Adnan Zaylani Mohamad Zahid: Banking in the era of generative AI
Closing remarks by Mr Adnan Zaylani Mohamad Zahid, Assistant Governor of the
Central Bank of Malaysia (Bank Negara Malaysia), at the3rd Malaysian Banking
Conference 2024, organised by the Asian Institute of Chartered Bankers (AICB) and the
Association of Banks in Malaysia (ABM), Kuala Lumpur, 11 July 2024.
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A very good afternoon and thank you for inviting me to deliver the closing remarks for
the 3rd Malaysian Banking Conference 2024.
Congratulations to the Asian Institute of Chartered Bankers (AICB) and the Association
of Banks in Malaysia (ABM) for organising a productive and insightful conference.
"Banking in the Era of Generative AI", is an apt theme at a time when artificial
intelligence technology is rapidly evolving, with widespread implications for financial
services.
It is an exciting time for technological innovation in the financial sector. The
digitalisation of financial services already promises many new possibilities, more
frictionless experiences and better-customised services for customers. With the advent
of large language models - or LLMs - we have in our hands the capabilities of powerful
AI tools that will further expand these possibilities.
The Malaysian financial sector is well-positioned to capitalise on all these
developments. We benefit from strong financial and telecommunications infrastructure.
Today, over 97% of Malaysians have access to the internet, 95% own a smartphone,
and 96% of adults have an active deposit account.
As the central bank and financial regulator, Bank Negara Malaysia (BNM) has a strong
interest in the digitalisation of financial services. Four years ago, we launched the
Licensing Framework for Digital Banks, and as of today, three of the awarded licensees
have commenced operations. Just this week, we also launched the Licensing and
Regulatory Framework for Digital Insurers and Takaful Operators (DITOs). Indeed,
many of our incumbent players have also embarked on their digitalisation journey. Our
vision is for the financial sector to leverage technology, including AI, to foster market
dynamism and better serve the needs of Malaysians.
The rapidly evolving nature of AI brings forth unprecedented potential benefits and
risks, many of which we have yet to fully comprehend. For example, the rise of LLMs
has propelled generative AI, or GenAI, into mainstream conversations, revolutionising
human-computer interaction by shifting from traditional coding and interfaces to natural
text and speech.
Adoption of AI has significant potential to improve financial services
Undoubtedly, the adoption of AI has significant potential to improve financial services.
Like electricity, the internet, and smartphones, some experts have argued that AI is set
to become the next general-purpose technology, with a real potential to improve our
lives.
Earlier today, you had the opportunity to hear about various AI use cases and
applications - from revolutionising the customer experience in banking to supporting
transition finance. These use cases have the potential to create value for financial
institutions and consumers alike.
In principle, these use cases stem from the AI system's ability to better process higher
volumes and less structured sets of data that would otherwise be impractical to analyse,
delivering superior pattern recognition and predictive capability.
In Malaysia, more than 80% of banks have adopted at least one AI-related project, with
the most common use cases ranging from customer analytics to fraud detection, and
electronic Know-Your-Customer (e-KYC).
We at BNM are also excited about use cases that can advance our policy objectives for
the nation. I will share four notable examples:
First, Project Aurora, developed by the BIS Innovation Hub demonstrated an
effective approach to improving anti-money laundering analysis using
privacyenhancing technologies, machine learning, and network analysis over traditional
methods.
Second, Project Gaia, also developed by the BIS, demonstrated the use of AI and
large language models for climate-related data extraction, which opens up the
possibility of analysing climate-related financial risks at scale.
Third, AI improvements to risk management approaches, such as default
prediction for underserved segments, can increase the potential for financial
institutions to viably achieve inclusion outcomes.
Fourth, in Malaysia, e-KYC solutions driven by AI have significantly increased
customer convenience by facilitating fully digital account opening experiences,
which was a key enabler for financial services, particularly during the pandemic.
Internally, we are also exploring ways in which we can use GenAI to support
supervisory and policy analysis.
However, admittedly we are only at an early stage of our GenAI adoption journey. For
now we have established an AI trust and governance workstream to explore
approaches to deploy AI in a responsible manner. Ethical and responsible use of AI
remains at the centre of our AI strategy. This also means prioritising the development of
expertise to seamlessly integrate responsible AI into existing analytical tools.
AI adoption may intensify existing risks and give rise to new ones
Ladies and gentlemen,
While AI has the potential to revolutionise the financial services industry, AI adoption
may intensify existing risks and give rise to new ones.
Firstly, AI models can exacerbate biases and discrimination, especially in cases
where the underlying input data is flawed or of unknown quality. Strong data
governance and management systems are, therefore, of paramount importance
when embarking on AI projects.
Secondly, the use of self-learning models in the absence of compensating
technical or human controls may lead to unstable model performance, creating
significant challenges for effective model validation.
Thirdly, the use of institutional or public GenAI tools could lead to unintended
increases in non-financial risk, such as increased third party risk arising from
systemic dependencies on a small set of foundation model developers.
