Customer stories
Classifying Sensitive Data for TDECU
Industry
Banking
Employees
900
Use Case
Classifying Sensitive Data
The challenge
TDECU, a Texas-based credit union boasting more than 366,000 members and $4.7 billion in assets with a mission to help people navigate their financial journeys.  Â
TDECU relies heavily on data so it can better understand its members and ensure excellence across banking and operations. It was embarking upon a cloud migration strategy to increase data reliability, reduce administrative work, and accelerate data-driven decision-making. All the while focusing on protecting member data and maintaining compliance.
Critical to their cloud migration strategy was creating a secure environment that meets the needs of their members and helps them achieve their financial goals.  For the TDECU security team, the journey began with data classification and data security posture management (DSPM). Â
The team tried rolling out its DSPM program three different times. Unfortunately, all three vendors and their products failed — specifically because they were all using regular expressions as a way of detecting the different categories of data, which proved ineffective.
While they hoped they had no sensitive data stored on their file shares, they had no way of confirming that notion. With data residing in OneDrive and potentially across different SaaS solutions, the key to unlocking their data identification, classification and posture management challenges was in knowing where everything was.
The solution
Using Concentric AI’s Semantic Intelligence solution, TDECU was able to find sensitive data on its file stores using the agent they have on-premises.
Then, they were empowered to move on to finding data in OneDrive and different SaaS solutions.Â
Throughout the initial proof of concept (POC), the security team hit every single data category that they needed to identify.Â
From the customer
Results
With the ease of implementing the POC under their belt, TDECU’s deployment was up and running quickly. Between their on-prem and cloud environments, they had enough practical information to work by the second day of deployment. Â
With Concentric AI’s user-friendly dashboard, TDECU was finally where it wanted to be: they could clearly define where all their data lives, know how to identify risk to their data and remediate to match their requirements. Concentric AI’s Customer Success team adjusted the learning algorithms to better sync the data context in understanding labels for all their data. As they continue working with Concentric AI’s solution, the data risk monitoring process is improving as it learns.Â