Dr. Yachen Lin, Chief Risk Officer of China Guangfa Bank Credit Card Center (CGB), was interviewed while at the 2011 Premier Business Leadership Series in Singapore. He discussed the analytics culture at CGB - explaining how CGB uses analytics to know its customers and manage risk.
There are only 14 banks in China, four state-owned and 10 corporate owned banks. (According to the FDIC, there were 8,430 FDIC-insured commercial banks in the US as of August 22, 2008.) CGB, a corporate-owned bank, was founded in 1988 and was the first in China to develop a credit card (in 1995). Today, CGB is the only credit card issuer to have earned profits on its cards for six consecutive years. As of 2010, CGB had issued more than 11.5 million cards.
According to Dr. Lin, by 2005, CGB could no longer remain competitive without SAS - the volume of data had become too large to handle any longer. “We needed the segmentation capabilities of SAS,” said Lin.
Big data analytics
That 2005 data challenge was not nearly so daunting as the one CGB would face today without SAS. “Today, the challenge is the volume of data, but also translating that data into actionable insights,” he said. “We use insightful analytics – predictive analytics – to know the internal variables between our customers.”
When asked if he could share how CGB manages risk, Lin said that the first step is storing the data. The challenge then becomes making sense of so much data. “We needed a tool, and SAS provided it,” Lin said. “The tool isn’t enough, of course. There was much more work to do. In risk management, you have to assess a limit, ‘Who is worth how much?’ This involves many complications for which we use predictive models.”
In response to the interviewer’s final question, Lin said that some smaller Chinese banks could leap frog their competition using analytics – maybe. “But, larger banks will have trouble because it is harder to change the direction of the older machines.”
Today, we think of China as the new frontier, but it seems that breaking the mold is so very difficult everywhere. How is your organization using analytics? How did you introduce an analytic culture? Were there boundaries and barriers?