Two employees fail a phishing simulation. Are they an equal threat to your organization? If you only track behavior, you might think so. But if one is an intern with limited permissions and the other is a domain administrator with privileged access, the context changes everything. This is the critical flaw in security metrics that lack context. To prioritize threats effectively, you need to understand potential impact, not just activity. This is where human risk score benchmarks become transformative. A meaningful score must correlate behavioral signals with identity and access data, as well as real-time threat intelligence. This correlated, data-driven approach is the core of modern Human Risk Management (HRM) and allows you to focus your resources where they will have the greatest impact.
Think of a human risk score as a dynamic number that quantifies the likelihood of an individual causing a security incident. It’s not a judgment on character, but a data-driven assessment of risk based on observable actions and context. A low score indicates safe habits, while a high score signals that an employee might need guidance to make more secure decisions. This approach moves security from a reactive guessing game to a proactive, predictive strategy.
To be truly effective, a risk score can't rely on a single data point. A comprehensive score is calculated by correlating signals from multiple sources. At Living Security, our leading Human Risk Management platform analyzes over 200 indicators across three critical pillars: employee behavior, identity and access systems, and real-time threat intelligence. By looking at who has access to sensitive data, how they are being targeted by attackers, and how they behave day-to-day, you get a complete and actionable picture of your organization's human risk. This allows you to see risk before it leads to an incident.
With human error contributing to the vast majority of security breaches, simply hoping your employees do the right thing is no longer a viable strategy. Human risk scores matter because they make an invisible threat visible and measurable. According to recent cybersecurity insights, this human element is the single largest attack surface in any organization.
For enterprise security teams, scores provide the clarity needed to focus limited resources where they will have the greatest impact. Instead of deploying generic, one-size-fits-all training, you can identify specific individuals or groups with elevated risk. This allows you to deliver targeted interventions, like personalized coaching or policy reminders, directly to the people who need them most, dramatically improving your security posture and operational efficiency.
Traditional security metrics often focus on activity, not outcomes. For example, achieving a 100% completion rate on an annual training module tells you that your employees checked a box, but it doesn't tell you if they actually learned anything or changed their behavior. This is where human risk scores create a fundamental shift.
Unlike legacy metrics, a human risk score evaluates whether employees are making safer decisions in their daily work. It’s a continuous measure of applied knowledge, not a point-in-time snapshot of compliance. This approach moves beyond basic security awareness and training to a model of constant observation and reinforcement, where you can see if your security program is truly reducing risk over time.
Calculating a human risk score isn't about assigning a simple grade based on training completion. A meaningful score quantifies the likelihood that an individual will cause a security incident, and it requires a data-driven approach. Instead of relying on a single metric, an effective calculation correlates signals from three distinct pillars: employee behavior, identity and access levels, and external threat intelligence. By weaving these data streams together, you can move beyond guesswork and create a dynamic, measurable view of your organization's human risk surface.
The leading Human Risk Management Platform from Living Security was built on this principle. It analyzes hundreds of indicators across these three core areas to generate a predictive risk score. This score doesn't just tell you who failed a phishing test; it shows you who is most likely to introduce risk in the future, allowing you to act before an incident occurs. This method transforms risk scoring from a reactive report card into a proactive security tool that guides targeted interventions and strengthens your overall defense posture.
The first step in calculating a risk score is to understand what your employees are actually doing. Analyzing behavioral signals means looking at the actions people take every day, both positive and negative. This includes everything from clicking on simulated phishing links and using unauthorized applications to reporting suspicious emails and completing security training modules. These behaviors provide the foundational data for understanding risk patterns within your organization.
However, simply collecting this data isn't enough. You need to identify which behaviors are most indicative of risk. Research from the 2025 Human Risk Report shows that a small fraction of employees, just 10%, are responsible for 73% of all risky behavior. By analyzing a broad set of behavioral signals, you can pinpoint this high-risk group and focus your resources where they will have the greatest impact, rather than applying generic training to your entire workforce.
