The foundation of all RQE API outputs — built on peer-reviewed methodologies, industry-standard frameworks, and real-world threat intelligence to deliver financial-grade risk quantification.
Our proprietary risk quantification algorithms combine statistical analysis with real-world threat intelligence to provide accurate, financial-grade risk assessments. We use probabilistic modeling to estimate both the likelihood and potential impact of cyber threats.
risk_score, likelihood, impact, cost_benefit.potential_loss
Comprehensive analysis of emerging cyber threats, attack vectors, and defensive strategies based on global threat landscape monitoring. Our intelligence feeds inform the category weights and severity multipliers used in risk calculations.
category, severity_multiplier, recommendations[]
Standardized approaches to risk quantification that comply with industry frameworks while providing actionable insights for security teams. Our methodology integrates multiple established standards into a unified risk model.
Factor Analysis of Information Risk
Cybersecurity Framework
Risk Management
Risk Rating Methodology
branch, branch_breakdown, weight_by_category
We work with security practitioners, risk managers, and academic researchers to continuously refine our models. Our collaboration network ensures that RQE stays aligned with real-world security operations and emerging threat patterns.
cost_benefit.mitigation_cost, cost_benefit.roi, timeline[]
RQE organizes risk into three primary branches, each mapping to specific Binary³ products and security domains.
Credential exposure, phishing susceptibility, authentication weaknesses
External attack surface, vulnerability exposure, network configuration
Detection coverage, log integrity, incident response readiness
Each branch contributes to the overall risk score. The API returns both individual branch scores and aggregated platform risk.
Embed our quantified risk methodology directly into your SaaS, dashboard, or automation pipeline.