Concentric AI addresses data security needs with deep learning technology - The EE

Concentric AI addresses data security needs with deep learning technology

Concentric AI, a vendor of intelligent AI-based solutions for autonomous data security posture management (DSPM), has announced it is seeing significant customer traction in the financial services industry. The company addresses financial services organisations’ data security needs with deep learning technology that improves financial firms’ data access and activity governance with unparalleled contextual understanding of structured and unstructured financial data, wherever it’s stored on premises or in the cloud across various locations and branch offices.

Today financial services organisations face significant data security and access challenges protecting client personally identifiable information (PII), including bank account numbers and statements, credit card numbers and statements, and more. This is due to the vast amounts of PII stored on premises at various locations and branch offices and in the cloud, often with inappropriate and out-of-date access rights. In addition, financial organisations not only have their clients’ data to keep safe, but their own intellectual property to protect.

With Concentric AI, financial services organisations can with a single deployment address their regulatory and security requirements around protecting their most sensitive financial, operational and customer data. Concentric AI’s DSPM solution identifies any type of data that is accessible and assigns risk so financial organisations can ascertain the data type, who has access to it, whether it has the correct permissions, and if it has been shared appropriately inside or outside the organisation. Discovery of the data type and risk profile are critical to understanding risk, and Concentric AI can also autonomously remediate issues and programmatically remove any unauthorised access to prevent data loss.

For example, late last year a large credit union with 38 service locations and 34 member centres that serves more than 372,000 members deployed Concentric AI’s Semantic Intelligence platform to protect its own and members’ sensitive data on premises across locations and in the cloud. The credit union faced challenges around data classification, access and activity governance due to manual processes, and relying on the teams to input classification data. Today it benefits from Concentric AI’s DSPM solution for autonomous data discovery, classification, risk monitoring, and remediation.

“We had tried to roll out our data security posture management program multiple different times using different products,” states principal IT security architect at the credit union. “They all failed based on the fact that they were all using regular expressions as a way of detecting the different categories of data we had. It didn’t work. Concentric AI hit every single data category that we need to identify using AI, and that’s the real benefit of the product. By using machine learning to go in and figure out the context and content of the data, and then to monitor and protect that data that was absolutely spot-on and is working very well for us.”

Concentric AI has a long history of working with financial services organisations and helping them secure their data. Recent real-world incidents where Concentric AI helped remediate and protect data in financial environments include:

  • Risky sharing outside the company – An employee at a financial services firm shared sensitive finance intellectual property with a friend.
  • Risky sharing to personal email – The CFO at a financial services company needed access at home and she sent the confidential 2023 budget to her Gmail account.
  • Inappropriate classification – At another financial services firm, mortgage documents that were not classified were open to almost everyone in the IT department.

Concentric AI’s DSPM solution scans financial services organisations’ data, detects sensitive or business critical content, identifies the most appropriate classification category, and automatically tags the data. Concentric AI uses artificial intelligence (AI) to improve discovery and classification accuracy and efficiency to avoid endless regex rules and inaccurate end user labeling. In addition, Concentric AI can monitor and autonomously identify risk to financial and other data from inappropriate permissioning, wrong entitlements, risky sharing, and unauthorised access. It can automatically remediate permissions and sharing issues or leverage other security solutions and cloud APIs to quickly and continuously protect exposed data.

“We are seeing significant traction and interest in financial services, and are pleased to work with financial institutions of all sizes to address their data protection needs and improve their data security postures,” says Karthik Krishnan, founder and CEO, Concentric AI. “Few industries rely so heavily on customer loyalty like financial services customer trust means everything and if it’s lost, business suffers. Financial organisations turn to Concentric AI because our DSPM solution gives visibility into their sensitive data across datasets and locations, as well as a consolidated view into the risk associated with inconsistent access privileges, permissions, activity, and location to protect their data from loss.”

Concentric AI secures data-centric work using AI to protect business-critical financial information hidden in the millions of files and databases storing PII on premises across locations and in the cloud. The company’s deep learning solution autonomously and accurately finds sensitive content, assesses risk, and remediates security issues, allowing financial services organisations for the first time to fully meet their data security needs.

Concentric AI’s Semantic Intelligence automates unstructured and structured data security using deep learning to categorise data, uncover business criticality and reduce risk. Its Risk Distance analysis technology uses the baseline security practices observed for each data category to spot security anomalies in individual files. It compares documents of the same type to identify risk from oversharing, third-party access, wrong location, or misclassification. Financial organisations benefit from the expertise of content owners without intrusive classification mandates, with no rules, regex, or policy maintenance needed.

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