A series of briefings that take a "bite-size" look at international trends in different jurisdictions,
drawing on Baker McKenzie's expert financial services practitioners.
July 2023 Ed. No. 12
Bite-size Briefings: Artificial Intelligence
Over recent years, developing artificial intelligence (AI) and machine learning technology has seen
gradual adoption within financial services, for example, in credit scoring, to automate assessments of
creditworthiness. Other use cases such as robo-advice have developed less quickly than expected.
However, the emergence last year of generative AI capable of human-like text that can analyze vast
amounts of data and create new content has caught the public's imagination and turbocharged
interest in potential use cases together with concern over the inherent risks. For our part,
Baker McKenzie in "The Next Decade in Fintech" has explored with experts in the field how AI in
financial services is likely to evolve in the years to come. In this edition of Bite-size Briefings, we
take a bite-size look at the latest developments concerning AI regulation as it affects financial services
in Australia, the EU, Hong Kong SAR, Singapore, Thailand, the UK and the US. Currently, the EU is
furthest along the road to developing specific AI legislation of general application and, given the size
of its market, this may set the tone elsewhere, while other jurisdictions and their regulators are busy
publishing principles and guidance. The mischief sought to be addressed is nonetheless the same
including governance, lack of explainability, as well as the risk of bias and discrimination.
Australia
AI continues to enhance capabilities in the Australian financial services, banking, capital markets,
superannuation, insurance and payments industries. Australia has historically taken a
technology-neutral position on regulating new forms of technology in the financial sector. The financial
services, payments and prudential regimes are largely principles-based, such that they operate in a
technology-neutral way. From time to time though, Australian regulators have provided specific
guidance corresponding to the specific technology in question. For example, the Australian Securities
and Investments Commission (ASIC) has released guidance on robo-advice.
AI ethics
In 2019, the Australian government released the Australian AI Ethics Framework consisting of eight
voluntary Ethics Principles consistent with the Organization for Economic Co-operation and
Development's (OECD) Principles on AI. Financial services institutions in Australia were key
participants in the Australian AI Ethics Principles pilot. Recently, Australian retail banks have pushed
to specifically regulate the use of AI within the financial services ecosystem. For example, in April
2023 key executives discussed generative AI (via large language models), with retail bank executives
supporting the work of the government under the National Science and Technology Council (NSTC),
with some executives suggesting that Australia would need AI legislation. These banks are already
deploying AI under their own internal ethics standards and governance processes.
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Regulation
The government has shown its commitment to regulating AI in a fit-for-purpose manner, with the
NSTC commissioned to help shape a policy response to AI, holding out the potential for new
legislation to regulate the use of AI such as generative AI. The government has also worked with
Australia's national science agency, the CSIRO, to launch the Responsible AI Network. This
network has been put in place to support Australian companies in using and creating AI ethically and
safely, centered around six core pillars — law, standards, principles, governance, leadership and
technology. Further, in the 2023-24 Federal Budget, the government dedicated AUS 101.2 million to
support business in integrating quantum and AI technologies into their operations.
On 1 June 2023, the government released its discussion paper on "Safe and Responsible AI in
Australia." This considers how the existing regulatory frameworks might provide safeguards for the
use and implementation of AI, including under financial services laws. The paper also identified
opportunities to fine-tune governance settings to make it easier for businesses to invest confidently in
AI-enabled innovations, and the importance of harmonizing the governance framework with those
globally. It proposes a draft risk management approach for managing AI risk that looks to the differing
levels of risk in various AI applications. It is likely that this consultation will lead to regulatory reform.
Regulators
The Australian regulators have also indicated that AI is a key area of interest. ASIC identified in its
2022/2023 plan for supervision of market intermediaries that it would undertake a thematic review of
AI and machine learning practices and that associated risks and controls was a priority. In its project
to modernize the prudential regulatory framework, the Australian Prudential Regulation Authority
noted that its framework must be more adaptable to cater to new risks and opportunities arising out of
new technologies such as AI. The Reserve Bank of Australia has linked advances in science and
technology, including the use of AI, as an aide to productivity growth while indicating the considerable
uncertainty around this. Further, reviews of the Privacy Act 1988 (Cth) have considered whether
there need to be specific rules around AI, such as an obligation to notify individuals if their data is to
be used for automated decision-making, and once a decision has been made, whether there should
be a right or obligation to give meaningful information about how that decision is made.
