Customer Insight – Useful Big Data


GFT has recently partnered with an innovative Spanish company, Adesis. Like GFT, Adesis works primarily in the financial services sector, and also like GFT, it looks for ways to intelligently apply big data technologies to improve its customers’ operations.

iStock_000017531225XLarge_editRetail banks manage and record their customers’ transactions within their core banking mainframe platforms. These IT systems are based upon older technologies, but do an excellent job of managing client transactions (deposits, transfers, ATM withdrawals, credit card charges, etc.). What they don’t do well is store these data; in fact, most mainframe systems only hold the last two years’ of data. Another drawback of these systems is their running costs – banks have to pay on a per-use basis.

To solve both these problems at once, Adesis designed a big data system which pulls transaction data from the mainframe systems and stores them into a NoSQL database. By offloading all the historical data and providing the ability to search over them, the new system not only provides a much more efficient way to query the data, but also a much less expensive one.

But why use big data technologies? Firstly, the volumes require it. 10 years of customer data include more than 15 billion records – terabytes of storage. These are data volumes which are not easily managed by a traditional relational databases. Secondly, using ElasticSearch, an open source NoSQL database with super-efficient querying capability (ElasticSearch has advanced indexing and caching capabilities), search times are reduced to milliseconds even for complex queries. Big data therefore provides better functionality, with cost savings to boot.

Adesis has implemented this system for a Spanish Bank and integrated it into the bank’s online banking solution, thus allowing customers to query their own data. How much money do I spend each month on gasoline? What were the largest 10 transactions that I have made each year for the last 10 years? How has my mortgage payments evolved year on year? These are the kind of questions that the banks’ customers can ask, and thanks to this innovative big data solution, have answered in a fraction of a second.

This is just the start, however. With this rich data source, the bank can provide value across the bank, from mobile banking to branches. In particular, the bank can now conduct deep data mining and analysis to understand the behaviour of its customers and identify new products and services.

Big data is just technology, a tool, but one which if used properly can provide great value to banks and customers alike. Using big data technologies, GFT and Adesis are two companies who know how to extract the most value from our customers’ data.

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Are you visiting CeBIT? Don’t miss Karl Rieder’s keynote on: Solving Banking’s Biggest Problem with Big Data

Location: Hall 16 // Time: Monday, 10th of March at 5pm.

 

 

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  1. Big Data Queen10/03/2014

    Karl, Big Data is surely a big deal. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business. For companies any size, getting meaningful insights from data analytics is an important priority. LexisNexis has open sourced its HPCC Systems big data platform which represents more than a decade of internal research and development in the big data analytics field. Designed by data scientists, their built-in libraries for Machine Learning and BI integration provide a complete integrated solution from data ingestion and data processing to data delivery. More at http://hpccsystems.com

  2. Big Data Queen10/03/2014

    Karl, Big Data is surely a big deal. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business. For companies any size, getting meaningful insights from data analytics is an important priority. LexisNexis has open sourced its HPCC Systems big data platform which represents more than a decade of internal research and development in the big data analytics field. Designed by data scientists, their built-in libraries for Machine Learning and BI integration provide a complete integrated solution from data ingestion and data processing to data delivery. More at http://hpccsystems.com