Infrastructure for Cyber Risk Assessment for Commercial Lines

Cyber risk assessment requires explicit documentation of which security controls reduce the risk score, what vulnerability thresholds trigger coverage restrictions or exclusions, and how breach history maps to pricing adjustments. The cyber threat landscape evolves rapidly—documented guidelines must be current and findable, not locked with specialist underwriters. State regulators increasingly scrutinize cyber underwriting guidelines, requiring formal documentation of risk appetite and assessment criteria.

Cyber risk assessment requires automated capture of external IT infrastructure scans (open ports, certificate status, exposed services), security questionnaire responses, threat intelligence feed results, and breach history from multiple databases. Manual or periodic capture is insufficient because the cyber posture of an insured's external-facing infrastructure changes continuously. Automated capture from domain scanning tools and threat intelligence feeds ensures the AI evaluates current security posture, not a snapshot from last quarter.

Cyber risk scoring requires formal ontology mapping Company.Domain to ThreatIntelligence.Indicators (ExposedPort, UnpatchedService, DataBreachHistory) with explicit relationships to CoverageRestriction and PricingAdjustment. The AI must know: Company.OpenRDPPort + Industry.Healthcare → HighRansomwareExposure → PremiumLoading.Ransomware with specific thresholds. Without machine-readable entity definitions and constraint rules, the AI cannot systematically score cybersecurity maturity or generate defensible coverage modifications.

Cyber risk assessment requires API access to external IT scanning services (BitSight, SecurityScorecard), threat intelligence platforms, internal claims and breach history databases, and industry breach repositories. These API connections enable the AI to retrieve current security posture data during the underwriting workflow without manual lookups. The insured's domain is the key identifier—API calls return structured vulnerability profiles that feed directly into the scoring model.

Cyber threat intelligence evolves daily—new vulnerability classes emerge, ransomware group tactics shift, and industry-specific attack vectors change within weeks. Cyber risk scoring models and threat indicator libraries must update near-real-time when new threat intelligence arrives. When a critical CVE is published affecting a widely-deployed service, the cyber assessment for insureds running that service must reflect the elevated exposure within hours, not at the next quarterly guideline review.

Cyber risk assessment requires API-based connections between the underwriting system, external scanning platforms, threat intelligence feeds, internal claims database (breach history), and industry databases (Advisen, CyberCube). These connections allow the AI to assemble a complete cyber risk profile combining internal insured history with current external threat posture. Point-to-point API connections between these systems are sufficient to power the cyber scoring workflow.