Cogility’s Cogynt Decision Intelligence IRM Solution: Achieving an 11:1 ROI

Deploying a behavioral analytics platform like Cogynt is both mission-critical and cost-effective for modern Insider Risk Management (IRM). Beyond intangible benefits—such as enhanced insight and proactive incident avoidance, which can save upwards of $800,000 per incident—there are clear, quantifiable ROI advantages. Conservative estimates show that the Cogynt High-Fidelity/High-Automation solution delivers dramatic improvements in accuracy (17:1), efficiency (22:1), and overall cost reduction (11:1 for organizations with 100,000 personnel) compared to traditional manual approaches. This is achieved through continuous coverage and significant reductions in risk and full-time equivalent (FTE) requirements.

Insider threat is a persistent and growing risk, evidenced by high-profile cases and industry statistics. A 2024 Insider Threat Report found that a staggering 83% of organizations experienced at least one insider incident in 2024, and the average annual cost of dealing with insider risk has risen to over $17 million USD. A major challenge is the sheer volume of alerts that come into an Insider Risk Management (IRM) hub and the time it takes to manage them: The resulting backlog means that nearly 40% of IRM alerts go uninvestigated.

Cogynt is a streaming decision intelligence platform that provides continuous risk assessment, scalability, and configurability to accommodate a range of intelligence and decision support missions. Its patented Hierarchical Complex Event Processing (HCEP) solution implements an advanced expert AI behavioral analytic, enhanced with an integrated generative AI/LLM capability to increase the analyst’s understanding and provide more efficient and effective case management.

The benefits of Cogynt are characterized by its impact on the timing and quality of actionable intelligence, its proactive risk assessment capabilities, and comprehensive case management support. While precise quantitative ROI calculations require proprietary or sensitive data that are only available to the organization of concern, general cost-saving projections can be estimated for a hypothetical organization.

Resource Requirements

We estimated resource requirements for a hypothetical organization with 100,000 personnel by examining major risk categories of technical/user activity monitoring (UAM) risks and behavioral risks (mental illness, disgruntlement/disengagement, and financial stress). We used open source population statistics to estimate the expected frequencies of IRM alerts in each of these risk categories and then compared the expected impacts on IRM hub resources for a conventional, unaided Low-Fidelity/Low-Automation use case versus the advanced Cogynt High-Fidelity/High-Automation solution. Using published open source material that informs estimated base rates of “risk population events” per month—i.e., UAM/IT alerts and behavioral risk alerts comprising serious mental illness concerns, disgruntlement/disengagement, and financial stressors—we estimated that an organization with 100,000 personnel will produce roughly 60,000 UAM events and 900 behavioral events of concern per month that IRM hub analysts must address.

To support this analysis, we compare the labor hours required to triage and process these events. The triage activity determines which of these risk population events are of sufficient concern to be taken forward for risk assessment processing. In the Low-Fideity/Low-Automation use case, this analysis must be performed unaided. For the High-Fidelity/High-Automation use case (based on Cogynt), this triage activity is performed by Cogynt to substantially “shrink the haystack” and reduce the number of cases (and therefore the time required to assess them). The following rationale supports conservative estimates of the benefits of High-Fidelity/High-Automation:

