Healthcare remains the most targeted industry for cyberattacks, with third-party suppliers implicated in the majority of major breaches. In fact, supplier-related incidents accounted for over 55% of healthcare breaches in 2024, and the average cost of a healthcare data breach exceeded $10 million. For organizations entrusted with protected health information (PHI) and critical patient services, continuous supplier oversight is no longer optional — it’s essential.
CORL Technologies, the healthcare industry’s leading managed third-party risk management (TPRM) solution, today announced a strategic partnership with Mastercard.
The collaboration will integrate Mastercard’s RiskRecon platform, which provides continuous cyber risk scoring and AI-enabled threat protection capabilities directly into CORL’s end-to-end TPRM platform — purpose-built for healthcare.
This partnership will transform supplier oversight from point-in-time snapshots into continuous, expert-vetted intelligence — without requiring clients to juggle multiple platforms or licenses.
“Our clients don’t need more raw data — they need the right insights at the right time,” said Jay Stewart, CRO of CORL Technologies. “This partnership with RiskRecon elevates our ability to provide healthcare-specific, human-interpreted risk intelligence that helps organizations act faster, with greater confidence.”
Why This Matters in Healthcare
Healthcare supplier ecosystems are vast, complex, and often under-monitored—spanning thousands of partners that handle PHI, sensitive systems, or regulated data. A single supplier weakness can cascade into HIPAA violations, operational disruption, and reputational damage.
Boards, regulators, and compliance leaders now demand proof of continuous oversight, not just annual check-ins. The CORL + RiskRecon integration addresses this by delivering real-time, healthcare-specific cyber risk intelligence — powered by AI and interpreted by risk advisors — so security teams can detect, prioritize, and act on emerging threats faster than ever before.
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