One of the most important assets to a credit union is its database. With the information contained in this central repository, credit unions can contact members, comply with regulations, and understand account and lending history.
However, this valuable resource goes through a strain during a merger. During this period, credit unions need to combine different systems that may contain different types of information and be on different sets of data standards.
This can put a strain on overall data quality at the worst time possible. Credit unions need to make any transition during a merger as easy as possible for members. Without a contact database free of duplicate records and inaccurate information, it is difficult for credit unions to understand members or communicate with them.
Credit unions should standardize information, combine accounts, and update information. This will help ease growing pains and ensure credit unions can serve members to the best of their ability.
The first step in any database consolidation is to standardize information. While the current internal database may be familiar, the newly acquired institution's files are likely formatted differently and not held to the same set of data quality standards.
There is no uniform way across the industry of entering and maintaining information, so every database looks different. Credit unions need to review information and see what fields need to be retained and what information is missing from each database. However, contact information is a great place to start when it comes to standardization.
Contact data can easily be transposed to a set of standards through software tools. For instance, a mailing address can be changed to the country's national postal authority format.
By cleaning existing records in bulk, stakeholders improve matching results later on. Additionally, back-end validation tools can help in updating incomplete and outdated records.
Duplicate accounts are problematic during any migration process. Merging credit unions can have overlapping members or databases can contain multiple records for each account. Some credit unions even have different databases for various departments or functions, which can lead to information being spread across the institution.
However, it is vital that duplicates are consolidated so credit unions can get a firm understanding of member history and can communicate intelligently with those members during the transition and beyond.
To get started, credit unions need to select matching elements to determine where duplicates can be found. Stakeholders should determine the level of matching they want to accomplish, as well as the tolerance level for what is considered a duplicate record for that particular institution.
This process can be very rigid or flexible, depending on the number of records and how much a credit union wants to review potential duplicates.
Once the criteria is set, credit unions can begin to merge accounts. This merging can be done manually or through software tools, depending on the size of the database or the amount of technical resources available. However, it is important to keep in mind that one of the top causes for data inaccuracy is human error. The larger the database, the more important it is to utilize automated processes for merging accounts accurately.
Updating Data To Ensure Consistency
Member information is very fluid and changes frequently. Because of this, contact records can be incomplete or become outdated quickly.
The age of incoming credit union data may be unknown and cause stakeholders to question its accuracy. Credit unions should put a plan in place for updating information in the newly combined database. While updating much of this information will require reaching out to members, certain contact fields can be updated with current information with minimal interaction.
For instance, address information can be updated easily. The USPS has National Change of Address, which businesses can utilize through third-party vendors. Credit unions can determine whether an individual has moved and send a request to the member for updated address information.
Creating A New Database For Growth
Merging databases is a relatively smooth process if proper planning is done and data quality is taken into consideration prior to migration. By merging a database accurately, credit unions can gain a firm understand of their new members.
With a centralized database and tools in place to ensure data accuracy, credit unions can enhance staff efficiency and improve member service during a merger and for years to come.
Thomas Schutz is SVP General Manager of Experian QAS.