The key takeaway for financial institutions considering AI implementation is to watch this space for
regulatory reform and to engage on the policy discussions with regulators.
EU
In the EU, there is no legislation or regulation specific to the financial services sector focused on AI.
Generally speaking, EU legislative measures applying to financial services are technology-neutral.
However, there are several initiatives from the EU Commission that relate to AI in financial services.
Most significantly, the EU Commission has launched a package of measures to support the rollout of
AI across EU member states, and as part of this initiative, on 21 April 2021 the Commission published
a proposal for regulation governing the use of AI (the AI Act). This legislation, if passed, would
impose significant obligations around the use of AI in many industries, including financial services. To
complement the AI Act, the Commission also published a proposal in September 2022 to harmonize
national liability rules related to AI systems.
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AI Act
The AI Act will harmonize rules for the development, placement on the market and use of AI systems
in the EU across a number of industries and sectors, including financial services. Requirements and
obligations will apply on a sliding scale basis to use cases categorized into four levels of risk following
a proportionate risk-based approach; in the financial services sector, relevant high-risk use cases
include AI systems used to evaluate creditworthiness or establish credit scores. Mandatory
governance and transparency requirements will apply to high-risk use cases; these requirements will
include risk management, data governance, record-keeping, human oversight, accuracy, robustness
and cybersecurity, transparency, and information provision obligations. For banks, some of the
governance, monitoring and risk management requirements will be integrated into, and enhance, the
obligations on internal governance arrangements, processes and mechanisms set out in the Capital
Requirements Directive. The AI Act is still progressing through the legislative process and may
change: trilogue negotiations have just begun, and the regulation is not expected to be finalized until
around early 2024.
European Supervisory Authorities
The European Supervisory Authorities are also pursing AI-related workstreams in their individual work
programs. The European Banking Authority's (EBA) work program for 2023 includes enriching the
existing risk analysis and mapping of use cases of AI in finance, including by clarifying supervisory
expectations on specific use cases, within its innovation and fintech activities. The European
Securities and Markets Authority's work program for 2023 sets out AI and machine learning as key
analytical priorities (among others) feeding into its financial innovation and product risk analysis; a 4
July 2023 speech delivered by José Manuel Campa, EBA chair, on fintech and the future of financial
intermediation confirmed that the EBA is focusing on the use of AI in creditworthiness assessments in
particular, as it is expected that this use case will be classified as "high risk" under the AI Act once
finalized. The European Insurance and Occupational Pension Authority's 2023-2025 work program
and planned activities for 2023 include several AI related tasks, including work on development of a
sound regime for the use of AI by the insurance sector to accompany the EU Commission's proposed
AI legislation and a possible set of complementary guidelines.
Hong Kong
Hong Kong's financial services regulatory regime is service-based and there is no single super-
regulator. The regulatory status of an institution (e.g., bank or financial intermediary) determines
which regulator has primary responsibility for overseeing its activities from both a prudential and a
business conduct perspective.
Although there is limited AI-focused legislation/regulation in Hong Kong, this does not mean that AI
otherwise operates in a vacuum. For each AI solution deployed, a financial institution will need to
comply with all applicable laws (which may include financial services, consumer and competition laws,
among others).
AI regulation
Both the Hong Kong Monetary Authority (HKMA) and the Securities and Futures Commission (SFC)
have issued guidance on using AI. This sets out their expectations over how regulated institutions
may use AI while still complying with their obligations under relevant legislation, including the Banking
Ordinance, and the Securities and Futures Ordinance.
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The HKMA published high-level principles regarding AI on 1 November 2019. They are not intended
to be overly prescriptive, given the evolving nature of AI and the manner in which it is applied,
implemented and ultimately overseen in practice. Key areas include:
− Governance: The board and senior management are accountable for all AI-driven decisions,
particularly in light of the "self-learning" capabilities of certain AI applications. Accordingly, they
should ensure they put in place a proper governance framework and risk management measures
to oversee the use of AI applications.
