On July 6, 2024, the FCA, the core regulatory agency responsible for financial conduct and consumer protection in the UK, described "AI regulation in the financial sector" as an ongoing "competition" during a media interview, openly stating that various parties are vying for the future regulatory narrative of this technology. Unlike past statements that revolved around traditional tools such as licenses and sandboxes, this time the FCA has directly called for expanded authority—hoping to obtain greater supervisory powers over large general models like ChatGPT, Claude, and Gemini, rather than merely applying existing financial rules to "casually" manage the technological applications. Conflicts have also come to the forefront: on one hand, the UK has been emphasizing the creation of a global hub for cryptocurrency and fintech in recent years, using regulatory sandboxes to attract projects for product testing; on the other hand, the EU has already passed a systematic AI Act, while the US is seizing the lead in AI regulation through multiple policy documents and hearing materials. The UK financial regulatory authorities are clearly unwilling to be mere "technology-friendly" bystanders in this race for regulatory standards. As of public information available in October 2024, the FCA’s request for specific legislative authority surrounding large models and AI cryptocurrency projects has yet to materialize, but this "race for regulatory power" that started two years ago now places a core question before all cryptocurrency and fintech projects operating in the UK: whether future compliance boundaries will be drawn according to assets and businesses, or whether the models used will also be included in the regulatory scope for individual review.

Regulatory Arms Race: Why FCA Is Eager to Expand Authority

When the FCA characterized the AI regulation in the financial sector as a "competition" on July 6, 2024, it was not merely making a technical commentary but was revealing a more realistic power struggle: who defines the "safety boundaries" of large models in financial and crypto scenarios. The EU has already provided a complete risk-tiered framework with its AI Act, while the US, despite lacking a unified federal statute, is continuously probing regulatory boundaries through White House documents and hearings. If the UK remains in the realm of principle-based discussions, the FCA’s future is clear — when global rules take shape, it will be compelled to adopt foreign standards, rather than leading the establishment of a localized financial compliance framework for models like ChatGPT, Claude, and Gemini operating in the UK.

This anxiety for expanded authority is directly linked to the UK's national strategy to "build a global hub for cryptocurrency and fintech." In recent years, regulatory sandboxes have helped numerous crypto and fintech teams test applications related to research assistance, code auditing, customer service, automated trading, and risk management in London, and the innovation dividends have begun to manifest. However, from the FCA's perspective, these same tools could also amplify market volatility in milliseconds, produce misleading suggestions in customer service dialogues, and leave systemic risks in code audits, ultimately leading to consumer complaints and systemic risk events. The UK government aims to attract global capital and projects while simultaneously ensuring that licensing, consumer protection, and anti-money laundering frameworks are not "bypassed" by model-driven businesses, which heightens the tension for the FCA between "letting go" and "managing," far exceeding traditional financial regulation dynamics.

In the context of international competition, the FCA's "competition" statement seems more like a dual battle for temporal and spatial dominance: the EU has occupied the regulatory high ground with codified laws, while the US maintains a technological discourse through policy documents and regulatory hearings. If the UK does not grant the FCA clearer supervisory authority concerning large models and AI cryptocurrency projects, it may long find itself in a passive position regarding cross-border business and standard output. As of October 2024, public information still shows that these expansion requests have not yet translated into specific regulatory texts, but the regulatory direction is clear enough — the essence of this regulatory arms race is the FCA’s attempt to shift from being a "rule adopter" to a "rule maker," and all cryptocurrency and fintech projects operating in the UK will be caught up in this role transformation.

From Large Models to Trading Bots: Crypto Scenarios the FCA Might Focus On

In the City of London, large models have quietly embedded themselves into the daily processes of crypto and capital markets: ChatGPT, Claude, and Gemini are used to generate first drafts of research reports, organize on-chain and macro information, and perform code audits, which are then manually reviewed before entering investment decisions; customer service teams use models to answer users' inquiries about product risks and fee structures, attempting to reduce costs and improve efficiency without crossing the line of "personalized investment advice." On the other end, crypto trading platforms and quantitative funds continue the tradition of algorithmic trading developed over years, beginning to incorporate more complex machine learning models in automatic ordering, risk parameter adjustments, and market signal identification, transitioning large models from merely "writing copy" to "timing assistance" and "portfolio adjustment support."

Once the FCA gains clearer regulatory authority over large models, these institutions already within regulatory sight will likely be prioritized under scrutiny: digital asset service providers licensed by the FCA in the UK using models to generate market interpretations or strategy suggestions for retail clients could be questioned on whether they are essentially providing investment advice derived from model processing; fintech companies testing products related to digital assets in the regulatory sandbox that attempt to drive automated trading or intelligent risk control using large models might be regarded as "high-risk innovations" and may be required to disclose additional information and undergo stress testing; large crypto trading platforms and quantitative funds using algorithmic trading and machine learning models may also need to provide the FCA with detailed explanations of how their models manage risks and how they avoid misleading outputs or systemic errors. It should be emphasized that as of October 2024, the FCA has not released any "list of AI applications requiring regulation," and the aforementioned scenarios should be considered reasonable projections; those involved must maintain a speculative tone when developing specific projects and business cases, framing them as potential review directions rather than established regulatory facts.

