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The study is based on interviews with Deep Instinct customers, then the collected results are used by Forrester for constructing a financial model using its TEI methodology. A director of information technology in education who is a Deep Instinct customer participating in the study said, “Having Deep Instinct running on endpoints is like having a cybersecurity analyst doing the job 24/7.”

Deep Instinct reduces the likelihood of a cybersecurity breach, and saves significant time managing endpoints by using a proactive method of threat prevention, where most threats are stopped before reaching the execution stage, according to the commissioned study.

Following are some findings:

• 99% reduction in number of alerts as a consequence of eliminating false positives
• 90% reduction in alerts requiring manual investigation – attributable to Deep Instinct’s automated investigation and remediation capabilities
• 80% improvement in time spent on managing endpoint protection solution
• 15% reduction in the likelihood of a material data breach due to the broad attack surface protection
• Payback period in 3 months

“The Forrester financial model provides an excellent foundation for any organization to use as the basis for their own analysis when investing their options for cybersecurity solutions,” said Guy Caspi, CEO and co-founder of Deep Instinct. “We believe the independent study provides financial justification for investing in deep learning-based threat prevention to deal with the growing number of endpoint threats that are becoming increasingly sophisticated.”

“The use of Deep Instinct solution helped interviewed customers in eliminating false positives, resulting in a 99% reduction in the number of alerts received,” reported Forrester Consulting. “The interviewed customers saw a two-fold increase in the number of potential endpoint attacks when all employees transitioned to remote working due to COVID-19, all of which Deep Instinct solution was able to successfully prevent.”

Prior to using Deep Instinct, the customers’ organizations were using a combination of endpoint detection and response (EDR) solutions and endpoint protection platforms (EPPs), including antivirus or anti-malware software. While these solutions were somewhat effective in detecting and responding to known and some zero-day endpoint threats, security operations (SecOps) employees were often inundated with time-consuming manual processes, that stretched from endpoint management to alert investigation and threat hunting.

The deep learning technology – a form of artificial intelligence – was proven to more effectively block threats while reducing the number of false positives. The result is having to spend significantly less time investigating, responding and remediating threats. The impact is lowering the overall cost of operations and demonstrating excellent return on investment.