Behavioral data tells you what is happening, but identity and access data tells you how much it matters. A risky action from an employee with limited system access carries a fraction of the potential impact as the same action from a privileged user or executive. To accurately calculate risk, you must correlate behavioral signals with data from your identity and access management (IAM) systems. This context is critical for prioritizing threats.
For example, an employee who frequently fails phishing tests is a concern. But if that same employee is a domain administrator with keys to your most critical systems, that concern becomes an urgent priority. The Living Security platform integrates directly with these systems to connect behavior to access levels. This correlation allows you to see not just who is acting insecurely, but who has the power to cause significant damage if their risky behavior leads to a compromise.
The final piece of the puzzle is understanding the external threat landscape. Are specific employees or departments being actively targeted by attackers? Whose credentials have been exposed in a third-party breach and are for sale on the dark web? Integrating real-time threat intelligence provides this essential context, showing you where external pressure is being applied to your organization. This allows you to see risk from an attacker's perspective.
A comprehensive risk score must account for this external reality. An employee might have perfect security behavior and limited access, but if they are being relentlessly targeted by a sophisticated phishing campaign, their risk profile changes. By integrating threat intelligence, you can identify individuals who are at high risk through no fault of their own. This enables you to provide them with extra support, such as targeted phishing awareness training or heightened monitoring, before attackers succeed.
Relying on any single data stream gives you an incomplete and often misleading picture of human risk. Behavior without access context creates noise, making it impossible to prioritize. Access without behavior identifies static potential for harm but misses active threats. Both without threat intelligence ignore the external forces actively working against you. True risk visibility only emerges when you correlate all three signals: behavior, identity, and threat.
This correlated approach is what separates modern Human Risk Management from legacy security awareness. As recognized in the Forrester Wave™ report, leading platforms can predict which combination of factors is most likely to result in an incident. By combining information about who is behaving riskily, who has elevated access, and who is being targeted, you can create a precise, predictive risk score that enables you to act decisively to prevent breaches.
To effectively manage human risk, you need to measure it. But relying on a single data point, like phishing clicks, only tells a fraction of the story. A truly data-driven Human Risk Management (HRM) program requires a holistic view built on multiple key metrics. These benchmarks make risk visible and quantifiable, allowing you to move from reactive awareness campaigns to proactive, targeted interventions. By tracking the right indicators, you can identify your most vulnerable areas, measure the impact of your security initiatives, and demonstrate clear risk reduction to leadership.
The most effective approach involves correlating signals across different data pillars: employee behavior, identity and access systems, and real-time threat intelligence. For example, an employee who repeatedly fails phishing tests is a concern. But an employee who fails phishing tests, has privileged access to critical systems, and is actively being targeted by threat actors represents a much more urgent risk. The leading Human Risk Management Platform from Living Security is built to analyze these interconnected signals, giving you a comprehensive and actionable understanding of your risk landscape. By focusing on these core metrics, you can establish a baseline, set meaningful goals, and build a resilient security culture.
Since more than 95% of successful cyberattacks involve a human element, phishing susceptibility is a foundational metric for any HRM program. This metric typically measures the percentage of employees who click on malicious links or engage with simulated phishing emails. While a low click rate is the goal, the real value comes from understanding who is clicking and why. Targeted phishing simulations can help identify high-risk individuals and departments, and focused training can lower their click rates by up to 25%. Tracking this metric over time provides a clear indicator of your organization's vulnerability to social engineering and the effectiveness of your initial awareness efforts.
Simply tracking whether employees complete their annual security training is a vanity metric. True risk reduction comes from behavioral change, not just checking a compliance box. Instead of focusing only on completion rates, measure how training impacts behavior. Are employees who complete specific modules less likely to click on related phishing simulations? Do they report suspicious emails more frequently? Effective security awareness and training should be adaptive and tied to specific risks. By analyzing engagement alongside other risk signals, you can determine if your training is actually working and pivot your strategy to focus on interventions that drive measurable change.
