Governance is about prioritization, and data management is no different-certain types of informational inaccuracies need to be corrected before others, particularly for compliance and reporting.
There's not much in banking that doesn't hinge on data these days, whether it's risk management, compliance, customer relationship management or marketing. Ensuring that data is reliable, and available when needed, has become a growing industry as banks hire data scrubbing firms to keep things in order.
Spain's Banco Popular is at the forefront of this movement, recently wrapping up a project that added automation to the bank's data management procedures.
Spain's third largest bank, which also has a presence in U.S. markets such as New York and Florida, has installed a data quality engine from Informatica to help inspect the data the bank uses to for compliance, sales, reporting and service.
The bank's data strategy includes the production of a data quality index based on 23 variables-such as name, date of birth, education level, occupational codes and other demographic and transaction information. Banco Popular then classifies these data variables as "mandatory," "necessary," or "desirable" based on business rules designed to govern data triage. For example, "mandatory" data refers to compliance, "necessary" data is typically used for business requirements and "ideal" generally refers to data used for marketing, such as information revealing consumer interests.
The bank, which had been using manual programming to distinguish data variables, now uses Informatica's technology to scan data to ensure inclusion and consistency of these variables across departments, with errors sent back to pertinent business lines for corrections to be made based on the bank's prioritization rules. Informatica is helping to automate this "scrubbing" to find overlapping data, missing fields on customer documentation and other informational errors that can dilute a bank's CRM, compliance and governance. In the tech firm's "proof of concept" it scanned 280,000 records.
"Often when you are doing business throughout the day, data is created at ATMs or on the Web or on another channel that is recorded with mistakes, or with the right information on the wrong place on a form," says Craig Clearwater, a vp at Informatica.
Clearwater says prioritizing these fixes based on a rules-driven hierarchy permits data corrections to be optimized across an enterprise. "The 'nice to have,' for example, may not be fixed right now, but at some point in the future," Clearwater says.
Informatica has about three dozen financial firms using its data quality technology, and faces competition in the enterprise data cleansing space from data management and analytics firms such as Epsilon and Experian.
There are still challenges. Ron Shevlin, a senior analyst at Aite Group, says that beyond identifying inaccurate data comes the task of repairing the source of the data. "What's the cost of fixing these systems, such as legacy applications, that have caused the data quality problems in the first place?"
Alberto Romero, director of Banco Popular's quality office, says the advantages of the new deployment include access to a dictionary of existing data domains, which allows ease of use benefits, such as the ability of staff without a technical background to use the system to ensure data quality. Romero says the bank's intention is to involve business users from branches to regional management in data quality so that is it "not seen as a task exclusively for IT."
Jost Hoppermann, a vp of research at Forrester, says Banco Popular's strategy of prioritizing data cleansing using an index is not yet mainstream in banking, but it's a type of approach that should get more traction in the future as data quality becomes ingrained in fundamental credit decisioning. He also says his firm's research shows that banks will increasingly become dependent on quick access to accurate customer data for CRM purposes in the future.
Data cleanliness is a task that banks have long struggled with in a siloed environment. But Jacob Jegher, a senior analyst with Celent, says the growth of personal financial management will shine a spotlight on data quality as a driver of event-based marketing. "The game changer is going to be [PFM], to be able to accurately see the spending habits of your customers," he says.
This article can also be found at AmericanBanker.com.
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