Data X-Ray Carves Out Regulated Data to Prepare a Bank for an M&A Divestiture
A large global bank recently used Data X-Ray to understand and secure their unstructured data during a M&A divestiture deal.
- Type: Product Insights
- Date: 30/11/2022
- Author: Kyle DuPont
- Tags: Unstructured Data, data discovery, Data Governance, Data protection
In February 2022, in the midst of a divestiture, the head of privacy and governance at a very large global bank had as his remit the task to sift through almost 20 million files in time for the divestiture deadline. The task at hand was to scan, classify, index, report on this data, and understand if that data should stay with the SellCo or go to the PurchaseCo.
This daunting, time-consuming task could take years to complete manually, which was not acceptable given the tight deadlines. Not having clarity of the unstructured data was not an option as it could easily lead to regulatory issues regarding anti-money laundering investigations and confidential regulatory correspondence. Given the deadlines, he needed to implement an automated solution to discover and classify sensitive data within his data estate.
Reimagining unstructured data analysis for divestiture data carve outs
“The requirement was to ensure that we migrate customer data in a governed, audited way. We needed to scan all SharePoint sites for relevant data. Our regulators had eyes on the migration process, so not knowing what data is sensitive from a regulatory standpoint was a key concern to make the divestiture happen”, noted the head of privacy and governance.
Knowing the file owners, what each file contained from a regulatory standpoint, and whether it should be carved out for the divestiture was the primary concern. Time was another concern as this needed to be completed before the divestiture legal day 1 deadline.
“Data X-Ray gave us the ability to scan unstructured data files at scale and enabled us to recognize which files should stay and which files should go.”
Data X-Ray enables understanding of unstructured data at scale
“We’ve seen unstructured data become a major problem to manage. It’s not only growing at an exponential rate but manual review of unstructured data at scale is simply an intractable problem for humans to solve as files can change literally every second. And, this is where we wanted to help,” said Kyle DuPont, Co-Founder and CEO, Ohalo. “We’ve built Data X-Ray to solve the unstructured data challenge for large enterprises. It scales linearly and can scan 100,000s of words per second with even the smallest servers. So, what could typically take months or even years to process can now be completed in hours and days.”
At the bank, the Ohalo team stood up an infrastructure which put Data X-Ray to work immediately. It scanned, discovered, and classified sensitive data from over 100 million unstructured data files. Data X-Ray’s modular system architecture was extremely beneficial, as it offered the flexibility and scalability that was needed in a hybrid cloud architecture.
“We estimated two months to remotely scan, classify, index and report on all the millions of files present on the identified Sharepoint sites, including set up on the client end,” said Alistair Jones, Co-Founder and CTO, Ohalo. “The team created a scan strategy, new labels to ensure data discoverability and visibility and set up automated notification triggers. We also produced an index of metadata which enabled the final retention and disposition actions on the records.”
Reducing cost and enabling regulatory approval
“Data X-Ray is effective and accurate, but more importantly it has helped us implement a process to understand our unstructured data, reduce our regulatory risk, and ultimately simplify data migration to the purchasing entity,” said the head of privacy and governance. “By dispositioning data in an automated fashion, Data X-Ray solved our regulatory issues around data governance to get sign off from our regulators.”
Three advantages of implementing Data X-Ray
Data X-Ray uses a combination of machine learning, regular expressions, and dictionaries to accurately identify sensitive information like regulatory keywords, personal data, PCI data, and more. It offers deep data intelligence and context around sensitive data, and provides audit trails of what is processed, showcasing data governance improvements.
Auto discovery can be scheduled or run on-demand. A single enterprise-wide classification framework can be created across multiple environments, categorizing information held according to sensitivity and confidentiality. Metadata generated by Data X-Ray can be easily integrated with leading data catalogs, retention management, data visualization, and other collaboration tools.
An unstructured data report, summarizing findings in the order of risk can help prioritize remediation efforts. This speeds compliance, provides an auditable trail of actions taken, and increases the security stance of clients.
“Post this divestiture, we decided to deploy Data X-Ray across the firm for our personal information governance program. I believe it will be key to the future of our data governance efforts.” said the head of privacy and governance. “It will help transform us into a firm with a modern and automated data governance framework.”
“The dangers of unstructured data during a divestiture or M&A deal can be painful, making data discovery a vital step for businesses looking to acquire or merge with other organizations. But finding the hidden data and then securing it doesn’t have to be a challenge. We can help reveal what sits in your data estate, both on-premise and on cloud, and help take action to secure it,” said Alistair Jones, Co-Founder and CTO, Ohalo.
If confidential, hidden data is discovered post-merger, you may find yourself becoming the next negative news story or worse, regulatory blowback. So, take action. Take a new approach to due diligence and data carve outs.