Competition in Taiwan’s credit card market is rife with the over-saturation of card providers, low customer loyalty and low threshold for account transfers. This means that the customer engagement cycle within the consumer financial services space is extremely short.
Banks are investing in a myriad of marketing activities using different approaches and touch points to reach out to customers. In fact, it is not unusual to see multiple marketing activities taking place concurrently, including retail tie-ups and seasonal promotions during payment of taxes and school fees, which sees high usage of credit among Taiwanese. There was an urgent need for Bank SinoPac to better understand customer usage patterns in an agile and timely manner using data.
Microsoft’s recent Asia Data Culture Study found that 88 percent of business leaders in Asia recognize the need to have an agile business that is data-driven in today’s business landscape. However, only 43 percent of respondents believe that their organization is equipped with the corresponding digital strategy today.
Led by Wang Wenyu, Head of Consumer Banking Division and Cai Ruiting, Head of Information Technology Division, Bank SinoPac’s management started to embrace a new data culture and focused on 1) having an agile data infrastructure, 2) ensuring data governance for collaboration, and 3) having an analytical workforce.
SQL Server R Services enabled them to tap on and set a benchmark for organizations looking to turn into a more agile business.
Said Wang: “We hope that in the future, we will make use of advanced analytics to better evaluate different marketing activities to ensure that we are investing in marketing resources with the highest returns. As such, the time is now ripe for us to create infrastructure and analytical tools that can increase efficiency and shorten the time required for analysis.”
From analyzing the past to forecasting the future
For enterprises using analytics today, current platforms like Decision Support System (DSS) share what has happened, but not Why or How it happened.
With the Why’s and How’s, Bank SinoPac felt it could put together specific activities for targeted audience groups to engage with promotions that they are interested in. For example, by identifying the spending habits of working professionals in Taiwan, the team at SinoPac was able to provide special offers through select channels and entice spending via credit cards.
As the demand for deeper analytics grew within Bank SinoPac, Wang saw the need to prepare the organization’s infrastructure and analytics capabilities for the future. Although the standalone tool that they were using could originally fulfil their current needs, it offered little clarity on the algorithm used, restricting its application to just pre-set functions.