Cracking the data silos in banking

Few industries face more regulatory tangles, legacy systems, and transformational new technology than the banking sector. “Banks set the stage for customer acquisition”, an article in the February issue of Bank Systems and Technology,  has an interesting study in one bank’s approach to managing customer data for sales and marketing purposes.

The fundamental challenge for banks is that they have long been organized by product and/or channel, and customer data has typically accumulated within application silos that serve that departmental structure. Great Western Bank, a South Dakota-based bank with $9 billion in deposits, tackled the challenge of creating accurate and integrated customer data by forming a data team comprised of members from across the bank. The committee, which reports to the bank’s business intelligence operations council, created standard definitions for different tiers, pricing and terms on accounts that are now used across all systems.

As Ron Van Zanten, VP of data quality, noted, getting buy-in from various users who had built fiefdoms of data within their departments had been difficult as a centralized data warehouse was built. But since they’ve been able to standardize and improve data quality, they have been able to integrate external data from Experian and start to base their marketing on integrated, predictive models–something that fewer than half of all banks were able to do according to a recent SAP survey.

In short, the ability to use external data effectively required getting internal data in order, and getting internal data in order required the buy-in and participation of all departments in the bank.