Big Data—A Banking Boom or Bust?”

  1. In my opinion, the top 3 issues where GIS and Location Analysis could help tame the huge amount of data are:
    – transaction security;
    – fraud analysis;
    – distributed cache regionalization (of speeding up access for customers).

  2. By incorporating spatial analytics within the spine of a ‘big data’ warehousing capability, users have the opportunity to interact with the data from a location or place based perspective. Essentially we are in the knowledge and understanding business and the increased availability of mapping visualisation services are shaping new ways to interact with data.
    This is driving innovation and enabling organisations to provide more accessible and simplified spatial searching capabilities. A geographic approach improves understanding and supports better decision making to ensure the financial services sector have the knowledge required to design more sustainable financial systems.
    From capital resilience, improved service delivery, stakeholder collaboration and the valuation and availability of essential commodities, GIS has a key role to play in the ‘big data’ debate for the financial services sector and its relationship with the communities it serves. Bring it on…

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