John from IT downloads 200 customer files at 3 AM on a Sunday. Sarah from accounting suddenly accesses engineering documents she’s never needed before.
These kinds of random events are potential insider threats that could cost your company millions. While traditional security focuses on keeping outsiders out, the truth is that some of your biggest risks already have the keys to your kingdom.
That’s where modern solutions like KORTO are changing the game, using smart tech to spot the warning signs hiding in plain sight.
The silent threat from within
We’ve all heard the horror stories. The trusted employee who walked out with proprietary designs. The contractor who sold customer data on the dark web. The accidental leak that exposed sensitive financial information.
These insider incidents represent roughly a third of all data breaches. What makes them particularly dangerous is their stealth. Unlike hackers triggering alarms at the digital front door, insiders blend in with normal business activities until it’s too late.
Drowning in access logs
Most document systems faithfully record who touches what file and when. Great in theory, useless in practice. A mid-sized company generates millions of access events monthly. No security team on earth can manually review this tsunami of data.
It’s the classic needle-in-a-haystack problem, except the needle looks remarkably like hay until disaster strikes.
The human approach falls short because:
- Even dedicated teams can only sample a tiny fraction of activity
- People can’t possibly memorize normal patterns for hundreds of employees
- Subtle warning signs get lost in the noise
- By the time odd behavior becomes obvious, data’s already gone
The AI difference in document security
This is where advanced Electronic Document Management Systems (EDMS) with built-in AI capabilities are transforming security operations.
Here’s what they bring to the table:
They know what “Normal” looks like
The technology learns by watching. By analyzing months of document interactions, AI establishes individual digital fingerprints for each employee:
“Mary typically accesses marketing files weekdays between 9-5, rarely downloads more than 10 documents daily, and never accesses financial data.”
This baseline becomes the comparison point for spotting unusual activity.
They never miss a beat
Unlike humans who tire and cut corners, AI systems watch 24/7/365, comparing every single document interaction against expected patterns:
“Why is Mary suddenly downloading engineering schematics at midnight? Why is she accessing 50× her normal document volume? Why is she searching for terms related to upcoming merger activity?”
They see the whole picture
Context matters enormously. A good system remembers that:
- The finance team always pulls more reports during quarterly close
- Developers need broader access during release cycles
- The legal team digs through everything during litigation
- Regional managers download customer data before field visits
These legitimate pattern changes don’t trigger false alarms.
They focus on what matters most
Not all document access is created equal. Crown jewels like source code, customer data, and financial forecasts get extra scrutiny. The system weighs multiple risk factors to prioritize genuine concerns while filtering out noise.
Making it work in the real world
Financial institutions have been early adopters, with banking document management systems leading the charge. Their experience shows several practical considerations.
The technology needs quality data to work with, comprehensive logging with enough metadata to establish patterns. Privacy concerns require careful handling, especially in Europe under GDPR. And human judgment remains essential. The tech flags suspicious activity, but experienced security personnel make the final call.
