Bsecure advances continuous audit with DORA and NIS2 compliance on IBM z series with AI and RAG
For many European financial institutions and insurers, the mainframe remains the backbone of mission-critical operations. This mainframe technology delivers unmatched resilience and throughput—but it also concentrates risk: privileged access, highly sensitive datasets, and core transaction integrity all converge in one place. Under the DORA and NIS2 directive, organizations are expected to demonstrate stronger governance, controls, and operational evidence. In practice, NIS2 compliance is no longer just about having policies; it is about proving that controls are implemented, verified, and continuously maintained—especially in critical environments such as mainframes.
At Bsecure, we are accelerating the shift toward continuous assurance for IBM zSeries (z/OS).
From scarce specialist knowledge to scalable, audit-ready control engineering
Mainframe security solutions have traditionally depended on a limited pool of rare experts who can translate regulatory requirements into technical controls, implement them, and document them with audit-grade rigor. That approach works—but it does not scale. To address this, Bsecure has built an internal AI capability based on RAG (Retrieval-Augmented Generation), trained on our most relevant knowledge spanning decades of z/OS audit and security. The goal is straightforward: convert expert know-how into repeatable delivery, enabling teams to expand control coverage faster while keeping documentation consistent and audit-ready. This directly strengthens how organizations approach DORA and NIS2 compliance and supports alignment with other frameworks, such as GDPR or NIST 2.What our AI does inside Bsecure DataPASS for z/OS
This is not a general-purpose chatbot. Our AI supports the full lifecycle of control engineering within our DataPASS infrastructure:- Understands a reasoned request for a specific control tied to a defined risk scenario.
- Generates the control in the right structure so it can be implemented within DataPASS.
- Produces audit-ready documentation, including what is validated, how it is validated, evidence outputs, frequency, and exceptions.
- Maps controls to major regulations and frameworks, supporting traceability for DORA compliance, NIS2 compliance, GDPR obligations, and more.
Practical outcomes for mainframe security and audit teams
By applying AI to control engineering in IBM z environments, organizations can improve both speed and consistency across mainframe security solutions:- Faster expansion of control catalogs: Reduce time-to-control for new risks and regulatory expectations, without sacrificing rigor.
- Standardized documentation and evidence discipline: Minimize variability between consultants and teams, improving audit readiness and repeatability.
- Scalable delivery model: Enable professionals with strong general systems experience to contribute effectively, supported by AI and DataPASS.
- Stronger traceability for NIS2 compliance and GDPR: Improve the chain from risk → control → evidence → regulation, simplifying reporting and oversight.
