Out with the old and in with the new: Reporting & analytics for credit unions
If you are responsible for report writing (including dashboards) at your credit union or you are a report consumer, you know the problem: the current process for fulfilling reporting requests is broken and it has been for years. The Business intelligence industry has failed to deliver on its promise. IT departments are overloaded and users are frustrated. The ability to close the gap between the current state and the need to quickly become an analytic driven organization is unobtainable for the vast majority of credit unions.
To understand why it takes so long to create a report, it helps to understand the process. The report writing process often uses a SQL-based language that requires expertise and a high level of precision. For example, things like applying the correct filters or using the right syntax will directly impact the accuracy of the report. Highly defined requirements go a long way to helping improve the process. Unfortunately, the requests that come in from business users are usually quite vague leaving the interpretation to the report developer.
The current report creation process is, in many ways, analogous to “sausage making process”. Yes, it tastes good but you really don’t want to see how it is made. The problem for report consumers is, unlike sausage consumers, they quite often need to drill into that sausage and then the frustration starts.
Below is a high level summary of the steps that go into the fulfilment of a report request.
- Interpret the user requirements.
- Figure out the data sources and the location of the data within those sources.
- Search through copious quantities of cryptically named tables for the requested data elements.
- Determine the joins (relationships) between the tables.
- Write the SQL to create a view or other kind of integrated dataset.
- Write the SQL to create the report from the view/dataset.
- Format the report.
- Iterate a number of times with the user until complete.
Fulfilling a report request is a time intensive, human error-prone process and it needs to change. Qlik, Birst, and Tableau have made significant improvements in the user experience but these new tools are only as good as the underlying data infrastructure used to create the report.
A good data infrastructure is analogous to a strong foundation that supports a home. This “foundation” is what is referred to as the Universal Semantic Layer (USL) and there has not been an effort to create this for the credit union industry until now.
A well-built USL provides three powerful benefits: (1) a single source of truth, (2) a standard set of credit union data elements supported by business rules, (e.g. – the definition of a Member), and (3) an “open” semantic layer that would improve the speed of creating a visualization like a report or dashboard regardless of the reporting tool being used (e.g. – Cognos, Tableau, Business Objects, etc.).
The USL resides between a credit union’s data stores (e.g. – data warehouse, flat files, MS Access, etc.) and the person creating the visualization. It is a business representation of the data warehouse or transactional database. The USL allows the IT department or end user to interact with their data without having to know the complexities of the data warehouse or where the data is stored. It uses familiar business terminology and embedded business rules to represent the universe of data elements such as Loan Categories, Member Credit Score, and Merchant Name in a format that creates an intuitive, productive user experience.
Larger credit unions that have invested heavily in creating data warehouses understand the need for a USL as well as the time and effort required for its creation. The solution for this problem is collaboration and just such a collaborative effort is being spearheaded by CUFX (Credit Union Financial Exchange), a CUNA-sponsored organization.
Rich Jones, Marketing and Business Development Executive at CUFX, talked about the importance of analytics for the Chief Marketing Officer, “CMOs are faced with a constant challenge to prove the value of their marketing efforts. The channels we use continue to grow, the technology continues to innovate, and the consumer expects more personalization and customization of offers than ever before. To be successful, CMOs must collect, segment, analyze, and visualize the data to be able to create efficiencies in their marketing efforts, to personalize and customize offers, to report to management believable numbers around adoption, and balance growth and profitability.”
Disruptive forces in financial technology are increasing the urgency for credit unions to embrace analytics as a core element of their organizational culture. There is an abundance of data at credit unions today. Yet, there is a lack of means to turn that data into meaningful analytics to better serve their members while improving their financial performance.
