To build or not to build (buy) – That is the question for credit unions
As the Age of Analytics for credit unions rolls forward, the question of “Build or Buy” is faced almost daily by decisionmakers. It comes at all stages in the data and analytics journey, so credit unions must understand the tradeoffs in deciding to Build or Buy.
First, however, consider the question itself: Build or Buy. “Build” means the credit union uses its own resources to design, construct, launch, and maintain an application or capability. “Buy” means acquiring these same elements from an entity outside the organization.
The fast pace of technological evolution has added an innovative dimension the definition of “Buy”. Increasingly, “Buy” includes Software as a Service (SaaS) as well as on-premises implementations.
The Build Option
The perceived advantages of Build are customization and control. By keeping projects in-house, the Credit Union can design a system tailored to its unique requirements. Although all credit unions are chartered to do a specific set of services, each has its own flavor for delivering these services.
These Build option advantages favor larger credit unions with greater resources. Having the team depth of a larger organization enables greater possibilities for having both the skills and numbers to take on Build projects.
The major disadvantage of Build is cost. A custom-tailored suit is more expensive than an off-the-rack brand. Another, subtle but important disadvantage is strategic focus. A credit union is wired to be a member-oriented financial services organization. Though it may have gifted technologists on its staff, most credit unions are unlikely to have the technical breadth and depth to build a truly industrial grade application. There is also a big risk of knowledge experts leaving the organization in the current low unemployment environment.
Another cost concern is ongoing maintenance and enhancements. Experience shows custom-built applications are notoriously expensive to keep up-to-date and in efficient working order. The credit union is saddled with this ongoing burden for its data and analytics capability to keep pace with new industry trends.
See 7 Challenges to Consider When Building a Data Warehouse: http://blog.onapproach.com/7-challenges-consider-building-data-warehouse
The Buy Option
At first glance, it might be assumed the Buy option is the mirror opposite of Build. A purchased product will not be exactly customized to the credit union’s specific requirements nor will the organization have as much control over the project. However, this is a game of trade-offs driven by primarily by the size of the credit union. In order to survive, all credit unions must embark on the data and analytics journey. Those ignoring this trend will ultimately be acquired by credit unions that do take data and analytics seriously or simply become obsolete.
For the majority of credit unions, the Buy option holds significant advantages. By giving up some customization and control, the organization gains significant data and analytics capabilities at a more affordable price. In fact, not only is a tested commercial product liable to cost less up front, it also has the advantage of having the bugs worked out as the result of use at multiple sites. Therefore, the cost and headaches of the inevitable errors in complex programming code are avoided. If fact, the perception that a Build project results in a more tailored outcome may be overstated. Most commercial products are very configurable to meet specific credit union requirements.
Another advantage of commercial products is technical excellence. Just as credit unions exist to satisfy the financial needs of members, data and analytics companies are highly experienced in their distinctive competencies. Not only is a product purchased but the buyer also benefits from the accumulated technical acumen of the vendor, something the credit union would be unlikely to possess in-house. Maintenance and enhancements are also easier with a commercial product. Vendors must stay up to date to be competitive and a tested product is less likely to have maintenance problems.
The experience of the vendor also benefits the credit union in the form of Design Depth. There is an old medical adage that the best outcomes are experienced by surgeons who perform the most surgeries. The same can be said of companies specializing in data and analytics for credit unions. With deep experience across many implementations, these companies have “seen it all” and bring that expertise in the form of design that is deep and complete. Simply stated, this means the credit union is purchasing product benefits that reflect best practices from across the industry.
Another benefit is that commercial data and analytics products are “generic”. This seemingly negative attribute has become a powerful advantage in the collaboration-oriented credit union industry. The standardization of data provides huge opportunities for securely aggregating data and sharing it among credit unions. Such regulatory mandates like CECL and technological innovations like predictive analytics depend on large pools of data that the average credit union is incapable of accumulating on its own. The secure aggregation of standardized data is a game changer not only for the individual credit union but for the industry as a whole as it battles banks and fintechs for its share of the retail financial service market.
Finally, a major advantage is the opportunity to deploy the “Buy” option in Software as a Service” (SaaS) model. SaaS supercharges the advantages of the “Buy” option. In the words of Graham Goble, CEO of OnApproach’s Partner, BankBI, “If a credit union buys into a SaaS product then they are buying into a single code base that not only works on day one but is continually improving as the result of many other financial institutions constantly contributing new ideas and features. They are buying the ability to work with an experienced strategic partner whose sole reason for existence is to continually deliver this software to their whole user base, leaving no credit union behind on legacy versions.”
A Buy Option Case Study: BankBI
Graham speaks from experience. One example of this is BankBI’s work with Ideal Credit Union (Saint Paul, MN) to deliver the BankBI Financial Performance SaaS application.
As a first step, BankBI worked with Ideal Credit Union EVP/CFO, Dennis Bauer, and his team at Ideal CU to understand their financial reporting priorities with the aim of delivering a successful outcome.
As stated by Dennis, “During this process BankBI worked to map and mimic our chart of accounts exactly as we would produce in-house and then present it back in dashboards and reports that were easy to consume in terms of both its appearance and content. The fact that BankBI was able to replicate what we needed rather than having to change everything was a major plus.”
Once that was done, robust foundations were in place to support the transformation of daily data from OnApproach M360. According to Dennis:
What was striking about initial setup was that we found it so easy to organize it on either a top level, trend-based appearance or in a more granular way where we could dig down and see loan portfolios and subsets of those portfolios. We also really liked both the professional way it looked and felt. BankBI had mapped and recorded our data and come back with something that looked and felt much better format-wise but that we could still consume and understand.
(See https://www.bankbi.com/bankbi-case-studies)
The Decision: What is Right for Your Credit Union?
In the end, the Build or Buy decision is dependent on your credit union’s unique situation. If your organization has substantial financial, technological, and skill resources, then the Build option may seem to make more sense. However, the vast majority of credit unions do not enjoy this high resource level and even with such resources the advantages of buying commercial products far outweigh any advantages of a do-it-yourself project. As a result, the Buy option with a strong consideration of the SaaS model is an effective and efficient way for your organization to begin the essential data and analytics journey.