• UAM Risk Assessment. For processing cases that reflect mainly UAM data, there is a huge benefit in automating the triage process that eliminates a large proportion (95%) of cases that would otherwise consume valuable analyst time—this shrinks the analyst’s backlog from 60,000 to 3000 cases for the Cogynt automated use case. For these cases that must be assessed, there is an additional benefit for the automated use case that slightly reduces the risk assessment time. Overall, this yields a substantial impact that reduces the FTE requirement from 439 FTE for the unaided use case to 19 FTE for the Cogynt High-Fidelity/High-Automation case—yielding a 23:1 benefit.
• Mental Health, Disgruntlement, and Financial Stress Risk Assessments. In these behavioral risk categories, we assume that there is a significant benefit in automating the triage process that eliminates 50% of cases that would otherwise consume valuable analyst time. This estimate is supported by recent research¹ that compared Cogynt’s triage output with expert judgments, revealing that Cogynt correctly identified essentially all cases deemed by experts to be of sufficient concern to justify detailed analysis versus those cases that were not considered worthy of further referral/study. Taking this finding at face value would even justify the assumption that the automated solution could eliminate nearly all but the most severe cases—i.e., 80-90% rather than 50%. We therefore consider the 50% triage benefit to be a conservative estimate. The automated triage support will have an impact of reducing the 900 behavioral risk events to 450 events per month; in addition, the automated use case is assumed to provide a 4:1 increase in analysis/assessment efficiency due to Cogynt’s HCEP and case management features. The result is that while the unaided use case requires more than 12 FTE IRM analysts to process the 900 behavioral risk events per month, the High-Fidelity/High-Automation Cogynt solution reduces the FTE requirement to 1.5. Thus, for the behavioral risk event assessment, there is a 8:1 benefit of the Cogynt support solution.

Cost Benefit Analysis

A significant benefit of the High-Fidelity/High-Automation Cogynt solution derives from the greater accuracy and efficiency afforded by its proactive, behavioral analytic approach that helps to avoid insider threat incidents. The associated cost avoidance advantage is substantial, given the increasing cost of remediating an insider threat incident (e.g., average cost of $715,366 USD for remediating a malicious insider incident according to the Poneman Insider Risk Global Report²).

Besides the cost avoidance provided by a more effective advanced technology solution that is more likely to proactively mitigate insider risks, we can derive an estimated cost comparison for the two alternative use cases based on differences in personnel resource costs. The large difference in FTE requirements more than makes up for the cost of deploying and maintaining the Cogynt software platform. For the Low-Fidelity/Low-Automation use case, the total FTE required to perform risk assessment for all four risk categories was 451. In contrast, the advanced Cogynt High-Fidelity/High-Automation solution requires just 20.5 FTE for the hypothetical organization with 100,000 personnel. The estimated annual cost for threat analysts, data scientists, and management for the Low-Fidelity/Low-Automation use case is $66,105,600. The Cogynt High-Fidelity/High-Automation solution has an associated annual staff cost of $3,456,000. For this solution, we must also include the annual cost of software and support for the Cogynt platform (figured based on a total organization size of 100,000): the cost of software and support is $2,460,000. The total cost for the Cogynt High-Fidelity/High-Automation use case is therefore $5,916,000. These results are summarized in Table 1, which indicates an overall 11:1 ROI benefit for the Cogynt High-Fidelity/High-Automation solution.

Table 1. Risk Reduction Summary – 100,000 Personnel

Conclusion

The deployment of a behavioral analytic platform like Cogynt is mission-critical and cost-effective for modern Insider Risk Management. Besides substantial intangible benefits that include enhanced insight and proactive opportunities for incidence avoidance that can save upwards of $800,000 per incident, there are definitive cost savings benefits that yield a ROI of 11:1 for a typical organization with 100,000 personnel. In addition to this significant ROI, the Cogynt High-Fidelity/High-Automation solution offers substantial efficiency and accuracy improvements for Insider Risk Management. By automating triage and assessment processes, organizations can dramatically reduce costs, analyst workload, and risk exposure, making Cogynt a strategic investment for large enterprises.

Interested in learning more? Read the Cogynt Behavioral Analytic Platform ROI Projection whitepaper.

References

1. F. L. Greitzer. Manuscript submitted for publication. From patterns to predictions: Insider risk modeling with a pattern-based behavioral analytic model
2. Poneman Institute. 2025. Cost of Insider Risks Global Report 2025. Poneman / DTEX. https://www2.dtexsystems.com/l/464342/2025-02-19/583csx/464342/1740000012hNhGjMpn/2025_Cost_of_Insider_Risks_Global_Report_by_Ponemon_and_DTEX.pdf