By Ashley Crawford, Risk Specialist at SAS UK & Ireland
Artificial intelligence (AI) is revolutionising the banking sector, allowing financial institutions to enhance customer experience, streamline operations, and strengthen risk management. However, this rapid advancement comes with increasing regulatory scrutiny.
As new AI regulations take shape – most notably the EU AI Act – banks are facing a complex challenge: how to innovate while ensuring compliance, transparency, and responsibility.
The evolving regulatory landscape
Regulators worldwide are racing to establish governance frameworks that balance innovation with risk mitigation. The EU AI Act is the most comprehensive regulatory initiative to date, classifying AI systems based on risk levels and imposing stringent requirements on high-risk applications, including those used in credit scoring and fraud detection.
While the UK is shaping its own regulatory approach, businesses operating across both the UK and the EU will need to align with the EU AI Act to ensure compliance. At the same time, the UK government has signalled intentions to review certain regulations, with the Chancellor suggesting deregulating some areas to foster innovation.
This evolving landscape creates uncertainty for banks, which must navigate divergent regulatory priorities. While the EU is tightening its stance on AI governance, the UK is moving towards a more principles-based approach, leaving financial institutions in a regulatory grey zone.
For banks operating across multiple regions, compliance becomes even more complex, requiring adaptable strategies to meet varying requirements.
The compliance challenge
AI’s rapid pace of development makes it difficult for banks to ensure their models remain compliant. Many institutions invest significant resources in developing AI-driven solutions, only to find that emerging regulations introduce new compliance demands. This reactive approach forces banks into a constant cycle of adjustment, limiting their ability to explore AI’s full potential proactively.
One of the most pressing concerns for regulators is explainability. In high-stakes areas like lending and fraud prevention, banks must demonstrate how their AI models arrive at decisions. However, many systems function as opaque black boxes, making it difficult to provide the necessary transparency.
Without robust governance, banks risk regulatory penalties, reputational damage, and erosion of consumer trust. To navigate these regulatory challenges, banks must implement comprehensive AI governance frameworks that ensure compliance while fostering responsible innovation.
Strengthening AI governance with a robust framework
Effective AI governance starts with robust oversight, where banks must monitor AI systems throughout their lifecycle to ensure alignment with ethical standards and business objectives.
Model interpretability is essential – AI systems should offer clear, auditable reasoning for their decisions, particularly in sensitive, high-stake areas like lending and fraud prevention. Regulators and customers alike need assurance that AI-driven outcomes are fair and justifiable.
Regulatory alignment is another crucial aspect of AI governance. Banks need to stay up to date with evolving regulations across different jurisdictions and integrate compliance considerations into AI model development from the outset.
A strong operational foundation is also necessary. Banks need an AI platform with capabilities supporting development and deployment of trustworthy, responsible AI.
However, an AI governance framework is only as strong as the culture supporting it. Ensuring sufficient AI literacy across the workforce helps employees understand AI’s capabilities, risk and ethical implications. By embedding AI governance principles into organisational culture, banks can drive responsible AI adoption and reinforce public trust.
With a structured governance framework banks can balance innovation with responsibility, and build trust with both regulators and customers while mitigating compliance risks. Such a framework not only supports adherence to regulations but also enables banks to leverage AI’s full potential with confidence and credibility.
Identifying potential risks
Risk management is also essential in AI governance. Banks must proactively identify potential risks associated with AI, such as bias, unfair treatment, or cybersecurity vulnerabilities, and implement robust controls to mitigate these threats. Without a structured risk management approach, AI systems can inadvertently create financial and reputational harm.
Finally, ongoing monitoring and auditing are necessary to maintain compliance and ensure AI models continue to perform as expected. Regular assessments, audits, and updates help identify potential issues before they escalate, allowing banks to address them proactively.
Advanced AI platforms, such as SAS Viya, enhance this process by leveraging capabilities across the data and AI lifecycle to detect hidden risks and uncover new opportunities. By moving beyond reactive risk management, banks can anticipate potential threats before they arise, enabling more confident and strategic decision-making.
Staying ahead of the curve
Rather than viewing regulations as barriers, banks should see them as an opportunity to build stronger, more resilient AI systems. By proactively engaging with regulators, financial institutions can help shape the future of AI governance while demonstrating their commitment to responsible AI use.
Furthermore, leveraging advanced AI governance tools, such as automated compliance monitoring, bias detection and mitigation algorithms, and leveraging capabilities or functionality for explainability, as well as model monitoring and management, can help banks stay ahead of regulatory requirements while enhancing AI performance.
Collaboration with industry bodies, regulators, and technology partners is also key to developing best practices and ensuring that AI innovation aligns with regulatory expectations.
The future of AI in banking
The future of AI in banking will be defined by the industry’s ability to navigate evolving regulations while continuing to innovate. Adopting robust AI governance frameworks enables banks to strike a balance between compliance and technological advancement, ensuring that AI remains a trusted and effective tool in financial services. Software vendors can add value here where they have expertise in regulatory compliance as well as use of their software, enabling them to work more as a partner to the bank.
As regulatory scrutiny increases, financial institutions that embrace transparency, risk management, and proactive compliance will be best positioned to thrive in this rapidly changing environment.
