Credit unions are working to understand their members to better meet needs and provide a meaningful banking experience. This personalized experience is what has set credit unions apart for many years. However, today that credit union trademark is in jeopardy.
Today's consumers change preferences at a rapid pace and interact with their financial institutions through more digital means. This reduction in face-to-face interaction makes it harder for credit unions to provide a high level of personalized service. It is no longer the norm for consumers to personally know the tellers at their local branch. Today's consumer prefers online and mobile banking paired with direct deposit.
In fact, Jim Marous, a marketing services leader focused on building strategic solutions for the industry, recently wrote on his blog that within the last year, 90% of people have checked their bank account's status online, and 48% have downloaded a mobile app for doing so.
Understanding Members
The reduction in personal interaction leaves credit unions relying on data to better understand their members. Unfortunately, this trend it tied with an increase in channels. According to a recent Experian QAS survey, organizations interact with customers across an average of 3.6 channels. The most popular are the organization's website, physical branch location, and face-to-face interaction with a sales team.
The variance in channels is hurting organizational data quality by creating inconsistencies in data entry and information spread out across multiple departments or channels. On average, businesses are operating with an average of four different databases across their organization.
To better understand members, credit unions need to link consumer information stored across departments and channels into one record for each member. This will allow credit unions to have a consistent member view, providing better insight to craft messages and make more informed business decisions.
However, merging records is not without its challenges. There are three steps credit unions can consider when looking to merge member databases or records.
First, standardize contact information. Contact details are contained within almost all member records, regardless of the department. By standardizing contact information across databases, the information can be used as a unique identifier to locate duplicate records.
Next, credit unions should define the meaning of a single record. Each organization will have different definitions of an ideal individual record. For some, each individual consumer should have a record. Others may prefer to have records categorized by household or family or perhaps by various accounts or services that members receive.
Defining Data Organization
Credit unions need to define how they want the database to be organized. They should decide if they want each individual to have their own record if they want to divide information by account or service. Decide what criteria or elements can be used to identify duplicates and merge them.
Finally, institutions should utilize matching software. Duplicates are typically found within every database and are more prevalent when combining records across departments or channels. While manual processes can sometimes be used to identify duplicates, the amount of data credit unions are dealing with today makes it challenging and error prone to review manually. Utilize software to better identify duplicate records and set automatic merging standards based on defined record criteria.
Better Understanding
Credit unions need to be sure they are still able to provide a personalized experience to members. As they move away from face-to-face interaction, credit unions will need to become more sophisticated and rely on intelligence to generate relevant online messages.
By creating a single member view and linking records across the organizations, credit unions are able to get a complete view of each member. By employing data management best practices, credit unions can create a complete picture to better understand their members through data.
Tom Schutz is general manager with Experian QAS. For info: www.qas.com.
