3 Keys to Improving Data Quality

Banks are investing heavily to analyze all the data they collect on their customers, but the best results from big data initiatives requires ensuring accurate data.

As data and analytics becomes more prevalent and important in understanding customers, ensuring data quality can be a big challenge. A white paper released this week by Experian QAS that surveyed 300 IT and business leaders across several industry verticals found that on average 25% of the data those companies collect is inaccurate. And while 82% of the respondents said their company has an analytics department for improving customer intelligence, 43% of them acknowledged that they aren't able to maintain accurate information for daily operations. Companies will never be able to fully realize the potential of data and analytics if they can't make up for that deficiency in accurate data. To start improving the quality of their data, Experian's research suggests that companies need to link customer records across all of their departments, improve their data collection processes across all channels and make sure they are getting accurate information form third-party sources.

Linking Customer Records

Banks' data is often spread out among multiple databases and parts of their organizations. To start linking customer records across those different departments, banks should standardize customer contact information throughout the organization. If contact information is standardized it can be used to locate duplicate records across different databases, the white paper argues. And database software should be used to identify duplicate records, since doing so manually can be prone to human error.

It's also important for banks to create their own definition of an ideal single customer record or profile and what identification criteria they'd like to use. Sometimes it might be best to have a record for each individual customer, while in other cases it could be better to group one household under a single record, Experian's paper points out.

Improving Data Collection Across Channels

With banks collecting information across so many customer service channels there are a lot of opportunities for error. Individual employees or customers could enter incorrect information, different data can be collected from different channels, new accounts can be mistakenly created for existing customers and so on. Putting verification software in place can help standardize data before it goes into the database, the paper recommends. And banks should create processes to make sure that the most important information is automatically verified across channels. Banks should also invest in improved search capabilities to help employees find the right records to help customers quickly and efficiently.

Adding Outside Information

Many of the respondents in Experian's survey used third-party data for a number of purposes such as searching for prospective clients, modifying ad campaigns and making business decisions. But effectively using third-party data has to begin with identifying the uses for it early on and tailoring processes for those uses, the paper says. And gathering information that is not pertinent to the intended use is a waste of resources, the paper points out. Lastly, banks need to figure out how they want to append the information from third parties. If a bank is trying to segment their customers then information can be added in bulk, where as if the goal is to adjust a marketing campaign, it would be best to add the data in real time.

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Jonathan Camhi has been an associate editor with Bank Systems & Technology since 2012. He previously worked as a freelance journalist in New York City covering politics, health and immigration, and has a master's degree from the City University of New York's Graduate School ... View Full Bio