− Application design and development: Banks should adopt an effective data governance
framework to ensure that the data used to train AI models is of good quality and assessed on
appropriately defined data quality metrics (covering factors such as accuracy, completeness,
timeliness and consistency). They should also perform rigorous validation and testing of trained
AI models to confirm their accuracy and appropriateness before they are deployed for production
use, preferably using an independent party.
− Consumer protection on the use of big data analytics and AI.
Following feedback from the banking industry, in November 2019, the HKMA also issued a set of
guiding principles on consumer protection relating to the use of big data analytics and AI (BDAI).
These focus on governance and accountability, fairness, transparency and disclosure, data privacy
and protection. The HKMA expects banks to adopt a risk-based approach commensurate with the
risks involved in their BDAI applications. The Hong Kong Institute for Monetary and Financial
Research, the research arm of the Hong Kong Academy of Finance, has also released an applied
research report, titled "Artificial Intelligence and Big Data in the Financial Services Industry: A
Regional Perspective and Strategies for Talent Development."
SFC — robo-advising
In March 2018, following a public consultation, the SFC issued new Guidelines on Online Distribution
and Advisory Platforms. Originally planned to take effect in April 2019, the Guidelines took effect in
July 2019 (see here). They apply to online distribution and advisory platforms for investment products
operated by licensed or registered persons and establish six core principles with which platform
operators are expected to comply. In addition to these general requirements, Chapter 4 of the
Guidelines specifically addresses the provision of robo-advice, an area where AI is increasingly being
used. The SFC's expectations in many areas are broadly similar to those of the HKMA.
Ongoing AI review and adoption
The HKMA continues to encourage AI and provide updates on use cases including as part of its
"Regtech Knowledge Hub," which promotes greater sharing of regtech adoption experience and
expertise within the regtech ecosystem in Hong Kong. One of the initial use cases highlighted through
the hub included AI solutions for corporate loan credit risk assessment. The hub was formed as part
of the HKMA's two-year regtech promotion roadmap announced in November 2020 to promote
regtech adoption. The Hong Kong Office of the Privacy Commissioner for Personal Data has also
recently published a letter to highlight the privacy and ethical risks involved in generative
AI-powered chatbots.
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Singapore
The Singapore financial industry has adopted AI in various forms and for a number of years — from
internal risk management purposes (e.g., onboarding of clients, assessing credit risk and fraud
prevention), to client-facing tools (e.g., chatbots) and AI-driven solutions and products (e.g., robo-
advisers), among others. This trend is expected to continue and potentially at a more rapid pace.
Regulatory approach
As the financial regulator in Singapore, the Monetary Authority of Singapore's (MAS) approach toward
AI can be summarized as a "pro-innovation, risk-sensitive approach." An example of MAS' "pro-
innovation" approach can be seen in the robo-advisory space. In response to the proliferation of robo-
advisory solutions in the last five years, MAS has adjusted its regulations to address specific risks
arising from algorithm-based technologies forming the core of the robo-advisory offering. At the same
time, MAS took care to ensure that regulations did not stifle the introduction of such an alternative
product and service offering to a wider group of investors. In this regard, MAS issued the Guidelines
on Provision of Digital Advisory Services in 2018, which set out its views on how robo-advisors could
comply with existing regulatory standards. At the same time, MAS introduced several exemptions,
such as the exemption from the need to hold a fund management license for portfolio rebalancing and
the exemption from the need to hold a license for dealing in capital markets products if trade orders
are passed to another appropriately licensed entity, to reduce the regulatory burden on robo-advisors.
An example of MAS' "risk-sensitive" approach can be seen in its reaction toward the advent of digital,
non-face-to-face client onboarding by financial institutions. MAS issued circulars, first in 2018 and
then subsequently in 2022, to guide the industry on the measures that financial institutions are
expected to take to address anti-money laundering and counter-terrorism financing risks arising from
non-face-to-face onboarding. These measures include the expectation to place appropriate controls
during the videoconferencing process to verify the identity of the customer and the authenticity of
identification documents sighted via videoconferencing (including, where appropriate, conducting a
sum digit test) and the need to commission an independent assessment to certify the effectiveness of
new technology solutions in managing impersonation and fraud risks.