Shadow IT, which is the use of unauthorized applications and tools at work, creates significant blind spots for security teams. When employees use personal cloud storage or unapproved project management apps, they move sensitive data outside of your organization's security controls. Analyzing data points related to this behavior is crucial for understanding your true risk surface. A comprehensive HRM platform can help identify this activity by correlating endpoint data with network traffic and other behavioral signals. This metric not only highlights individual risky habits but also points to potential gaps in your sanctioned toolset that may need to be addressed.
An employee’s risk isn't just defined by their actions, but also by their level of access and exposure. This metric combines internal and external data to create a more complete picture. For instance, if an employee's credentials are found on the dark web, their risk score should remain elevated until their passwords are changed and their accounts are secured. This should be cross-referenced with their access privileges. An exposed password for a standard user is a problem, but for a system administrator, it's a critical threat. Effective Human Risk Management requires you to continuously monitor for credential exposure and correlate it with identity data to prioritize your response.
While you want to see phishing click rates go down, you want to see incident reporting rates go up. This metric measures the number of employees who report a suspicious email or potential security event, turning your workforce into an active line of defense. A high reporting rate is a strong indicator of a healthy security culture where employees feel empowered and responsible for protecting the organization. Tracking this positive behavior is just as important as tracking negative actions. You can find more data-driven insights on this and other key behaviors in the latest Cyentia Institute report on human risk.
Tracking how often employees violate internal security policies is essential for maintaining compliance and protecting sensitive data. This metric can include everything from mishandling confidential information and using unauthorized USB drives to failing to follow clean desk policies. Monitoring policy violations helps you identify individuals or departments that may require additional training or reinforced guidance. For GRC teams, this data is invaluable for proving due diligence and ensuring the organization adheres to regulatory requirements like GDPR, HIPAA, or PCI DSS. It provides a clear, evidence-based way to manage compliance risk with targeted solutions.
Understanding how your organization’s human risk stacks up against industry peers provides critical context for your security strategy. Benchmarks are not just about seeing who is “best” or “worst”; they are about gaining an objective measure of your performance to identify strengths and prioritize areas for improvement. However, risk is not uniform across the business landscape. Industries like finance and healthcare face different threat models than manufacturing or retail, and their risk profiles reflect that reality.
A comprehensive approach to benchmarking requires looking beyond simple behavioral metrics. To truly understand your position, you must correlate data across employee behavior, identity and access systems, and real-time threat intelligence. This is the foundation of a modern Human Risk Management (HRM) program. By analyzing these interconnected signals, you can move past generic comparisons and gain a precise, contextualized view of your risk posture. This data-driven clarity helps you answer key questions: Are we being targeted more than our peers? Do our employees have more privileged access than is typical for our sector? Answering these questions is the first step toward building a more resilient security culture.
Certain industries consistently emerge as high-risk due to the nature of their data, regulatory environments, and attractiveness to threat actors. Sectors like finance, healthcare, and technology are prime targets because they manage vast amounts of sensitive personal and financial information. According to security research, industry intelligence can provide estimated organizational benchmarks for comparative analysis, but these are based on broad threat landscape patterns.
The drivers behind this elevated risk are multifaceted. For example, healthcare organizations must contend with strict HIPAA compliance, while financial institutions face sophisticated state-sponsored attackers. These external pressures, combined with complex internal IT environments, create a challenging risk landscape. While industry benchmarks offer a valuable starting point, they are only estimates. True risk visibility comes from analyzing your organization’s unique combination of behavioral, identity, and threat data with a platform like the one offered by Living Security.
There is no single number that defines a "good" human risk benchmark. The definition of success is highly contextual and varies significantly across sectors. As one guide notes, benchmarking against industry peers provides an objective measure of your performance and is a powerful tool for identifying areas for improvement. For a highly targeted financial services firm, a 10% phishing simulation click rate might be a significant achievement, while the same rate could be a red flag for a manufacturing company facing fewer targeted threats.
Instead of chasing a universal score, the goal should be continuous, measurable improvement. A "good" benchmark is one that trends downward over time as your HRM program matures. The Human Risk Management Maturity Model helps organizations chart this course, moving from basic awareness activities to a predictive, data-driven security posture.
