Singapore’s financial sector is at the forefront of adopting artificial intelligence (AI), particularly generative AI (Gen AI), as it seeks to maintain its position as a global hub for financial technology. This cutting-edge technology promises significant productivity gains for banks and financial institutions, from improving customer service to streamlining operations. However, as with any disruptive innovation, adopting AI in finance comes with its own set of challenges and risks.
In a recent interview with the Business timeChia Der Jiun, Managing Director of the Monetary Authority of Singapore (MAS), highlighted ongoing efforts to understand and manage the risks associated with AI in finance. “The focus has been on building capacity, both within the industry and on the regulator side, in terms of understanding risk and therefore how to better manage it,” Chia explained.
As Singapore’s financial sector evolves in this AI-driven landscape, regulators and industry leaders are working together to develop frameworks that balance innovation and risk management. Projects like MindForge and the ongoing development of an AI governance playbook demonstrate the collaborative effort to establish best practices and guidelines for implementing AI in finance.
Grace Chong, Head of Financial Services Regulation at Drew & Napier, highlights Singapore’s regulatory approach to AI in financial services. “Singapore adopts a principles-based model through MAS and its FEAT (fairness, ethics, accountability and transparency) principles,” says Chong. “The FEAT framework encourages companies to conduct self-assessments to ensure that AI systems, particularly in credit scoring, operate transparently and avoid bias against specific demographic groups.”
This approach reflects Singapore’s commitment to fostering innovation while maintaining strong regulatory oversight. “MAS’s Veritas initiative also supports this by providing practical tools to measure the fairness and transparency of AI models, thereby promoting responsible innovation,” she says.
However, financial institutions in Singapore face several legal and compliance challenges when implementing AI solutions, particularly around data privacy and algorithmic transparency, notes Chong. “While Singapore’s approach provides flexibility, it may allow for inconsistencies in upholding AI ethical standards between different institutions,” she adds.
Achieving algorithmic transparency presents unique challenges, particularly for complex “black box” models. “The Singapore FEAT Principles and the PDPC AI Governance Model encourage transparency, urging institutions to communicate the methodology, rationale and impacts of AI-based decisions,” says Chong, noting that this emphasis focus on transparency aims to build trust in AI systems among consumers. and regulators.
Accountability for errors or biases in AI-based financial decisions is another crucial area of focus for Singapore regulators. “Regulators are increasingly prioritizing structured accountability to address errors or biases in AI-based decisions, particularly in high-stakes financial services,” says Chong. “The Singapore MAS has expressed this through its FEAT principles, which establish both internal and external accountability.”
This approach highlights the need for transparent governance from senior management down. As Chong explains, “Internal reviews and documentation should be part of this process, with senior management taking direct responsibility for AI outcomes, emphasizing the need for transparent governance from senior management down inferior”.
Looking ahead, Singapore is well-positioned to play a leading role in effectively governing AI in financial services while fostering innovation. Chong suggests that introducing regulatory sandboxes specifically aimed at AI applications could be beneficial. “Sandboxes provide a controlled environment for companies to test AI models under regulatory oversight, giving regulators insight into the practical implications and risk profiles of the technology before instituting formal rules,” notes- she said.
Singapore’s commitment to AI innovation in finance is also demonstrated through initiatives such as the National AI Strategy and AI Singapore, which aim to develop local talent and capabilities in terms of AI. These efforts, combined with MAS’s regulatory approach, create an enabling environment for the adoption of AI in the financial sector.
As Singapore’s financial services sector continues to adopt AI, the need for balanced and effective regulation becomes increasingly crucial. By fostering collaboration between regulators, industry leaders and technology experts, Singapore is poised to harness the power of AI in finance while mitigating risks and ensuring ethical practices. The city-state’s approach to AI in financial services serves as a model for balancing innovation and responsible governance, with the potential to influence global standards in this rapidly evolving field.
“Establishing standards for algorithmic explainability, data governance and internal accountability within financial institutions could strengthen regulatory frameworks without imposing a rigid compliance burden,” says Chong. “This balanced approach will be crucial to enable Singapore to maintain its position as a leading fintech hub while ensuring the responsible and ethical use of AI in financial services.”