Thinklytics

Lone Star Credit Union · Financial Services · Houston, TX · 20 weeks

Lone Star Credit Union System Consolidation case study

Lone Star Credit Union operated four different core banking systems after three acquisitions, which blocked any unified view of their members. We merged these systems into one member data platform, cutting data costs by $1.3 million annually and delivering same-day analytics that the credit union couldn’t access before.

Challenge

After three acquisitions in five years, the credit union was stuck with four separate core banking systems and no single member view. Combining data across these systems took three days of manual work each time. Maintaining all four data environments cost $1.3 million annually. The board demanded a unified member view before approving any further acquisitions.

Approach

We created a member data platform on Azure Synapse that pulled data from all four core banking systems. We matched member identities across these systems to generate one daily-updated member record. Then, we developed a Power BI analytics layer tracking deposits, loans, product use, and member lifetime value.

Outcome

We launched the unified member platform in week 20, cutting annual data costs from $1.3 million to $310,000. We enabled same-day cross-system member analytics, which improved decision-making speed. Six weeks after launch, the board approved the next acquisition, directly referencing the unified member view as a critical factor.

How We Pulled Member Data from Four Different Systems into One Spot

Our client was dealing with four separate core banking systems, each with its own member ID format, no way to link them up easily. So, we got hands-on and built a matching method that used SSN, date of birth, and account number. When we ran the test, it matched 992 out of 1,000 records. Not flawless, but definitely solid.

How We Pulled Off Same-Day Analytics for Those Last-Minute Board Requests

The board needed quick insights to decide on their next acquisition, like, the same day quick. So, we hooked up a daily data refresh on our unified platform to keep the info coming nonstop. Six weeks in, the board gave the thumbs up to move forward with the deal.

How We Cracked the Code on Member Lifetime Value

We gathered all the member data into one easy-to-understand snapshot. Then, we noticed about 8,400 members had just one product but seemed ready to pick up more. With that in hand, marketing launched a targeted cross-sell campaign. The payoff? $2.1 million in new product sales in six months flat.

Results

  • $1.3M Annual data cost savings
  • 4 to 1 Core banking systems unified
  • 3 days to same-day Member analytics availability
  • 20 wks Full platform delivery

We were using four different systems and couldn’t see the full picture of our members. Thinklytics pulled it all together in 20 weeks, and the board approved our next acquisition the following month.

Chief Data and Analytics Officer, Lone Star Credit Union

In the client's terms

The question

What breaks when these systems become one?

The situation

Three acquisitions in five years had left four core banking systems and no single view of a member. Combining data across them took three days of manual work each time. The four environments cost $1.3M a year, and the board would not approve another acquisition without a unified member view.

What we found

The board's condition was the real specification. This was not a cost exercise with a reporting benefit, it was a prerequisite for the next deal, which set both the deadline and what finished had to mean.

What it produced

Live in week 20. Annual data cost fell from $1.3M to $310K and cross-system member analytics moved from three days to same day. Six weeks after launch the board approved the next acquisition, citing the unified member view.

The roadmap

A member data platform on Azure Synapse drawing from all four cores, with identity matched across them into one member record refreshed daily. A Power BI layer covering deposits, loans, product usage and member lifetime value, which is what the board actually asked to be able to see.

The work behind this result

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Frequently asked questions

How do you build a single member view across core banking systems?

Match on what the systems share. Lone Star Credit Union ran four cores with four member ID formats, so matching on SSN, date of birth and account number resolved 992 of every 1,000 records, with the remainder going to manual review rather than being force-matched.

What does running multiple core banking systems cost?

$1.3M a year here across four environments, falling to $310K after consolidation. The operational cost was larger: combining member data across the four took three days of manual work every time it was needed.

Why does a board require a unified member view before an acquisition?

Because without it the next integration compounds the problem. This board would not approve further acquisitions until one existed. It was delivered in week 20 and the board approved the next deal six weeks later, citing it.