The Pareto principle, or the 80/20 rule, applies directly to human risk: a small group of individuals is often responsible for a disproportionate amount of risky activity. In fact, research from the 2025 Human Risk Report by Living Security and the Cyentia Institute found that just 10% of employees are responsible for 73% of all risky behaviors. This finding, drawn from over 200 behavioral signals across more than 100 organizations, underscores the inefficiency of generic, one-size-fits-all security training.
This concentration of risk highlights the critical need for targeted interventions. Instead of burdening the entire workforce with the same training, security teams can achieve far greater results by focusing their efforts on the small population of high-risk individuals. An AI-native HRM platform can automatically identify these employees by analyzing risk signals and then orchestrate personalized nudges, micro-trainings, or policy reminders to guide them toward safer habits.
Not all risky behaviors are created equal. The impact of a security mistake is magnified exponentially when it comes from an employee with privileged access. As Mimecast notes, risky behavior from someone with high access is much more dangerous than from someone with less access. A single compromised administrator account can lead to a catastrophic breach, while a similar mistake from an intern with limited permissions may have minimal impact. This is why access levels are a critical variable that can skew benchmarks.
An effective HRM program must weigh risk scores by the level of access an individual possesses. Simply identifying a risky employee is not enough; you must prioritize interventions based on their potential to cause harm. This requires a platform that can correlate behavioral signals with identity and access data from systems like your identity provider. By focusing on high-risk individuals with high levels of access, you can allocate resources efficiently and prevent the most damaging incidents before they happen.
Moving from abstract awareness to measurable outcomes requires a structured approach. Establishing your own human risk benchmarks is the foundational process for making risk visible, quantifiable, and actionable within your organization. It’s how you create a data-driven narrative that security leaders can use to prioritize resources, justify investments, and demonstrate progress to the board. Instead of relying on generic industry averages, creating custom benchmarks allows you to build a program that reflects your organization’s unique risk landscape, compliance needs, and security culture. The following steps outline how to build this framework from the ground up, transforming your Human Risk Management program from a reactive checklist to a proactive, predictive security function. By following this process, you can create a clear, defensible standard for what "good" looks like in your specific environment.
You cannot improve what you do not measure. The first step is to establish a comprehensive risk baseline by quantifying the current state of human risk across your organization. This involves more than just tracking training completion. A true baseline requires correlating data from multiple sources to get a complete picture. By analyzing signals across employee behavior, identity and access systems, and real-time threat intelligence, you can assign a quantifiable risk score to individuals and groups. This initial assessment provides a critical starting point, a "before" snapshot that allows you to measure the effectiveness of your interventions and demonstrate a clear return on your security investment over time.
A single, company-wide risk benchmark is not enough. To be effective, your benchmarks must be segmented to reflect the diverse roles and access levels within your enterprise. An engineer with privileged access to critical infrastructure has a fundamentally different risk profile than an employee in the marketing department. By segmenting your benchmarks by role, team, and access privileges, you can understand how different groups contribute to your overall risk posture. This granular view is a powerful tool for moving beyond one-size-fits-all training and implementing targeted, context-aware solutions that address the specific risks relevant to each group.
Benchmarks are only valuable if they drive action. Once you have established your baseline and segmented it appropriately, the next step is to define risk thresholds that automatically trigger specific interventions. When an individual or group crosses a predefined threshold, it should prompt a targeted response. This could be an automated enrollment in a specific micro-training module, a contextual nudge reinforcing a security policy, or a notification to a manager. The goal is not to be punitive but to provide the right support at the right time. This approach allows you to scale your security awareness and training efforts efficiently, focusing your resources on the areas of greatest need.
Your human risk benchmarks are more than just internal metrics; they are essential evidence for your Governance, Risk, and Compliance (GRC) program. By correlating behavioral data with identity and threat intelligence, you can effectively measure and manage your human risk surface in a way that is both auditable and defensible. These benchmarks provide tangible proof to regulators, auditors, and insurers that your organization is proactively managing human-driven risk. Aligning your benchmarks with frameworks like NIST or ISO helps translate security actions into a language that resonates with GRC teams and executive leadership, making human risk a core component of your overall compliance strategy.
