AICB Nexus as a Strategic Platform
It is a great pleasure to join you this morning at the inaugural AICB Nexus Conference. Let me begin by congratulating the Asian Institute of Chartered Bankers (AICB) and its partners for bringing together the Malaysian Banking Conference and the Bank Audit Conference under one platform.
Bringing these communities together reflects an important reality: the future of finance cannot be shaped through separate conversations. Innovation cannot succeed without governance. Governance cannot be effective without assurance. And neither can earn public trust without the other. It is timely that we bridge these conversations, recognising that innovation and assurance must increasingly advance together.
Innovation without trust is not progress
Today, AI is reshaping financial services. It is helping institutions detect fraud, assess credit and insurance risks, strengthen compliance, manage risks more effectively, and serve customers better. When optimised, AI can improve productivity, decision-making and access to financial services.
Understandably, much of today's discussion will focus on how quickly we can adopt AI. But perhaps the more important question is this: can we ensure that AI strengthens trust, preserves accountability and reinforces public confidence in the financial system?
After all, finance is built on trust. Trust that savings will be safeguarded. Trust that capital will be allocated efficiently. And trust that the institutions, governance and rules underpinning the system remain credible and resilient.
AI may transform finance. But trust will determine whether that transformation endures. That is why I would like to emphasise one simple yet powerful principle, “Innovation without trust is not progress”. This is not merely a statement about adoption of technology; it is about how we exercise leadership, how we uphold governance and ensure that the financial system we build remains trusted and firmly anchored in the needs of society.
If trust is to remain the foundation of finance in the age of AI, there are three priorities that deserve our attention. Allow me to frame these three principles today.
First priority: Purposeful innovation
First, innovation must be pursued with purpose. This is especially important as AI becomes more deeply embedded in financial services. Today, more than 70% of Malaysian financial service providers have implemented at least one AI application. Industry responses to our Discussion Paper on Artificial Intelligence in the Malaysian Financial Sector show that AI adoption is accelerating. Adoption is concentrating where there are opportunities for efficiency gains, productivity gains, and better risk management.
Thus far, financial institutions have focused on use cases that deliver internal value. The opportunity before us now is to move beyond this institution-centric lens. The next frontier is to use AI to solve problems that no institution can solve on its own.
Challenges such as scams, fraud and cyber threats require collective action. In the case of Malaysia, BNM, PDRM, financial institutions, PayNet and other partners have worked together to strengthen safeguards, share intelligence and protect customers. Trust is not built by one institution, but by an ecosystem working as one. This is innovation with purpose. Institutions should compete where markets demand it and collaborate where public interest demands it.
Second priority: Responsible and risk-aware innovation
Second, progress must be pursued responsibly and anchored in trust. We often speak about trust in AI as a technical challenge. One of model accuracy, data quality or system reliability. But in reality, it is a governance challenge.
As AI systems become more capable, they also become more complex. In many cases, AI models that offer the greatest analytical power are also among the most difficult to explain, validate or challenge. This presents new questions for every institution represented here today.
- First, how do we preserve accountability when decisions become harder to explain?
- Second, how do we ensure fairness when models continue to learn and evolve?
- Third, how do we govern technologies whose capabilities are advancing faster than our traditional control frameworks?
These are not technology questions alone. They are leadership questions.
As AI becomes more deeply embedded in financial services, the role of professional judgement becomes even more important. While machines may generate insights and support decisions, accountability must remain with those entrusted to govern and lead. Responsibility cannot be delegated to an algorithm.
For boards and senior management, this has profound implications: AI should not sit at the margins as a technology project. It belongs firmly on the board agenda. It is a matter of capital allocation and governance, anchored in clear business outcomes, measurable value and a defined risk appetite. The responsibility of leadership is to ensure that innovation strengthens, rather than weakens, trust.
To our colleagues in risk, compliance and internal audit: your role has never been more important. As systems become more complex and autonomous, assurance becomes harder – to be constructive and to be fair. It is no longer sufficient to confirm that controls exist. The question is whether institutions can explain outcomes, challenge decisions, and retain accountability in increasingly opaque systems.
Third priority: Innovation that brings progress for all
Last but not least, innovation must translate into progress for all. This begins with investing in people. The future of AI will be shaped less by technology than by talent. It is not only about technical skills, but governance capability, critical judgment and the ability to operate effectively where humans and machines interact. Without these capabilities, even the most advanced technologies will struggle to earn trust.
At the same time, AI is reshaping the nature of work. Roles are evolving, workflows are being redesigned, and job composition is changing. Preparing the workforce for this transition is not optional; it is a strategic imperative. Institutions must invest in upskilling and reskilling, while supporting their workforce through transition to ensure no segment is left behind.
