By Ashley Crawford, Senior Risk Solutions Executive at SAS.
For decades, we’ve seen banks manage risk and treasury functions in parallel but as largely separate domains. Credit risk teams focused on exposures and impairments, treasury departments managed liquidity and funding, and balance sheet optimisation often sat somewhere in between.
That model is now under strain. In an environment defined by volatility, regulatory scrutiny and rapid technological change, fragmentation is no longer sustainable. And we’re seeing the consequences play out in real time.
Recent industry research, including PwC’s 2025 Global Treasury Survey, suggests treasury functions are increasingly moving toward more connected operating models in response to heightened volatility, regulatory pressure and demands for faster decision-making.
This new model is one centred on integration, optimisation and real-time insight. Across financial organisations we work with, we’re increasingly seeing institutions consolidating risk and treasury capabilities into unified platforms, enabling a more dynamic and coordinated approach to balance sheet management.
For many banks this shift is not incremental. It represents a foundational redesign of how financial risk is understood, managed and acted upon.
Breaking down the siloes
The traditional siloed structure has long constrained banks’ ability to respond quickly to market changes. Separate systems, inconsistent data models and disconnected reporting processes create latency at precisely the moment speed is most critical.
Scenario analysis, which is essential for navigating interest rate shocks, liquidity stress or credit deterioration, can take days or even weeks to run across fragmented systems.
When we bring together credit risk, market risk, liquidity risk and treasury functions within a single architecture, we can run enterprise-wide simulations in near real time.
Recent industry reports have highlighted the operational cost of fragmentation, with siloed data environments often forcing teams into manual reconciliation and duplicate reporting processes that can delay hedging, pricing and balance sheet decisions. In volatile markets, even small delays can have material consequences.
A single, integrated architecture also enables decision-makers to assess the interplay between funding strategies, capital allocation and risk exposures more holistically. From what we’ve seen, a unified data foundation reduces reconciliation issues and improves transparency, both internally and for regulators. It also supports more consistent application of methodologies and assumptions, which is increasingly important as supervisory expectations evolve.
The convergence of CRO and CFO
As integration deepens, the traditional boundaries between the chief risk officer (CRO) and chief financial officer (CFO) are becoming less distinct. Both roles are now deeply invested in balance sheet optimisation, capital efficiency and forward-looking risk management.
What we’re seeing increasingly is shared accountability at the top. CROs and CFOs making strategic calls together that would previously have sat separately. For example, decisions around loan pricing, hedging strategies or liquidity buffers now require simultaneous consideration of profitability, capital impact and risk appetite.
Integrated platforms provide the common language and shared metrics needed to support these discussions.
Crucially, this alignment also strengthens resilience. During periods of stress, such as sudden rate hikes or market dislocation, the ability to coordinate risk and treasury responses can significantly reduce losses and preserve capital.
It enables banks to move from reactive to proactive management, identifying vulnerabilities before they crystallise.
AI, optimisation and the governance imperative
AI is playing an increasingly prominent role in this transformation. Advanced analytics and machine learning models can enhance forecasting accuracy, identify emerging risks and optimise balance sheet strategies at a level of granularity previously unattainable.
However, the growing reliance on AI introduces new challenges – particularly around governance, transparency and control.
Without robust frameworks, there is a risk that models become opaque, decisions less explainable and vulnerabilities harder to detect. This is especially pertinent as generative AI and, in the future, quantum-driven models begin to influence financial decision-making.
Embedding governance into the design and operation of AI systems is therefore essential. This includes clear model validation processes, auditability, bias monitoring and alignment with regulatory expectations. It also requires a cultural shift, ensuring that human oversight remains central even as automation increases.
In our experience, when governance is built in from the start rather than bolted on, AI becomes a genuine enabler, unifying disparate data sources, automating complex calculations and supporting real-time decision-making.
A more complex risk landscape
The case for integration is further strengthened by the evolving nature of risk itself. Cyber threats are becoming more sophisticated, financial crime is increasingly technology-driven, and geopolitical instability continues to introduce new uncertainties.
Findings from the World Economic Forum’s Global Risks Report 2025 identified cyber espionage, misinformation and state-based conflict among the fastest-growing global risks facing organisations, reinforcing the need for more coordinated and enterprise-wide risk management approaches.
These risks do not sit neatly within organisational boundaries, but cut across functions and require coordinated responses.
An integrated risk-treasury framework allows banks to view these threats in context. For instance, a cyber incident is not just an operational risk – it can have immediate liquidity implications, reputational impact and regulatory consequences. Similarly, geopolitical events can affect funding markets, credit quality and capital flows simultaneously.
The road ahead
While the strategic rationale for integration is clear, there are also tangible operational benefits. Streamlined processes and automation can reduce manual workloads, easing headcount pressures and allowing skilled staff to focus on higher-value activities. Improved data quality and consistency reduce the risk of errors and enhance reporting efficiency.
Importantly, integration does not mean uniformity. Banks must retain the flexibility to adapt models, assumptions and strategies to their specific business profiles and risk appetites.
Modern platforms are increasingly designed with this balance in mind, combining standardisation where it adds value with configurability where differentiation is needed.
Looking ahead, we believe the trajectory is clear. As regulatory demands intensify and the risk environment becomes more complex, the ability to operate with a unified, optimised view of the balance sheet will be a defining capability. Institutions that continue to rely on fragmented systems and siloed processes will find it increasingly difficult to compete.
The transition to integrated risk and treasury is not without challenges. It requires investment, organisational change and a commitment to strong governance. But the rewards, in terms of agility, resilience and strategic clarity, are substantial.
Ultimately, the shift from silos to synergy is about more than technology. It reflects a broader rethinking of how banks manage uncertainty, allocate resources and create value in a rapidly changing world.
By grounding innovation in governance and aligning risk with treasury, institutions can build a more resilient foundation – one capable of supporting both current demands and the emerging risks of the future.