How generative AI helps mitigate outsider and insider threats for a major financial institution
August 25, 2023
The threat landscape is always evolving as attackers grow smarter and technologies become more advanced. To keep up, enterprise security postures must evolve alongside these ever-changing risks – especially if you’re a leading financial institution with over 200,000 employees.
“We are now a risk partner in everything we do,” a security leader from the organization said. “And when I think about my role today, it’s around risk: brand risk, reputational risk, the risk to our employees, assets and enterprise.”
So, how does this multinational organization protect against both outsider and insider threats? It starts with a converged security solution that’s rooted in AI technology.
Taking a proactive approach to security.
With generative AI, organizations can use physical security data to automate alarms, mitigate risks and create positive outcomes across the entire enterprise. And if a security operations center team is sifting through nearly 150,000 alarms to determine their relevance and significance, AI can save valuable time to stop crimes before they intensify.
Let’s look at a real-life example: by using AI-powered SOC Insights that identify patterns in the data, the same financial institution has recently identified criminal activities that SOC team members could initiate a police response 3-4 minutes before they’d normally receive an alarm.
This would potentially alleviate and reduce the costly impact of theft, vandalism – and compromised customer information and trust.
“Everything we do is reactive. But how could you be a little more proactive? The answer is that AI component.”
AI-powered protection from the inside out.
There’s plenty of talk about preventing malicious outside attacks – and for good reason, as indicated in the example above. But what about the threats lurking inside company walls?
According to recent data, 90% of organizations feel vulnerable to insider attacks (Insider Threat Report, Cybersecurity Insiders). Whether it’s a violent incident or theft of organizational data, these attackers know all the company intricacies and can act without triggering suspension. And if IT, OT, HR and physical security systems aren’t talking to each other, these insider crimes will continue to occur.
“Our HR systems are very private for a reason – it’s sensitive, personal data about all our individuals,” a security leader from the financial institution said. “But if something is called into our operations center, and I don’t know that there are eight other similar incidents because it’s stuck in an HR database, I’m not doing a comprehensive threat analysis.”
Imagine a full-time employee regularly using a company badge outside typical business hours. Maybe this same employee also has multiple complaints in a private HR file, a previous criminal record, or has publicly posted company criticism on social media. When analyzed separately, these events may not be a cause for concern. But together, they can be used to detect or predict malicious behavior.
And that’s where generative AI comes in; a converged, AI-powered security posture enables these systems to start sharing data and analyzing it for unusual activity and patterns that could indicate current or future wrongdoing. This helps protect company data, trade secrets, facilities and an organization’s most important asset: its people.
“Where we really need this AI technology is to help us cut through all this data and be able to focus on the threats that we have to take seriously.”