AI principles and governance
What perhaps has the widest scope of application, albeit in a nonbinding form, are the Principles on
the use of AI and data analytics (AIDA) issued by the MAS in 2018. The principles aim to provide
firms with a set of foundational principles to consider when using AIDA in decision-making in providing
financial products and services. In summary, MAS encourages firms to consider the principles of
fairness, ethics, accountability and transparency (FEAT) when assessing existing or developing new
internal frameworks to govern the use of AIDA.
In February 2022, MAS released the Veritas Toolkit version 1.0, which focused on the assessment
methodology for fairness. In June of the same year, MAS released an information paper, where it
shared observations and good practices noted during its AI thematic review of financial institutions.
More recently, in June 2023, MAS issued Veritas Toolkit version 2.0, an open-source toolkit designed
specifically for the financial industry to help financial institutions carry out assessment methodologies
for the FEAT principles, covering beyond the principles of fairness as seen in version 1.0.
For financial institutions, it should be borne in mind that AI regulations are cross-sectoral and will
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likely remain so. For example, the Infocomm Media Development Authority and the Personal Data
Protection Commission (PDPC) have jointly released a Model AI Governance Framework, which
provides that organizations using AI in decision-making should ensure that the process is explainable,
transparent, fair and human-centric. In developing the principles, MAS has also reiterated that they
are meant to complete the PDPC's Model AI Governance Framework.
Looking forward
With continued but increased and rapid adoption of AI, the impact on the financial industry is likely to
become more widespread. With this, we expect to continue to see incremental refinement and
extension of existing regulatory guidance to accommodate and address risks from advances in AI
technology. Some aspects of the non-binding guidance provided by MAS could potentially find their
way into some form of regulations in the mid to longer term. We also envision that financial institutions
will increasingly be expected to consider use of AI more substantially in their internal risk
management framework, governance and control.
Thailand
Development of the regulatory framework in Thailand for technology and digital transformation has
moved slowly compared with the exponential growth of digital technology adopted by financial market
participants. The pace of digital adoption, particularly in new technologies such as AI in Thailand's
financial services sector, has dramatically accelerated in the post COVID-19 era. This has propelled
regulators to establish a robust regulatory regime to maximize the impact of AI and other emerging
digital technologies on the Thai financial markets.
National AI Strategy and Action Plan
In response to Thailand's rapidly evolving technology landscape, on 26 July 2022, the government
approved the National AI Strategy and Action Plan (2022-2027) with a vision to enhance Thailand's
economy and improve the quality of life by building an effective ecosystem that facilitates
development and adoption of AI systems in strategic sectors and industries. The National AI Strategy
and Action Plan will be implemented with five key strategies, namely: (1) preparing Thailand's
readiness in society, ethics, law and regulation for AI application; (2) developing national
infrastructure for sustainable AI development; (3) increasing human capability and improving
education on AI; (4) driving AI technology and innovation development; and (5) promoting AI usage in
the public and private sectors.
The National AI Strategy and Action Plan covers use of AI in the financial sector. By 2027, the
authorities expect to develop clearly defined policies and regulations governing the use of AI in three
main areas, namely: (i) introduction of credit sourcing models for the analysis and assessment of
customer financial status and liabilities; (ii) integration of chatbot with customer relations management
(CRM) systems to develop an efficient response system that streamlines customer service
operations; and (iii) leveraging AI to assist the financial sector in identifying irregular activities and
abnormal transactions, e.g., anti-money laundering monitoring process.
Banking regulation
The Bank of Thailand (BOT), as the main regulator of the Thai banking sector, published a
consultation paper to seek public and stakeholder feedback on its scheme to reposition Thailand's
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financial landscape to secure a sustainable digital economy. A majority of respondents agreed with
the BOT's principle to implement measures to strike a balance between promotion of innovation and
management of risks, as Thailand transitions towards a digital economy and sustainable growth.
