RegTech Forum 2026 - Panel: Building trust in AI

As artificial intelligence becomes increasingly embedded in financial services, building trust in its use is essential. The Building Trust in AI panel explored how organisations can realise the benefits of AI while ensuring its deployment remains safe, responsible and reliable. The discussion highlighted the importance of strong governance, high-quality data and clear accountability in managing the risks associated with increasingly capable AI systems.

Strong governance is the foundation of trust. Organisations need clear accountability, effective oversight and robust controls to ensure AI is deployed responsibly. These safeguards should be integrated into existing risk management frameworks, taking into account potential challenges such as bias, data privacy, security and operational resilience.

Reliable AI depends on reliable data. The quality of AI-generated outputs is directly linked to the accuracy of the underlying data, the clarity of data lineage and the explainability of the processes involved. While AI can deliver significant efficiencies, speed must not come at the expense of accuracy, transparency or trust.

Controls must reflect the level of risk. Not all AI applications carry the same potential impact. Organisations should adopt a proportionate approach to governance, validation and monitoring, applying more rigorous safeguards where AI decisions could have significant business or customer consequences.

Trust requires continuous monitoring. As AI systems evolve and become more widely accessible, organisations must maintain visibility over how they are used and regularly assess emerging risks. Ongoing monitoring is essential to ensure controls remain effective and that AI continues to operate within appropriate boundaries.

Human accountability cannot be delegated to AI. Although AI can support decision-making and improve operational efficiency, organisations must retain responsibility for its outcomes. Decisions and outputs should remain open to scrutiny, challenge and explanation, with appropriate human oversight in place.

Ultimately, responsible AI adoption requires a balance between innovation and control. Financial institutions have opportunities to use AI to improve efficiency and customer outcomes, but realising this potential depends on understanding its limitations and maintaining appropriate safeguards. By prioritising strong governance, reliable data and human accountability, organisations can build the trust needed to adopt AI responsibly and sustainably. The Building Trust in AI panel explored how organisations can realise the benefits of AI while ensuring its deployment remains safe, responsible and reliable. The discussion highlighted the importance of strong governance, high-quality data and clear accountability in managing the risks associated with increasingly capable AI systems.

Strong governance is the foundation of trust. Organisations need clear accountability, effective oversight and robust controls to ensure AI is deployed responsibly. These safeguards should be integrated into existing risk management frameworks, taking into account potential challenges such as bias, data privacy, security and operational resilience.

Reliable AI depends on reliable data. The quality of AI-generated outputs is directly linked to the accuracy of the underlying data, the clarity of data lineage and the explainability of the processes involved. While AI can deliver significant efficiencies, speed must not come at the expense of accuracy, transparency or trust.

Controls must reflect the level of risk. Not all AI applications carry the same potential impact. Organisations should adopt a proportionate approach to governance, validation and monitoring, applying more rigorous safeguards where AI decisions could have significant business or customer consequences.

Trust requires continuous monitoring. As AI systems evolve and become more widely accessible, organisations must maintain visibility over how they are used and regularly assess emerging risks. Ongoing monitoring is essential to ensure controls remain effective and that AI continues to operate within appropriate boundaries.

Human accountability cannot be delegated to AI. Although AI can support decision-making and improve operational efficiency, organisations must retain responsibility for its outcomes. Decisions and outputs should remain open to scrutiny, challenge and explanation, with appropriate human oversight in place.

Ultimately, responsible AI adoption requires a balance between innovation and control. Financial institutions have opportunities to use AI to improve efficiency and customer outcomes, but realising this potential depends on understanding its limitations and maintaining appropriate safeguards. By prioritising strong governance, reliable data and human accountability, organisations can build the trust needed to adopt AI responsibly and sustainably.

Panellists:

• Murat Abur, Co-founder & CIO, Suade (Moderator)
• Gaetano Chionsini, Head of Statistics, European Banking Authority
• Vicki Jordan, Policy Manager - AI, Remuneration, and Policy Profession, Financial Conduct Authority
• Nick Talbot, Head of Climate & Nature Risk; Head of AI Risk Framework Programme at NatWest

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.