Risk Management 2026: Between the MaRisk reset and technological transformation – how GRC is evolving from a compliance function to a value driver
For many institutions, 2026 is not just another year of regulatory compliance. It marks a fresh start. New expectations regarding proportionality, ESG, ICT resilience and model governance are colliding with a risk landscape where cyber threats, AI and geopolitical tensions are intertwined. Those who continue to treat GRC merely as a compliance function will find themselves lagging behind.
The demands on risk management are increasing. At the same time, the pressure to make decisions faster and manage transformations effectively is growing. This is precisely why it is no longer enough to simply work through new requirements in isolation. What is needed is a GRC setup that is robust from a regulatory perspective, functions effectively in practice and improves management decision-making.
Key points at a glance:
- Regulation requires greater control, not just more documentation.
- Cyber threats, AI, third-party risks and geopolitical tensions will interact more closely in 2026.
- Governance-enabled technology makes GRC faster, more consistent and more audit-proof.
- The real added value lies in better decision-making for the Executive Board, the Supervisory Board and the specialist departments.
2026 is not a typical year for regulatory developments:
Regulators now expect more than just formally sound processes. Institutions are expected to make use of their discretion in a manner commensurate with risk, provide transparent justifications for decisions, and implement effective governance. This shifts the focus: away from tick-box exercises and towards actual management capability.
For many institutions, this marks a turning point. Issues such as ESG, ICT resilience, outsourcing, model risks and AI can no longer be managed in separate silos. They are interlinked and have a direct impact on business models, organisation and decision-making processes.
Where institutions now need to take specific action:
- ESG will become part of the core system
ESG is no longer an add-on module. ESG risks must be integrated into the risk inventory, strategy, control system and reporting. This turns scenario analysis into a repeatable capability. What matters is not the next individual analysis, but a robust framework comprising data, methodology and governance. .
- ICT risks and resilience are becoming central to risk management
ICT risks are not purely an IT issue. They need to be included in the risk inventory and in strategic management. At the same time, there is a growing need for a consistent ICT and resilience strategy. Crisis management capabilities must not only be described, but must also be manageable and verifiable in the event of an emergency.
- Third-party risks require an integrated approach
Whether it’s outsourcing, external ICT services or other critical dependencies: from an operational perspective, the big picture is what counts. Institutions need transparency regarding contracts, controls, exit scenarios and concentration risks. Only in this way can various regulatory requirements be translated into a functioning governance model.
- Model governance explicitly includes AI
With AI, the pace and complexity are increasing. At the same time, the demands on data quality, validation, monitoring, recalibration and explainability are growing. For institutions, this means that AI must not be treated as an isolated use case. It must be managed as a governance object – with clear roles, documented decisions and a robust lifecycle.
The winner is not the institution with the most policies, but the one with the better governance and decision-making structure.
The risk landscape is becoming more hybrid:
By 2026, a clear pattern emerges: risks rarely occur in isolation. Cyber security remains a dominant issue. At the same time, AI increases productivity, dependencies and the burden of control. Geopolitical tensions are affecting supply chains, costs, markets and operational resilience. Regulatory divergence further adds to the complexity. And a lack of in-house capabilities turns every modernisation project into an implementation risk. For risk management, this means that the separation into individual disciplines is becoming less effective. Managing cyber, AI, third parties, data and resilience separately creates new blind spots. What is needed is an integrated view of interactions, dependencies and escalation pathways.
Technology only creates value if it can be effectively managed:
More tools alone will not solve the problem. New technologies only create added value if they improve governance, traceability and decision-making capabilities.
This is what matters:
- A robust inventory for models, AI applications, assets and third parties
- Consistent workflows for controls, records and approvals
- Reusable scenario and stress testing capabilities
- Monitoring of model behaviour, drift and exceptions
- Dashboards that translate technical risks into actionable management information
This reduces the amount of manual work involved. Issues are identified earlier and resolved more quickly. Audits become more transparent and reliable. Decisions can be made earlier and with greater consistency.
Why GRC is now becoming a value driver:
GRC derives its value not from documentation, but from the quality of decision-making. If the Executive Board and Supervisory Board can identify at an earlier stage which risks affect the business model, how scenarios impact capital, liquidity or earnings, and which controls are actually effective, the institution’s ability to act is enhanced. This has a direct impact on pricing, portfolio management, investments, product development and crisis management. This is precisely where the role of risk management is shifting: away from mere hedging, towards a function that makes strategic decisions more well-founded.
What institutions should prioritise now:
Firstly: Start with a structured impact assessment. Clarify exactly what is changing in terms of scope, proportionality, governance and operating model.
Secondly: Establish a model and AI governance framework that covers the entire lifecycle. Not as a collection of policies, but as a process involving roles, approvals, evidence and monitoring.
Thirdly: Modernise your ICT risk profile. Integrate risk inventory, resilience strategy, crisis pathways and third-party dependencies into a consistent management model.
Fourthly: Make ESG scenario analysis repeatable. Methodology, data and governance must be sustainable in the long term, not just for the next audit.
Fifth: Sharpen your board communication. Cyber and AI risks need to be translated into risk appetite, limits, KRIs and concrete decision-making templates.
Sixth: Embed AI literacy and upskilling as a risk management measure. Skills are not a peripheral issue. They are a prerequisite for effective governance.
Conclusion
By 2026, it will become clear how organisations will approach risk management in the future. As a document-based project, it is too slow, too expensive and too fragmented. As an integrated management function, it becomes a lever for resilience, speed and better decision-making. Those who successfully integrate regulation, data, processes and technology turn GRC into more than just a compliance requirement. They turn it into a driver of value.
We help organisations translate regulatory requirements into digital workflows that turn GRC into a genuine driver of value. Let’s explore together how you can use modern software solutions to reduce complexity and improve the quality of your decision-making.
