[동향] 해외 금융산업의 빅 데이터 사례와 교훈

 

<*> Banks Use Big Data To Understand Customers Across Channels

http://www.forbes.com/sites/tomgroenfeldt/2013/06/11/banks-use-big-data-to-understand-customers-across-channels/

 

Thomas Davenport and Jill Dyché

 

 “Big Data in Big Companies,” it included looks at health insurance, retailers like Sears and Macy’s  and industrial firms such as GE, UPS and Schneider trucking. In finance, the firm interviewed Wells Fargo WFC +0.74%, Bank of America BAC +0.38% and Discover.

 

주요 활용 분야 :

 to understand multi-channel customer relationships

 

접근방법:

분석대상 데이터 >> structured and semi-structured 

      (+ website clicks, transaction records, bankers’ notes and voice recordings from call centers)    효과 >>  better at understanding common journeys,

             monitoring for quality of service

             and identifying reasons for attrition.

 

[Interesting] that while a lot of big data talk is about unstructured data or social media analysis,

banks seems to have plenty of work just to understand the mostly structured data they already have and generate daily.

 

 

<*> Banks Using Big Data to Discover ‘New Silk Roads’

 

http://blogs.wsj.com/cio/2013/02/06/banks-using-big-data-to-discover-new-silk-roads/

 

Banks are now "seeking answers to questions such as whether they always eat dinner out or whether they offset shopping at high-end department stores with trips to discount stores"

 

 

 

 

<*> Case study: How big data powers the eBay customer journey

 

http://www.computerweekly.com/news/2240219736/Case-Study-How-big-data-powers-the-eBay-customer-journey

 

With 50TB of machine-generated data produced daily and the need to process 100PB of data all together, eBay's data challenge is truly astronomical.

 

 

The challenge for eBay is that web analytics is like having a video camera mounted on the head of every customer going into a supermarket, said Stephenson. Recording everything every customer does generates 100 million hours of customer interaction [per month], creating an unmanageable amount of customer data. "There is no way to start if you want to process 100 million hours [of web analytics]," he said.

"We need to understand customers, learn from our customers and apply data science techniques to allow us to get more data and new types of data."

 

 -- (Speaking at the Gartner CRM Summit in London, David Stephenson, head of global business analytics at eBay)

 

 

The eBay site has 100 million customers who list

items in 30,000 categories.

In terms of transactions, the site processes thousands of dollars per second.

And Stephenson described this transactional data as "just the tip of the iceberg".

 

In 2002, eBay built a 13TB Teradata enterprise data warehouse, which effectively provides a massive parallel relational database. This has now grown to 14PB, with the system built on hundreds of thousands of nodes.