Credit unions, as member-owned financial cooperatives, track and report regularly the number of members they have. Membership is reported to the National Credit Union Administration (NCUA), the credit union board, credit union management and in the annual report to members, among others.
Often the number of members reported varies depending on who at the credit union does the reporting. This can lead to confusion and concern. There may be someone in finance, someone in marketing and someone in administration all reporting on how many members the credit union has, and all reporting a different number of members!
Obviously the total member count needs to be consistent and accurate. However, there are several challenges that must be overcome:
- Lack of agreement on what constitutes a member.
- Multiple sources of membership counts reported by different people.
- Lack of a single source of the truth (i.e. a data warehouse).
- Poor member information data quality.
Let’s see how to deal with each of these challenges when a credit union uses a data warehouse for reporting.
What Constitutes a Member?
The first step in counting members is to define and gain consensus on what constitutes a member. Answering these questions is critical for obtaining accurate member counts:
- Does a member need to have a minimum amount in a deposit account?
- Does the branch that opened the member account get the credit for the member’s activity or is it the branch where the member conducts the majority of their business with the credit union?
- What types of deposit accounts qualify for membership?
- Is there a probation period before membership?
- Can individuals be assigned more than one member number?
- When is a member no longer considered a member?
A common issue is when an individual can have multiple member numbers. When this is allowed, it is important to find all the member numbers for an individual and consolidate them into one member count. This is often done based on a unique identifier such as tax ID. Similarly, if individuals are joint account holders, it is important to uniquely identify each joint account holder so as to count them only once.
Equally important is the need to specify when a member is no longer a member. Is this based on the date they are declassified or when they are placed in a new member class or other criteria?
Once these business rules for counting have been settled, they are ready to be built into the daily load process of the data warehouse which then calculates the member count and stores this information for daily reporting.
It is normally the role of management to determine business rules for membership, communicate those rules broadly across the organization and gain consensus. Once the business rules are determined, we can move to the next challenge.
Multiple Sources of Membership Counts
Credit unions commonly use multiple source systems to manage their members and accounts. Often there is a core system used to manage members. This core system is referred to as the system of record. To tackle the challenge of using multiple sources of information, it is important to identify the system of record for membership and make sure this is the basis upon which the data warehouse is built.
The core system is then used to identify members in other source systems, such as loan origination systems.
Lack of a single source of the truth
Once the data is loaded into the data warehouse it is then possible to incorporate the member counting logic into the daily update process and create a single source of the truth for membership reporting. This is commonly done by applying the business rules for counting members and building an aggregate fact table containing metrics for member additions, losses and net member counts.
Poor member information data quality
Data quality is always important. However, when it comes to counting members, it is especially true. If there are data quality issues apparent in the source system used to manage membership they need to be addressed and corrected there rather than corrected in the data warehouse. It is easier and more efficient to correct the source data than to try to correct it in the data warehouse. Once corrected the daily update process will automatically apply the corrections to the data warehouse.
Having accurate membership counts is critical to the understanding of your customers. Taking the time to define the business rules for identifying members and then implementing those rules using a data warehouse can help overcome the challenges of consistently and accurately reporting the total number of credit union members.