Stakeholders also view that the BOT should proactively establish guidelines on the use of data, AI
and gamification techniques in the designing of financial products and services, to incentivize
customers to adopt sustainable financial behavior.
Ethics guidelines
Thai regulators' interest in AI has been evident throughout the recent years. In 2021, the Ministry of
Digital Economy and Society (MDES) proposed the country's AI ethics guideline to ensure the proper
use of advanced technologies, addressing governance issues relating to transparency, bias, privacy,
accountability and safety, which is in line with international standards established by the OECD.
Additionally, in October 2022, the MDES also held a public hearing on regulations governing use of AI
in each sector. One of the topics discussed in the hearing was prohibited uses of AI, e.g., any activity
that may lead to unfair treatment or discrimination, including social scoring.
As Thai market participants navigate emerging trends by exploring and accelerating the adoption of
new technology in order to drive growth, reduce costs and increase efficiency, the government and
relevant regulators are in the process of developing an AI regulatory framework to keep pace with the
technological evolution in the financial industry that market participants should be looking out for.
UK
There is no specific legislation or regulation focused on AI in the UK. A government white paper
launched on 29 March 2023 proposes a cross-sector, principles-based approach to AI regulation,
centered on five principles for regulators to consider how best to facilitate the safe and innovative use
of AI in the industries they monitor:
− Safety, security and robustness
− Transparency and explainability
− Fairness
− Accountability and governance
− Contestability and redress
Instead of taking a single-regulator approach under an AI-specific regulatory regime, the government
will support sector regulators to implement bespoke regulatory requirements building off the
framework set out in the white paper, with further guidance to follow (and, in due course, the
introduction of a statutory duty on regulators requiring them to have due regard to the principles).
However, this does not mean that AI operates in a vacuum. For each AI solution deployed, a financial
institution will need to comply with all applicable existing laws (which may include financial services
laws, consumer laws and competition laws, among others). The financial services regulatory
framework in the UK is technology-neutral, and there has been little specific guidance from the
Financial Conduct Authority (FCA) on regulatory compliance relating to AI. The use of AI by financial
services firms in the UK must not conflict with a firm's regulatory obligations. These include, for
example, the requirements to conduct business with due skill, care and diligence; to pay due regard
to the interests of its customers and treat them fairly; and to pay due regard to the information needs
of its clients and communicate information to them in a way that is clear, fair and not misleading.
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UK regulatory approach
Both the FCA and the Prudential Regulation Authority (PRA) have publicized their intention to engage
with the financial services sector on AI, to understand how its use affects risks to safety and
soundness, and to enable safe and ethical deployment. The FCA considers technological innovation
(including AI) as a key driver of change across financial services and has highlighted as a key issue
the potential for AI to affect pricing decisions, which could lead to concerns about unethical data use if
more personalized pricing, especially for insurance and credit products, leads to unfair pricing and/or
some consumers being excluded from the market.
While it has not issued specific guidance as such, the FCA has indicated its approach to the potential
harms arising from the use of AI and machine learning by financial services firms, and is beginning to
focus more intensely on the benefits and risks of AI in the sector. The FCA is focused on the
importance of good culture and governance as a safeguard. Firms that deploy AI and machine
learning must ensure they have a solid understanding of the technology and the governance around
it. The FCA does not employ one universal approach to harm across financial services, and this holds
true for harms arising from the use of AI: specific safeguards will need to be considered on a case-by-
case basis. Explainability, ethics, data bias, data representation, governance and risk management
are key concerns.
The FCA is also implementing AI to help detect financial crime by using supervised machine learning
models to analyze financial crime data returns. The aim is to identify data gaps and better predict
inherent financial crime risk in order to improve supervision.
Other regulatory initiatives
There are a number of other recent regulatory initiatives relating to AI, including:
− The establishment of the joint Financial Services AI Public Private Forum (AIPPF) by the FCA
and the Bank of England (BoE) to better understand the practical challenges and barriers
associated with AI and machine learning in financial services, and to gather views on potential
areas where principles, guidance or good practice examples could help support safe adoption of
these technologies. The AIPPF's final report, published in February 2022, sets out insights, key
findings and examples of best practice in relation to data, model risk and governance (though it
does not set out future regulatory policy).
