Data protection and auditing for financial services
In 2021, the average cost of a data breach in the financial sector was $5.72 million. Today, firms must protect financial records, customer Personally Identifiable Information (PII), source code, trading models, actuarial tables, and a wide variety of intellectual property.
Cyberhaven automatically finds and classifies all sensitive data without manual classification or tagging, and every user’s data action is tracked and analyzed for risk.
Problems we solve
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Automatically find all types of high-value data.
Data deemed sensitive is unique to each business unit. Whether a client’s financial records, proprietary market research, or algorithmic trading models, Cyberhaven finds it and tracks where it moves.
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Find risk across the lifecycle of your data.
Track the who, how, and when of every data action to find risky users and actions before data is leaked. Is a client’s trade history file being sent to an employee’s personal email? Cyberhaven tells you.
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Protect data while educating your staff.
Go beyond simple block/allow decisions to ensure traders, analysts, CSRs, and staff remain productive while also being trained to reduce risk. You have the flexibility to block or educate depending on the situation.
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Sample data flow
The scenario
Jenny, a data scientist, was offered a new job and wanted to impress her new employer by using her current employer’s algorithmic trading model to kick-start a new project. She checked out the algorithm from GitHub, archived the code in a zip file, added a password, and renamed it. She then uploaded the file to her personal Google Drive account.
Cyberhaven solution
Cyberhaven detected exfiltration of source code to personal cloud storage. The data was traced when Jenny checked it out from GitHub and archived, encrypted, and renamed it. When she tried uploading the file to Google Drive, Cyberhaven knew the file contained proprietary code from a private repository and raised an alarm.