What Is CTEM in Banking Cybersecurity?
CTEM follows a structured, continuous process. Bell describes it as five stages: “It’s effectively five steps in the maturation — scoping, discovery, prioritization, validation and mobilization.”
For banks and credit unions, these stages focus on high-value systems:
- Scoping identifies critical assets such as core banking, payments and digital channels
- Discovery uncovers vulnerabilities, misconfigurations and attack paths
- Prioritization ranks risks based on financial impact and likelihood of exploitation
- Validation simulates attacks to confirm which exposures are exploitable
- Mobilization coordinates remediation across teams
Cartwright notes that CTEM expands beyond traditional scanning.
“Typically, in vulnerability management, you have a scanner, you detect vulnerabilities and you patch them,” he says. “That tends to happen in a silo of the security organization. With CTEM, you need to identify your sources of data across the enterprise, aggregate all of that data, deduplicate it, add business context and then have a mobilization layer to remediate.”
EXPLORE: How banks are modifying their data strategy because of AI.
Why CTEM Matters for Financial Institutions
Security teams are increasingly overwhelmed. “Their security operations center teams are overloaded on software vulnerabilities,” Cartwright says. “Every single day, there are new critical vulnerabilities coming out. Their teams just can’t handle remediating all of those without impacting the business.”
At the same time, traditional programs often miss key risks — including misconfigured cloud environments, nonsecure application programming interfaces and overpermissioned identities.
“What about exposures related to misconfigured systems or risky configurations?” Cartwright asks. “It’s not necessarily a vulnerability, but it’s the way the system has been deployed.”
Without business context, teams struggle to prioritize effectively, often reacting to alerts instead of focusing on protecting critical systems and member data.
“There’s a generalized fear of what AI is bringing to overall threat approaches,” Bell says. “Point-in-time analysis is really insufficient. Customers want a more continuous ability to evaluate their risk posture.”