After establishing internal benchmarks, the final step is to contextualize your data by comparing it against industry peers. This external validation helps you answer a critical question: "How are we really doing?" A high phishing simulation failure rate might seem alarming on its own, but if it is significantly lower than your industry's average, it tells a more positive story. The 2025 Human Risk Report shows that peer benchmarks provide an objective measure of performance, helping you set realistic goals and communicate your security posture to leadership with greater confidence. This context is invaluable for justifying security budgets and proving the maturity of your Human Risk Management program.
A human risk score is not a simple grade on a report card. It’s a dynamic measurement that reflects the complex interplay between individual actions, system permissions, and the external threat environment. To be truly effective, a risk score must move beyond tracking single behaviors, like phishing clicks, and instead provide a holistic view. The most accurate scores are influenced by a wide range of factors, from an employee’s role and access level to the sophistication of threats targeting your organization. Understanding these variables is the first step toward creating meaningful benchmarks that drive proactive security measures.
A strong security culture is your organization's first line of defense, but its effectiveness can be difficult to quantify with traditional metrics. Human risk scoring offers a way to measure culture through action, not just awareness. It quantifies the likelihood an employee will cause an incident based on their actual behaviors, not just their training completion records. For example, does an employee consistently report suspicious emails, or do they frequently click on simulated phishing links? A Human Risk Management platform analyzes these behavioral signals to provide a clear picture of your organization's security posture, helping you see where your culture is strong and where targeted interventions are needed to reinforce secure habits.
Not all employees represent the same level of risk. An executive with access to confidential financial data or a system administrator with broad permissions poses a much greater potential impact if compromised than an entry-level employee. This is why a person's risk score must account for their access levels and identity exposure. Analyzing how often specific employees are targeted and what systems they can access provides critical context. By correlating behavioral data with identity and access information, security teams can prioritize interventions for individuals who represent the highest potential impact, ensuring resources are focused where they matter most. This approach provides tailored security solutions for every level of your organization.
Human risk is not created in a vacuum; it is heavily influenced by the external threat landscape. If a specific department is under constant attack from sophisticated phishing campaigns, its collective risk score will naturally be higher. New threats, especially those created with AI, are becoming exceptionally good at tricking even savvy employees. An effective risk score must therefore integrate real-time threat intelligence. Understanding the volume, type, and targets of external attacks allows you to see risk from an attacker's perspective. The Living Security platform achieves this by correlating threat data with behavior and identity signals, giving you a predictive view of where the next incident is most likely to occur.
The definition of "human risk" is expanding to include non-human actors. AI agents, scripts, and other automated tools are now integral to business operations, but they also introduce a new and complex risk variable. These agents can be compromised, manipulated, or used to execute attacks with unprecedented speed and scale. For example, AI can be used to create highly personalized fake attacks that are difficult for employees to spot. A forward-looking Human Risk Management strategy must provide visibility into the actions of these AI agents, monitoring their access and behavior just as you would a human employee to manage the growing intersection of human and machine-driven risk.
Establishing benchmarks is a critical step in making human risk measurable, but it’s easy to get it wrong. A flawed benchmarking strategy can give you a false sense of security or, worse, lead you to focus on the wrong problems. To build a truly effective Human Risk Management (HRM) program, you need to be aware of the common traps that can undermine your efforts. Avoiding these pitfalls ensures your data is accurate, your interventions are effective, and your security culture remains positive and proactive. Here are four of the most common mistakes organizations make when benchmarking human risk.
A human risk score based only on phishing click rates or training completion is an incomplete picture. To truly understand risk, you need to collect and correlate data from multiple sources. A narrow view misses the critical context provided by a person’s access level or the real-time threats targeting them. The leading Human Risk Management platform from Living Security avoids this by design, analyzing over 200 signals across employee behavior, identity and access systems, and threat intelligence feeds. This comprehensive approach moves beyond simple behavioral metrics to provide a holistic and actionable view of risk, showing you not just what is happening but why it matters to your organization’s security posture.