Additionally, it may increase the risk of inadvertently disclosing private customer
information.
In addition, external risks arising from the use of AI by malicious actors are likely to
affect organisations regardless of whether they deploy AI systems, introducing new
sources of cyber risk. For example, GenAI has enabled scammers to increase the
sophistication of scam attacks and disinformation campaigns.
Email phishing attempts have become increasingly difficult to distinguish as
GenAI vastly expands hackers' ability to write credible phishing emails.
Malicious actors armed with GenAI tools have also created realistic videos, fake
IDs, and false identities to mislead their target audience. This extends to the
creation of hyper-realistic deepfakes of company executives to prompt unlawful
money transfers.
A heightened prevalence of AI-enabled scams may undermine consumer confidence in
digital financial services. Potentially, this might cause some consumer segments to
withdraw from services like online banking altogether, for fear of falling victim to scams.
This would risk the significant progress we have made in advancing financial inclusion
through digitalisation.
What are the next steps for financial regulators and the industry?
Ladies and gentlemen,
Reflecting on these developments and conversations held today, what ought to be the
best way forward for the financial industry?
To start, many, if not most, of the risks described earlier are familiar to financial
regulators and bankers in the room today. In approaching these risks, we are building
upon existing foundations. Frameworks such as the Risk Management in IT (RMiT)
policy document lay out clear principles for technology risk management and address
risks associated with third-party vendors and service providers. The policy document on
the Management of Customer Information and Permitted Disclosures (MCIPD) likewise
addresses risks to data privacy to consumers.
While our current regulatory framework may not necessarily single out AI as a
technology, it applies to the use of AI systems and is designed to address risks in a
technology-agnostic way.
How, then, do we identify and prepare for risks that are still unknown or emerging?
Globally, financial institutions, regulators and international standard-setting bodies are
generally converging on guiding principles for the responsible use of AI. These include
fairness, inclusivity, transparency, robustness, and accountability. For financial
institutions, responsible AI can be fostered through strong internal governance and risk
management practices.
At our end, BNM is committed to ensuring that our regulatory framework continues to
remain proportionate to risks as we unlock the upsides of innovation. This means
creating a conducive environment where responsible innovation and healthy
competition are nurtured, novel business models and new entrants are given an
opportunity to flourish, and associated risks are managed effectively - especially those
that may threaten system-wide stability, consumer outcomes, and confidence in the
financial sector.
Towards this end, the BNM Regulatory Sandbox can play a key role in facilitating the
testing of innovative AI use cases where there are any existing regulatory impediments.
In such cases, the Sandbox may enable financial institutions to assess the feasibility of
new AI-enabled use cases while providing BNM with insights into both opportunities
and risks associated with these innovations. So far, the Sandbox has played a role in
facilitating the testing of innovative use cases and business models, including digital
remittance, e-KYC, Buy-Now-Pay-Later and digital insurance.
Finally, it is worth highlighting that the financial industry also plays a role in responsible
co-innovation to effectively overcome challenges faced and realise the potential of AI in
finance.
Firstly, the industry can work together to share knowledge, best practices, and AI
tools to lower costs, foster the development of common standards, and elevate
standards of risk management in this emerging area. One example is the
industryled development of AI guidelines and risk management best practices by the
Chief Risk Officers' Forum. We hope to see further similar efforts across the
industry, in addressing areas such as responsible AI use and the development of
tools or standards for addressing fairness concerns.
Secondly, it is key that consumers' digital and financial literacy continue to
improve in line with developments in digital technologies. To this end, financial
institutions and the industry have a bigger role to play in increasing financial
education and awareness. Education will be the first line of defence to protect
consumers against more sophisticated GenAI-enabled scams, improve digital
inclusion outcomes, and strengthen confidence in digital financial services.
Thirdly, the advancements in AI underscore the necessity of evolving and
investing in our talent ecosystem to prepare for the workforce of the future.
Beyond investments in skilled technical developers and IT personnel, we also
need to cultivate a workforce capable of effectively and safely utilising the next
generation of AI tools. In this regard, we look forward to the release of the Future
Skills Framework for the Malaysian Financial Sector later this month, an industry
initiative led by AICB in collaboration with the Islamic Banking and Finance
Institute Malaysia, and the Malaysian Insurance Institute, as a big step forward in
evolving the talent ecosystem in the financial sector.
Conclusion
Ladies and gentlemen,
In closing, to quote Alan Turing, the English computer scientist and arguably one of the
forefathers of AI, "We can only see a short distance ahead, but we can see plenty there
that needs to be done".
AI has the real potential to improve financial services. But it also creates new and
complex challenges. While AI systems today are increasingly adept at mimicking
human intelligence, they are not infallible. It remains essential that human judgment
plays a central role in overseeing and managing risks.
By embracing AI responsibly, ensuring ethical standards and robust security measures,
we can harness its full spectrum of capabilities to build a more resilient and
customercentric financial ecosystem. Let's seize this opportunity to innovate responsibly and
shape a future where AI in finance enhances transparency, security, and accessibility
for all.
Thank you.