Let’s talk data liberation.
Sometimes, a fintech comes along and changes the entire way we think about something. That’s what Cinchy is doing with credit union data.
And we’re going to try to make this relevant for CIOs and CEOs alike.
Apologies in advance for anything remedial. We think it’ll be worth it if you’re ready to take the next step in using your data (instead of just having it).
The Current State of Credit Union Data
Credit unions produce a huge amount of data, and that data can power big strategic wins. But all that data comes from countless fragmented sources. And, unless there’s a solution in place, all that data stays locked in those sources.
The best solutions until now have been data warehouses and data lakes. Whether in-house or outsourced, these solutions try to improve data management and strategy by ensuring that data from different sources ends up in one place, rather than silos that never see each other.
For remedial purposes, we’ll clear up the difference between data warehouses and data lakes here. It’ll be important in a minute:
- Data warehouses are storage spaces where data is collected, transformed, and structured from different sources. They are excellent for analyzing historical data, but they require data to be cleaned and formatted first. This is tedious, expensive and requires a lot of maintenance. They are rigid in design and require a heavy dependency on IT teams for new reporting requests centralizing all demand for your CU.
- Data lakes store vast amounts of raw data in its native format. Although it still requires maintenance, this approach offers more flexibility as far as what types of data (and how much of it) can be stored. However, because the data is unstructured, it’s harder to draw insights and get value out of the data.
It’s true that both solutions can store all of a credit union’s data in one place. But the claim is that warehouses and lakes reduce silos. That claim isn’t altogether correct.
The reality is that data warehouses and lakes store all the silos in the same place. The data may be grouped together, but it’s still siloed. It’s still separate. It still requires a lot of time-consuming integration and management to connect that data as more and more silos creep up
But that’s where Cinchy comes in.
Cinchy bills themselves as a data collaboration platform that can liberate credit union data. Their technology allows data from different sources to be commingled. This allows a seamless flow of data across sources and departments, eliminating barriers, silos and drive to self-service where all employees in the credit union can leverage data.
There are a few benefits to this approach:
- Better, more complete data. Cinchy eliminates the need to transform, structure, and integrate credit union data. In turn, this offers more complete views of members, trends, and opportunities.
- Reducing Integration Friction. Once data is liberated, you can reuse it over and over again. Resulting in less data copies, eliminating future integration costs and using data to pay it forward.
- Real-time insights. Because data is designed to seamlessly connect to core applications, it unlocks the ability to now bring real-time capabilities to your CU replacing nightly batch processing in order to access data.
- Future-friendly architecture. Thanks to its ability to deliver more complete, real-time data, Cinchy is positioned for the future of fast-paced technology, strategy, and fintech solutions.
- Two-way data flow. Improving data every step of the way. Most analytical solutions are read-only and 1 way. With Cinchy, you have a place for even net new data! Resulting in eliminating future silos as well.
The downside of discussing any data solution is this:
Data—from storage, to management, to how it’s used—is simply a tool that credit unions use to accomplish their goals. We can’t say, “Cinchy does this tangible thing for your members, your balance sheet, your staff…” It’s too variable.
Rather, we can say, “Cinchy gives you the complete platform to make better, faster decisions than other solutions.”
Use Cases for Cinchy’s Data Liberation
If you’re not feeling creative about what Cinchy’s solution can do (or what data liberation means), here are a couple things we’ve learned:
In one instance, a credit union saw that they were about to lose $1 million in deposits to another financial institution. Within minutes of the transaction, that credit union was able to guide that member to reinvest that money and more, netting $1.7 million in deposits with a phone call.
In another instance, a credit union considered a daily dividend increase to drive deposits. After examining their trend data, they found no benefits to their members and scrapped their dividend increase, which saved them $180k in annual expenses.
If you’d like to learn more about how Cinchy works, download this:
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