Human risk is not a fixed number you calculate once a year. It’s a dynamic metric that changes as threats evolve, roles shift, and new technologies are introduced. Treating benchmarks as static, point-in-time assessments means you’re always looking in the rearview mirror. A modern approach to Human Risk Management requires continuous measurement to quantify risk based on actual, evolving behaviors. By monitoring risk trajectories in real time, you can move from a reactive stance to a predictive one, identifying and addressing risks before they escalate into incidents. This allows you to adapt your security controls and interventions as your organization and the threat landscape change.
Not all risky behaviors are created equal. A moment of carelessness from an intern has a much different potential impact than the same mistake from a system administrator with privileged access to critical infrastructure. Prioritizing individuals based on behavior alone is a critical error. As experts note, risky behavior from someone with high access is far more dangerous. That’s why it’s essential to correlate behavioral data with identity and access information. This allows you to focus your limited resources on the individuals who pose the greatest potential threat to the organization, ensuring your interventions deliver the biggest impact on your overall security.
The goal of measuring human risk should never be to name and shame employees. Assigning risk labels without a supportive framework can quickly create a culture of fear and blame, where people hide their mistakes instead of reporting them. This is counterproductive to building a strong security posture. An effective program uses risk data to guide, not punish. By delivering personalized, supportive interventions like targeted phishing simulations and just-in-time micro-training, you can empower employees to become active partners in security. This approach fosters a positive security culture where everyone feels responsible for protecting the organization, turning your workforce into your strongest defense.
Establishing benchmarks is just the beginning. The real value of a Human Risk Management (HRM) program comes from using those benchmarks to drive continuous improvement. A static score is a snapshot in time, but human risk is dynamic. To effectively reduce incidents, security leaders need a living, breathing view of their risk landscape, coupled with the ability to act on that intelligence in real time. This means moving beyond annual reports and toward a proactive cycle of monitoring, intervening, and adapting. The goal is to create a security culture that is both aware and resilient, where risk reduction is an ongoing process, not a one-time event.
The leading Human Risk Management Platform from Living Security is built for this continuous motion, helping you predict and prevent incidents before they happen. By correlating data across the three critical pillars of behavior, identity, and threats, you can create a system that not only measures risk but actively works to reduce it. This holistic approach provides the context needed to understand not just what is happening, but why, enabling more precise and effective security strategies. It transforms risk management from a reactive checklist into a proactive, data-driven function that strengthens your entire security posture.
Traditional risk scores offer a static picture, but your organization’s risk is constantly in motion. A truly effective strategy requires a continuous measurement methodology that shows you not just where risk is now, but where it’s headed. Instead of a single score, you should be tracking risk trajectories. By analyzing hundreds of signals across employee behavior, identity and access systems, and real-time threat intelligence, you can quantify the likelihood of an incident based on actual behaviors, not just training records. This approach allows you to measure and manage your human risk surface effectively, spotting negative trends before they lead to a breach and giving you the foresight to intervene proactively.
Identifying a rising risk score is one thing; correcting the behavior is another. The most effective interventions are delivered in the moment of need. When an employee’s risk trajectory changes, an automated system can immediately assign a short, targeted training module or a policy reminder. This “just-in-time” learning is far more effective than generic annual training. Living Security’s AI-native platform uses Livvy, an AI guide, to orchestrate these actions autonomously, delivering personalized nudges and microlearning to reinforce secure habits. This automation frees up your security team to focus on high-level strategy, while human-in-the-loop oversight ensures you always maintain final control over critical decisions and actions.
The threat landscape is not static, and neither are your benchmarks. What constitutes a “good” score today may be insufficient tomorrow. It’s critical to regularly adapt your benchmarks based on evolving external threats and internal changes within your organization. Benchmarking human risk against industry peers provides an objective measure of your performance and helps contextualize your posture. As new attack vectors emerge or as your company adopts new technologies like AI agents, your risk models must evolve. A forward-looking HRM program continuously ingests new intelligence to refine its benchmarks, ensuring your security controls remain aligned with the real-world risks your organization faces.