− A joint October 2019 FCA and BoE report on the use of machine learning within the financial
services industry, setting out key findings and use case examples on the deployment of machine
learning by firms.
− A year-long (2019-2020) FCA collaboration with the Alan Turing Institute on AI, exploring the
transparency and explainability of AI in the financial sector.
− A joint FCA, PRA and BoE discussion paper launched on 11 October 2022, building on the work
of the AIPPF. The discussion paper explores whether the current set of legal requirements and
guidance is sufficient to address the risks and harms associated with AI and how additional
intervention may support the safe and responsible adoption of AI in UK financial services. A
follow-up to the discussion paper is expected in Q4 2023.
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US
Unlike many other countries looking to legislate on AI, such as the EU's proposed AI Act, there is no
current US equivalent. However, this is not to say that the US has not taken substantive action on AI.
The National Artificial Intelligence Initiative Act of 2020 was enacted on 1 January 2021, as part of
the National Defense Authorization Act. Largely, the legislation funds study and coordination efforts
with the primary stated purposes to ensure continued US leadership in AI R&D; lead the world in the
development and use of trustworthy AI systems in public and private sectors; prepare the present and
future US workforce for the integration of AI systems across all sectors of the economy and society;
and coordinate ongoing AI activities across all federal agencies, to ensure that each informs the work
of the others.
AI Bill of Rights
In addition, on 4 October 2022, the White House Office of Science and Technology Policy released a
blueprint for an AI Bill of Rights, to help guide the design, development and deployment of AI and
other automated and algorithmic systems so that they may protect the rights of the American public.
The blueprint lays out five commonsense protections that all Americans should be entitled to:
− Safe and effective systems
− Algorithmic discrimination protections - to protect from inherent biases in these systems
− Data privacy
− Notice and explanation - to advise when such systems are used and explain how they are
being used
Human alternatives, consideration and fallback - to afford options instead of automated systems,
where appropriate, and access to a person to manage issues encountered.
SEC approach
Focusing on financial institutions, Gary Gensler, chair of the US Securities and Exchange
Commission (SEC), in a speech in May 2023, at a Financial Industry Regulatory Authority (FINRA)
conference, acknowledged that banks and other financial institutions had employed AI in various
functions, including compliance work involving vetting new customers or checking for suspicious
transactions. But he noted that despite possible gains in efficiency, the systems used should be
closely monitored to ensure a clear understanding of how risk is being managed and the potential for
biased decisions.
The SEC's Investor Advisory Committee (IAC) in a letter to Chair Gensler dated 6 April 2023, shared
that it had previously stressed the importance of providing ethical guidelines for AI and algorithmic
models used by investment advisers and financial institutions. On the basis the SEC has authority
under the Investment Advisers Act of 1940, and focusing on investment advisers, the IAC encouraged
the SEC to develop guidance on the use of AI, to include the following tenets to support better
financial outcomes for all: equity; consistent and persistent testing; and governance and oversight.
The IAC also called for further SEC guidance or policies on ethics in AI to incorporate these tenets, as
informed by investors, market participants and frameworks developed by other regulators to mitigate
possible bias in investment adviser algorithms.
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We can expect to see some of this guidance when the SEC issues its anticipated rules on broker-
dealer and investment adviser digital engagement practices and the related analytical and
technological tools that registrants use to learn about and provide advice to their clients. In August
2021, the SEC issued a long and detailed request for information and comment (RFI) in an effort to
inform its rulemaking process. AI and machine learning were among the topics considered in the RFI
and were clearly on the mind of Chair Gensler, as he has addressed those issues specifically in
multiple speeches, more recently, as noted above, and at the time.
Thus, we can anticipate rulemaking from the SEC in this area, perhaps as early as the start of Q4
2023; and it remains to be seen whether the US Congress will continue to rely on existing laws and
legal duties to regulate AI or whether it will enact specific legislation; the US Senate having recently
held hearings on the regulation of AI generally across business and generative AI in particular.
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