KYND launches AI detection tool for cyber insurers

KYND has launched an AI detection tool for cyber insurers. It is designed to give underwriters an independent view of AI technologies visible across an organisation's online assets.

The new feature from the London-based cyber risk intelligence provider lets insurers identify AI technologies across an organisation's external digital footprint from a single domain, without needing information from the insured business. It is intended to sit alongside proposal forms and underwriting discussions when insurers assess cyber risk.

The launch reflects a growing challenge for cyber insurers as businesses adopt AI tools faster than many governance processes can track them. Underwriters are being asked to assess how companies use AI and what risks may follow, but those assessments often rely heavily on the applicant's own disclosures.

According to KYND, the tool identifies AI applications and features visible across infrastructure, including AI assistants and chatbots, generative AI tools, AI used in marketing and commerce technology, and AI crawlers permitted by a company's infrastructure.

KYND argues that independently observed data could help insurers spot gaps between declared and detectable technology use. It says the approach may also help underwriting teams ask more detailed questions during risk selection.

Research cited by KYND points to the scale of the challenge. IBM found that one in five organisations reported a breach last year linked to "shadow AI", referring to AI use without formal approval or governance. Organisations with high levels of shadow AI also faced average breach costs USD $670,000 higher than those with low or no shadow AI.

The issue has implications beyond individual policy decisions. Insurers and reinsurers are also trying to understand whether the same technologies appear repeatedly across their books of business, creating concentration risk if weaknesses or incidents affect multiple policyholders at once.

KYND said its AI detection feature can be applied across portfolios as well as individual risks. In that context, the data could give portfolio and reinsurance teams a clearer view of common AI technologies and dependencies across insured organisations.

Melanie Hayes, Co-founder, KYND, said: "Proposal forms and underwriting conversations remain essential, but AI use is changing rapidly and businesses themselves may not always have complete oversight of the technologies being used across their organisation. Giving underwriters independently observed information means the conversation can start with greater visibility of what is detectable on the risk, helping underwriters ask more informed questions and build a clearer picture of the exposure."

KYND has previously examined what it describes as silent AI exposure within insurance portfolios. In that research, it warned that businesses may be adopting AI faster than they disclose it, leaving some exposure unidentified during underwriting and making it harder for insurers to see where concentrations are forming.

Broader detection

AI is one part of KYND's wider technology detection offering. Its platform also identifies payment and cloud services, analytics and tracking pixels, session-recording tools, identity and access management systems, and the platforms on which websites are built.

This broader view of digital infrastructure is relevant to insurers because cyber underwriting increasingly depends on understanding third-party dependencies as well as a company's own security posture. External visibility tools have become one way for insurers to gather information without relying entirely on questionnaires or broker submissions.

Competition in cyber insurance has also pushed carriers to sharpen their view of risk while keeping underwriting processes efficient. Tools that provide externally observed signals are being used to support pricing, selection and portfolio management, particularly in areas where technology adoption is changing quickly.

Hayes said the issue is likely to become more pressing as AI becomes more common across business operations. "As AI becomes more deeply embedded across businesses, insurers will increasingly need to understand where common technologies and dependencies are appearing across their books. The industry is still building its understanding of how AI-related losses will develop. Being able to identify those dependencies now gives insurers a stronger foundation to understand and manage exposure as it evolves."