10 high-performance analytics tips for bankers


Bank Systems & Technology just published a special issue focused on "big data" - and how high-performance analytics helps solve the big data problem. Clicking on the cover image will take you to the ebook, so you can flip through 24 pages full of information about the benefits of big data for banking.

Since some of you don't have time to flip through the whole thing, I've pulled out some key points here. Honestly, there are dozens of ideas worth sharing in this publication - but these are my favorites:

  1. If you're tired of working in silos, high-performance analytics is your friend. Part of what makes big data big is that it's coming in from all areas of the business. To really use it as an asset, you need to move out of your comfort zone and break down organizational boundaries (page 4).
  2. The traditional model of storing data in multiple silos will change. Instead, banks are looking for one large system that stores data from all across the bank (page 5).
  3. Trendy terms for data management in 2012 include granular reporting, requirements management, data lineage and front-to-back linkages. Terms ilke systemic risk and data overload are on the outs. Read dozens more on page 7.
  4. It is hard to force fit analytics into a traditional database. Data needs a place where deep and complex analysis can occur without being constrained by a transactional database (page 8).
  5. Because of capital overlay for each customer, the relative profitability of each customer is going to matter more for banks than it did in the past (page 10).
  6. Unused data is, simply, overhead  (page 13).
  7. Use customer data to recognize which customers can benefit from new banking efficiencies (page 13).
  8. Soft skills are just as important as technical skills when hiring analysts (page 17).
  9. Use data from 17 million customers and 19 million transactions for an early-warning system to detects customer disengagement - like one US bank (page 20).
  10. Another global bank is processing more than 100 million rows of data per month, along with a reporting repository fo rmore than 5 billion rows to make sure its single vision of the truth encompasses both risk and finance (page 21).

This is day three of my "HPA once a day" blog post series. To read more, follow the high-performance analytics posts on this blog.













About Author

Alison Bolen

Editor of Blogs and Social Content

Alison Bolen is an editor at SAS, where she writes and edits content about analytics and emerging topics. Since starting at SAS in 1999, Alison has edited print publications, Web sites, e-newsletters, customer success stories and blogs. She has a bachelor’s degree in magazine journalism from Ohio University and a master’s degree in technical writing from North Carolina State University.

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