AI is no longer just a futuristic concept – it’s here, deeply embedded in our professional and personal lives. The uptake of AI by organisations is soaring, from 20% of organisations in 2017 to 78% in 2024 and the growth of GenAI is even sharper, from 33% in 2023 to 71% in 2024.
As the technology evolves at a blistering pace, we often don’t realise how much we already depend on it. Just consider the rapid development of open-source AI models – groundbreaking innovations can become ‘old news’ in a matter of weeks.
This acceleration brings both incredible opportunities and substantial risks. While AI can enhance efficiency, automate complex processes and strengthen compliance efforts, it can also introduce new vulnerabilities, particularly in financial services, where trust, security, and regulatory compliance are paramount.
Importance of governance in AI
To navigate this landscape successfully, financial institutions must implement a robust AI governance approach. AI governance refers to the practices, policies and tools used to ensure AI systems are deployed and used responsibly and in compliance with regulations. It isn’t just about managing the technical aspects of AI, but also about ensuring that AI solutions align with broader business goals, ethical standards and legal obligations. And with the EU AI Act setting new legal frameworks, financial companies need to get ahead of the game.
AI – a game changer in financial compliance
AI is already transforming industries, with financial services at the forefront of this shift. For example, the technology plays a crucial role in both enabling and combating financial crime. On one hand, AI has given criminals powerful new tools- creating hyper-realistic fraudulent documents, developing sophisticated money laundering schemes and the automation of cyberattacks.
On the side of the good guys, financial institutions are leveraging AI to strengthen their defences against financial criminals and enhance compliance with anti-money laundering (AML), counter-terrorist financing (CTF) and sanctions regulations. AI-driven solutions are enabling advanced document validation, for example, to detect fraudulent identities and financial statements. AI solutions can also ensure banks and financial firms can conduct continuous and automated screening against sanctions lists. They can also conduct AI-powered risk profiling for customers and transactions and real-time transaction monitoring to detect suspicious activities faster and more accurately.
AI’s role in financial compliance is not just about efficiency – it’s about ensuring institutions fulfil their role as gatekeepers of the financial system.
The risks of AI in business-critical processes
AI offers many benefits, but its integration into core business processes introduces significant risks too. One of the primary concerns is the lack of transparency – AI models can generate inaccurate results without clear explanations, which can complicate decision-making.
Another issue is that biased training data can lead to discriminatory outcomes, which ultimately undermines fairness and trust. Data security is another challenge, as AI tools can inadvertently expose sensitive information, resulting in breaches of regulatory norms. And non-compliance with regulations, such as the EU AI Act, can lead to substantial fines, exacerbated by reputational damage from ethical failures.
For financial institutions, these risks are not abstract; they represent real challenges that must be managed within a strong risk framework. So addressing them effectively is vital if financial institutions are to maintain long-term success and trust amongst customers, employees and their industry.
The EU AI Act: a compliance imperative
To address AI-related risks, understandably the regulators are stepping in. The EU AI Act, which came into effect in August 2024, introduces a risk-based approach, categorising AI systems from minimal to high risk, with more stringent compliance requirements for high-risk applications.
Key elements of the act include mandatory risk management practices, transparency requirements and human oversight for high-risk AI systems. It also stipulates that stronger enforcement measures are needed, including potential fines for non-compliance. There is a phased rollout with elements of the EU AI Act, with – for example – AI literacy obligations coming into force in February 2025
For businesses, this means AI governance is no longer just best practice or a way to squeeze the best out of AI initiatives – it’s a legal imperative.
AI governance: the path to responsible AI adoption
AI governance is the way for financial institutions to ensure they have the guardrails in place to remain compliant whilst still being able to maximise its benefits. It’s essentially a structured framework to make sure that AI systems are managed effectively, lawfully and securely. It helps organisations balance innovation with accountability, ensuring AI acts as an enabler rather than a liability.
Even AI systems classified as ‘low-risk’ under the EU AI Act, can still pose significant challenges if they are not properly managed. This is why financial institutions must integrate AI governance into their wider risk management strategies. The challenge? Many organisations still lack clear guidelines and standardised approaches for effective AI governance – they don’t really have a cohesive, strategic approach.
Getting AI governance right
AI governance requires embedding risk management into your organisation’s core processes. It’s imperative that financial institutions treat AI risks with the same priority as cybersecurity or fraud prevention to make sure that they are effectively managed and risks are avoided to the best of the organisation’s ability. So what are the key aspects of getting AI governance right for financial firms?
- Mitigating bias and ensuring fairness: regular audits of AI models and embedded systems are vital to make sure that firms can identify and address biases – this ensures fair outcomes and ethical decision-making.
- Data security and compliance: financial institutions need toprotect sensitive data and AI-generated content with strong security measures. Financial compliance teams now need to add AI regulations, such as the EU AI Act, to their usual financial compliance agendas to make sure they avoid AI-associated legal risks and reputational damage.
- Transparency and explainability: AI-driven decisions must be understandable and justifiable. Clear explanations build internal trust and ensure compliance with external regulations.
- Model registering: a centralised AI model register for organisations is key. It ensures visibility over the AI models you’re using, monitors performance and maintains accountability, making it easier to manage compliance and mitigate risks.
- Embedding AI in software services: as AI becomes increasingly embedded in third-party software, oversight is critical. Ensure these integrations are monitored for risks like bias, security vulnerabilities, or unintended consequences.
It’s time to act now
AI governance is not just about risk mitigation – it’s about empowering businesses to harness AI’s full potential in a responsible way. Financial institutions that proactively implement governance frameworks will not only ensure compliance, but also foster trust among customers, partners, and regulators, which ultimately will help them to gain a competitive edge.
At Valcon, we specialise in helping businesses navigate the complexities of AI governance, ensuring AI-driven success with compliance and risk management at the forefront. Ready to future-proof your AI strategy? Let’s start the conversation. Please get in touch with: [email protected], [email protected] or [email protected]