AICB has an important role in building a future-ready workforce. Through the Future Skills Framework, it is helping professionals develop the AI literacy, ethical judgment and governance capabilities that will become increasingly important for the industry. We strongly support this effort and its continued evolution to meet the future needs of the industry.
Our approach
For BNM, our approach is clear: encourage innovation, uphold trust and ensure that progress benefits society. We neither constrain innovation prematurely nor leave it to unfold unchecked. Our stance is anchored in proportionality, parity and technology neutrality, ensuring innovation progresses responsibly and with confidence.
In practice, this means engaging industry early, providing clearer regulatory expectations, supporting responsible experimentation, and investing in shared infrastructure that enables innovation at scale.
Alongside AI, other developments will shape the sector. Our Open Finance framework establishes a foundation for secure, consent-based data sharing, with supporting infrastructure being developed with PayNet and the industry, and phased implementation from 2027. At the same time, our asset tokenisation roadmap is progressing into pilots through the Digital Assets Innovation Hub.
But we are clear that these are tools, not destinations. Their true value lies in whether they improve lives, strengthen resilience and deepen trust.
Looking ahead, we are shaping the next chapter of financial sector development through the Financial Sector Blueprint 2027 to 2030, developed in close collaboration with the industry, government and stakeholders to ensure it is grounded in real challenges and aligned with the evolving needs of the economy.
The future of finance will not be defined by how fast and sophisticated our technology is. It will be defined by whether that technology strengthens trust, broadens opportunity and serves society well.
That is the challenge before us. It is also our shared responsibility. And I believe that together we can deliver this outcome.
Facts Only
* The event was the inaugural AICB Nexus Conference, bringing together the Malaysian Banking Conference and the Bank Audit Conference.
* The article posits that innovation and assurance must advance together; innovation without trust is not progress.
* AI is reshaping financial services by helping institutions detect fraud, assess risks, strengthen compliance, and improve service delivery.
* Three priorities for ensuring trust in AI are proposed: purposeful innovation, responsible and risk-aware innovation, and innovation that brings progress for all.
* Purposeful innovation requires moving beyond institution-centric value to collective action across an ecosystem.
* Responsible innovation involves addressing governance challenges related to explainability, fairness in evolving models, and governing fast-moving technology.
* Innovation must translate into progress for all, requiring investment in upskilling and reskilling the workforce.
* BNM's approach is to encourage innovation while upholding trust through proportionality, parity, and technology neutrality.
* The framework for data sharing is established by the Open Finance framework and asset tokenisation roadmap pilots.
Executive Summary
The inaugural AICB Nexus Conference brought together the Malaysian Banking Conference and the Bank Audit Conference under one platform to address the intersection of finance, innovation, and governance. The central theme established is that progress in finance requires innovation and assurance to advance together, asserting that "Innovation without trust is not progress." This principle is framed around three priorities for navigating the integration of Artificial Intelligence (AI) in finance: purposeful innovation, responsible and risk-aware innovation, and innovation that brings progress for all.
The text posits that AI offers significant potential in financial services by enhancing fraud detection, risk assessment, and service delivery. However, the core challenge shifts from mere adoption speed to ensuring that AI strengthens trust and accountability. The article outlines that achieving this requires a shift in focus: moving beyond institution-centric value creation to collective action across an ecosystem, embedding leadership responsibility on the board, and investing strategically in workforce upskilling to ensure broad societal benefit. Regulatory bodies like BNM are taking a stance to encourage innovation while upholding trust, supported by existing frameworks for data sharing and asset tokenization.
Full Take
The narrative establishes a necessary tension between technological acceleration and foundational systemic requirements: trust and accountability. The argument moves successfully from a technical discussion of AI capabilities to a philosophical one about leadership, governance, and societal benefit. The structure relies on reframing the adoption debate: it is not merely *if* we adopt AI, but *how* we govern its deployment to maintain the social contract underpinning finance.
The progression from "Innovation without trust is not progress" to the three priorities demonstrates a sophisticated recognition that AI risks creating an opaque power differential if governance lags behind capability. The shift in focus—from internal institutional value (first priority) to external, collective responsibility and human capital development (third priority)—suggests an acknowledgment of systemic failure points inherent in purely market-driven technological adoption.
The pattern detected is a strong call for re-centering the locus of control from algorithms to human judgment and institutional accountability. This plays against the typical technological determinism often present in AI discourse, pushing instead toward a socio-technical management paradigm. The implied assumption is that advanced technology inherently demands higher levels of ethical governance, which is less an external constraint and more an internal imperative for legitimate operational authority. The missing element is how to practically enforce these high-level leadership mandates across diverse institutional cultures without creating regulatory gridlock or stifling the very innovation they seek to govern.