The Gap in Licensing Framework: New Obligations That AI Crypto Projects May Face

Over the past decade, UK fintech and crypto businesses have grown accustomed to the relatively clear "entry rules" set by the FCA: anyone selling products to retail customers, holding customer funds, or providing payment or lending services must obtain the corresponding authorization or enter the regulatory sandbox, allowing regulators to assess business models, technical solutions, and risk exposures in a controlled environment. Payments, lending, wealth management, and certain projects related to digital assets have already undergone "laboratory-style" regulatory testing under this sandbox system. Surrounding these authorizations and testing arrangements, the FCA has consistently emphasized preventing misleading sales, requiring product risks to match customer capabilities, and having formed compliance expectations for marketing to retail investors, suitability assessments, and complaint handling. However, when large models are embedded in research, customer service, automated trading, and even compliance assistance, this licensing framework, centered on "institutions + products," suddenly reveals several key gaps: regulatory documents rarely address the transparency of the models themselves, there are almost no direct requirements for disclosing the legal basis of training data, and there is no systematic answer to a key question — when decision-making heavily depends on AI outputs, where does the responsibility lie, with the platform, the model provider, or some invisible technical team?

It is also in these gaps that the FCA's request for expanded authority has been interpreted by the industry as a potential outline of new obligations that may arise in the future. For crypto projects operating in the UK that are also using large models, when applying for licenses or entering a sandbox, they may no longer only be questioned about "what you sell" and "how you receive customer funds," but will also need to prepare a comprehensive explanation regarding model governance: for instance, explaining to regulators how models participate in decision-making at various business stages, how to control the risks of misleading sales arising from "black box decisions" and unpredictable outputs, the categories from which training data is sourced, whether it complies with existing data protection and financial regulatory requirements, and what human review and deactivation mechanisms are in place in the event of bias or systematic errors. In a more radical scenario, the FCA may require large models in high-risk scenarios to undergo independent algorithm audits and produce reports similar to a "model risk assessment," or even incorporate the processes for regular model review and updates into the company's licensing compliance obligations. It should be noted that as of October 2024, the FCA has not released specific regulatory clauses or timelines for large models and AI cryptocurrency projects; the potential disclosure, risk control, and auditing requirements mentioned above are merely hypothetical, based on its demands for expanded authority and global regulatory discussions. The actual rewrite of the UK licensing framework will depend on political maneuvers and technological understanding evolving in the legislative and regulatory processes in the coming years.

Cross-Border Compliance Overlay: How UK Standards Affect Global Platforms

As a key global financial center, London has long been a critical node for institutional and high-net-worth client-facing crypto trading, custody, and research operations; much of the high-end client traffic from Europe, the Middle East, and even Asia ultimately funnels into the UK or EU markets. When the FCA publicly describes AI regulation in the financial field as a "competition" and seeks to gain more regulatory narrative over large models like ChatGPT, Claude, and Gemini, this "competition" effectively transforms into a cross-border standard contest: whoever establishes the compliance baseline for AI + crypto business in the London and UK markets first indirectly sets new thresholds for technology and data governance for global institutional business. For platforms seeking to obtain licenses or access London funds, they must not only meet traditional licensing, supervision, and sandbox testing requirements but also anticipate that the use of AI models, the sources of training data, and the logic of risk control will be viewed as part of the licensing review process.

Simultaneously, the EU has passed its AI Act, implementing a risk classification and corresponding obligations for businesses providing or deploying AI systems for the EU market, compounded by GDPR, anti-money laundering, and anti-terrorism financing regulations, forming a complete compliance "stack." When crypto platforms operate in the UK and the EU, they already need to handle licensing applications, anti-money laundering arrangements for trading and custody operations, and ensure data collection, labeling, and storage comply with legal requirements. Once the FCA accelerates its standards in the AI regulation "competition," cross-border institutions often must adopt a "highest standard priority" strategy — using the compliance requirements of the UK and the EU as the unified template for technology, processes, and corporate governance, before descending these to other jurisdictions. In this environment of concurrent multihead regulation, regulatory arbitrage and business migration become real options: some projects may choose to avoid stricter markets like the UK and the EU, or alter their technological structures, company registrations, and service boundaries to reduce regulatory exposure, but the cost is the proactive abandonment of high-value clients and funding sources from London and even the EU. A new game between platforms and regulators is taking shape, and the next round of competition in cross-border business may revolve around who can maintain the continuity of their global business map under the compliance overlay pressures of the UK and the EU at manageable costs.

Time Window and Self-Help Path: What AI Crypto Teams Can Do Now

Two years ago, when the FCA characterized AI regulation in the financial sector as a "competition" and publicly contended for regulatory authority over large models like ChatGPT, Claude, and Gemini, this step pulled UK-focused AI + crypto projects into a new watchlist. However, as of October 2024, these expansion requests remain at the level of directional signals rather than formal obligations. For project parties, the potential impact pathways are roughly clear: once the FCA is granted new regulatory powers, future UK licensing approvals, sandbox admissions, and consumer protection rules may very well include "whether and how large models are used" as a review dimension, requiring verifiable documentation on model governance, data protection, and risk control; however, when this will happen and which specific regulations it will be incorporated into are currently substantially uncertain. During this window of uncertainty, downstream writing and business decisions must strictly adhere to one red line: clearly distinguishing between regulatory actions that have already occurred (for example, the FCA's public expansion of authority itself) and scenario projections based on trends; all judgments regarding "how it might be regulated in the future" should be treated as strategic hypotheses rather than current rules. Amid tightening global regulation, the EU's AI Act serving as a reference framework, and the UK actively seizing AI regulatory authority, what platforms, project parties, and intensive users can currently do for self-help is largely principled preliminary planning — systematically reviewing their usage of large models across research, code auditing, customer service, trading, and risk control, enhancing model explainability, data protection, risk control audits, and human-machine collaboration mechanisms per international recommendations, and closely monitoring whether the FCA releases consultation documents, inter-agency joint statements, or updates to licensing guidelines about large models, using these "boundary signals" to decide whether to continue deepening their engagement in the UK market or redefine their business safe boundaries between cost and compliance.

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