An effective Human Risk Management (HRM) program starts with a data-driven foundation that makes risk visible, measurable, and actionable. Before you can implement targeted security controls, you first need to assess your organization's overall cyber risk exposure. This is where benchmarking comes in. It provides the objective data you need to understand your current security posture, identify critical gaps, and set a clear path for improvement. Without benchmarks, you’re essentially flying blind, unable to prove the value of your security initiatives or prioritize your efforts effectively.
Once you have a baseline, you can begin to contextualize your data by comparing it against industry peers. Using authoritative industry intelligence for comparative analysis helps you understand how your organization stacks up. Are your phishing susceptibility rates higher than average for your sector? Is your policy violation frequency on par with similar-sized companies? Answering these questions provides an objective measure of your performance and gives you the evidence needed to secure executive buy-in for new security investments. This data transforms security from a cost center into a strategic, measurable business function.
This benchmark-driven approach allows you to focus your resources where they will have the greatest impact. Research from Living Security's 2025 Human Risk Report found that a small fraction of employees are responsible for the vast majority of risky behaviors. Instead of deploying generic, one-size-fits-all training, you can use benchmarks to identify high-risk individuals and groups, then deliver targeted interventions that directly address their specific behaviors. This targeted strategy is not only more efficient but also far more effective at changing behavior and reducing your overall risk profile.
Ultimately, building a benchmark-driven program transforms your approach from reactive to proactive. It shifts the focus from simply measuring risk to actively managing it through a continuous cycle of assessment, intervention, and improvement. By integrating this methodology, you can move beyond traditional security awareness programs and build a resilient security culture. The leading Human Risk Management Platform provides the tools to not only establish these benchmarks but also to automate the interventions needed to see measurable improvement over time.
How is a human risk score different from just tracking phishing clicks? Think of tracking phishing clicks as looking at a single symptom, while a human risk score is like getting a full diagnostic report. A phishing metric tells you one specific thing, but a comprehensive risk score provides a much richer, more predictive picture. It achieves this by correlating behavioral data, like phishing susceptibility, with two other critical data pillars: identity and access information, and real-time threat intelligence. This allows you to see not just who clicked a link, but how much it matters based on their system access and whether they are being actively targeted by attackers.
My team is already overwhelmed. How does this approach make our jobs easier instead of just adding more data? This is a great question because the goal of a modern Human Risk Management (HRM) program is to reduce noise, not create more of it. Instead of drowning you in alerts, a platform like the one from Living Security, a leader in Human Risk Management (HRM), uses AI to analyze risk signals and surface only the most critical priorities. It pinpoints the small group of individuals driving the most risk and can even automate routine interventions like assigning targeted micro-training. This frees your team from chasing down low-level alerts and allows you to focus your expertise on high-impact strategic initiatives.
Is there a universal "good" human risk score we should aim for? There isn't a single magic number that defines a "good" score for every organization. The context of your industry, company size, and the specific threats you face all influence what a healthy benchmark looks like. A financial institution under constant attack will have a different baseline than a manufacturing company. The most important goal is to establish your own internal baseline and then focus on demonstrating continuous improvement. A "good" program is one where you can show risk scores trending downward over time as a direct result of your targeted security efforts.
What's the most important first step to start benchmarking our human risk? The most critical first step is to establish a comprehensive risk baseline. You can't measure improvement if you don't know your starting point. This involves collecting and correlating data across employee behavior, identity and access systems, and external threat intelligence to create an initial, quantifiable snapshot of your risk posture. This baseline becomes the foundation for everything that follows, allowing you to set realistic goals, measure the effectiveness of your interventions, and clearly demonstrate risk reduction to leadership.
How does Human Risk Management account for non-human actors like AI agents? This is a key consideration as workplaces evolve. The principles of HRM are now being extended to monitor non-human actors like AI agents and automated scripts. Just like a human employee, these agents have access to systems and can exhibit behaviors that introduce risk. An advanced HRM platform provides visibility into these agents by monitoring their activity and access levels alongside human users. This helps you manage the growing intersection of human and machine-driven risk, ensuring you have a complete picture of your security landscape.