RegTech Forum 2026 - Fireside chat: How to use the best tool for the job
As financial institutions explore new ways to improve efficiency and modernise regulatory reporting, choosing the right technology for the task has become increasingly important. The How to Use the Best Tool for the Job panel examined how automation and artificial intelligence can deliver meaningful benefits, while highlighting the importance of reliable data, effective controls and human accountability.
Automation creates value when it frees people to focus on higher-value work. Replacing repetitive manual processes with more effective tools can improve speed and efficiency, allowing specialists to dedicate more time to investigating risks, analysing data and supporting better decisions. However, these benefits depend on selecting technology that addresses a genuine business need.
Strong data foundations remain essential for reliable AI. Legacy systems, inconsistent data definitions and poor data lineage continue to present challenges for financial institutions. AI cannot compensate for fundamental weaknesses in the information it relies on. Investing in data quality, integration and consistent definitions is therefore critical to producing trustworthy outputs.
Accuracy requires more than generating an answer. Producing a report or recommendation does not guarantee that it is correct. Reconciliation, validation and robust controls are essential to ensure outputs are accurate, consistent and suitable for regulatory use. As AI becomes more capable, firms must retain the ability to verify its work rather than assume its results are reliable.
AI governance must be embedded into the technology itself. As AI agents become more autonomous and operate at greater speed and scale, relying solely on human oversight may not be sufficient. Firms need clearly defined permissions, preventative controls and mechanisms to identify and stop inappropriate actions. The level of control should reflect the risks associated with each application.
Human accountability remains central to responsible adoption. Organisations must be able to explain why they trust a system, demonstrate the checks applied to its outputs and identify who is responsible when something goes wrong. AI can support decision-making, but it does not remove the need for professional judgement or clear ownership of outcomes.
The right tool depends on the task and its potential impact. AI can be particularly valuable for improving productivity, scrutinising data and interpreting complex regulatory requirements. Applications with greater autonomy or significant financial or customer consequences require more rigorous testing and stronger safeguards. The objective should not be to deploy the most advanced technology available, but to choose the solution best suited to the problem.
Technology should strengthen expertise, not replace it. Making information and answers more accessible can support learning and collaboration across teams. However, employees must continue to develop the knowledge and judgement needed to challenge AI-generated outputs and recognise when results may be incomplete or incorrect. Effective adoption combines technological capability with human understanding.
Effective oversight starts with asking the right questions. Boards and senior leaders do not need to become technical specialists, but they must understand the potential impact of AI, the scenarios in which systems could fail and the safeguards in place. Clear accountability, credible contingency plans and informed challenge are essential to maintaining effective governance.
Looking ahead, legacy infrastructure and fragmented systems remain significant barriers to progress. Modern tools can help connect information and improve reporting processes, but sustained investment in underlying technology and data capabilities is still required. As lending, payments and other financial activities become faster and increasingly real-time, regulatory reporting and risk management will also need to become more responsive.
Ultimately, successful technology adoption is about combining innovation with control. By choosing the right tools, strengthening data foundations and embedding effective governance, financial institutions can turn efficiency gains into better decisions and stronger risk management. The goal is not simply to automate more, but to ensure that technology delivers reliable, measurable value while preserving the expertise and accountability on which the industry depends.
Panellists:
- Oliver Margetts, Chief Technology Officer, Suade (Moderator)
- Zachary Anderson, Chief Data & Analytics Officer, Global Banking & Payments, JP Morgan
- Jonathan Taylor, Head of Quantitative Analysis & Model Risk Management, PRA, Bank of England
- Nick Wilson, Liquidity Reporting Senior Manager, Lloyds
This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.