Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For many organizations, vendor risk management (VRM) feels like an endless chase—gathering evidence, trudging through questionnaires, wrangling spreadsheets. Add expanding risk surfaces and new scrutiny from AI-driven regulations and customers, and it’s no wonder teams feel overwhelmed.

While fintech has helped streamline operations for financial institutions and everyday consumers, it has also introduced new risks that you must account for. According to the CyberCube Global Threat Outlook H1-2024, fintech is one of the top five sectors with the highest exposure to cybersecurity threats.

With the rapid adoption of AI and automation technologies, the automotive industry is experiencing a massive transformation. From autonomous driving tech to vehicles connected with cloud-based services, these innovations are reshaping how automakers and suppliers operate globally. However, these shifts have introduced new vulnerabilities, especially cyber risks, that need to be addressed.

Security leaders often face challenges that extend beyond the firewall: a major gap in communication between the security function and executive leadership. This misalignment can have severe consequences, including stalling deals, increasing organizational risk, and preventing security from being recognized as a key driver of business growth.

There’s a growing sense of risk awareness in the SaaS space as companies face increasing scrutiny over information security. According to Vanta’s State of Trust report, nearly two-thirds of organizations report that their stakeholders expect proof of a robust security posture and alignment with popular cybersecurity standards. ‍ ISO 27001 is one of the most widely recognized frameworks for demonstrating a strong security posture.

Introducing third-party AI into your systems can be a milestone for productivity and growth, but it also expands your attack surface in unpredictable ways. If your AI vendors have weak controls, threats like data poisoning and algorithm failure can ripple through your systems.