Deep Knowledge Group is pleased to release its latest report “AI for Finance in Hong Kong”, a first-of-its-kind report and ecosystem platform mapping Hong Kong’s AI-for-Finance landscape, with the Financial Services Development Council (FSDC) serving as the Observer. The study profiles 245 key actors shaping applied AI in financial services in Hong Kong—150 companies, 50 investors, 5 hubs, and 30 ecosystem leaders. 

The report finds that Hong Kong’s AI-for-Finance ecosystem has achieved significant scale and end-to-end functional coverage, spanning incumbents deploying AI, specialised AI/FinTech vendors, data and infrastructure providers, investors, and hubs. Density is highest in wealth and investment tooling, digital-asset infrastructure, and analytics services.

The report has identified several key features of the AI-for Finance landscape in Hong Kong:

• End-to-end coverage: Hong Kong’s AI-for-Finance ecosystem now spans the full financial value chain—banking, payments, capital markets, insurance, risk, compliance, and market infrastructure—with growing production deployment across core workflows.
• A uniquely “finance-grade” AI environment: A compact governance architecture and strong supervisory foundations support AI adoption that is auditable, resilient, privacy-aware, and scalable—key requirements for finance.
• Capital-markets gravity + cross-border interface: Hong Kong combines deep capital markets with a distinctive China–international gateway role, creating an ecosystem that can scale solutions regionally while remaining globally connected.
• East-West Bridge and Uniquely Open Technological Architecture: Hong Kong is one of the only global financial hubs where Western LLMs and Mainland Chinese AI models can be accessed, tested, and deployed within the same regulated financial environment.
• Concentration of enabling infrastructure: The ecosystem benefits from dense enabling layers—public institutions, sandboxes/innovation pathways, data-exchange initiatives, and innovation hubs—that shorten the path from pilots to production.
• A platform for international AI-for-Finance growth: Hong Kong increasingly functions as both a deployment market and an international business-development base for AI-for-Finance companies seeking partnerships, clients, and capital.

Leading Segments: Investment and Wealth Management, Blockchain, and Data Analytics at the Forefront of Hong Kong's AI-For-Finance Landscape

The mapped company landscape in this study includes 150 organisations active across multiple AI-for-Finance segments. The largest segments include 38 companies in investment and wealth management, 31 in blockchain and cryptocurrencies, and 27 in data and analytics. 

Other notable sectors include capital markets and trading, infrastructure and technology, and lending and credit. Smaller groups focus on customer experience, B2B financial services, InsurTech, payments, RegTech, risk management, and personal finance. These segments reflect Hong Kong’s strengths in institutional finance, active capital markets, and the data-driven services required for scalable AI deployment.

Hong Kong's Competitive Edge: Regulated Adoption, Cross-Border Connectivity, and Depth in Institutional Finance

The report benchmarks Hong Kong against leading peer hubs and other financial city-hubs, revealing that Hong Kong’s strengths are most visible in regulated adoption capacity, cross-border connectivity, and institutional financial depth. 

The report highlights opportunity zones where these strengths compound, particularly in compliance and RegTech exportability, AI-enabled risk and resilience tooling, cross-border finance connectivity, data-interoperability foundations that shorten time-to-deployment for institutions and vendors, and market infrastructure services that link finance demand with scalable technology supply.

Priority development areas for Hong Kong include strengthening specialised AI-for-Finance talent pipelines, accelerating interoperable data foundations, and broadening AI adoption across a wider base of institutions and service providers. 

Dr King Au, Executive Director of the FSDC, noted, “Understanding AI deployment pathways in finance is essential for maintaining Hong Kong’s long-term competitiveness as an international financial centre. With the city’s strengths in regulated adoption, cross-border connectivity, and institutional financial depth, Hong Kong is uniquely positioned to contribute to the global adoption of AI in financial services.”

“Hong Kong is well poised to scale AI in financial services because it combines deep financial infrastructure with strong governance expectations that support trust,” said Dmitry Kaminskiy, General Partner of Deep Knowledge Group. “This report provides a structured evidence base on where AI is already deployed and which strategic interventions can strengthen competitiveness.”

Transforming Financial Operations: The Integration of AI into Core Functions

Financial services are entering a phase where AI is increasingly integrated into core operations rather than confined to isolated pilots. Institutions are applying machine learning and automation to credit and risk decisions, transaction monitoring and financial-crime controls, market surveillance, claims and fraud detection, and customer operations, while strengthening controls to meet finance-grade expectations for auditability, resilience, privacy and accountability. 

Hong Kong’s opportunity is to combine its international financial centre depth with a governance environment that enables AI adoption safely and at scale. The report translates that opportunity into a mapped ecosystem of actors, use-case domains, and enabling mechanisms that matter for real deployment.

About the Report and Platform

The “AI for Finance in Hong Kong” report is designed for regulators, policymakers, financial institutions, investors, and ecosystem organisations seeking to identify partners, benchmark progress, and understand competitive dynamics in applied financial AI. The platform complements the report by providing a structured knowledge base of mapped entities, supporting filtering by sector and role, and enabling future extensions into benchmarking dashboards and longitudinal tracking.

It provides a structured, decision-maker-friendly evidence base on how AI is being embedded into finance-grade workflows—where adoption is already at production scale, where it remains emerging, and which governance and ecosystem enablers matter most for responsible acceleration. It examines AI deployment and ecosystem structure across five sector deep dives:

• Banking, payments and retail finance
• Capital markets, exchanges and asset management
• Insurance, InsurTech and risk solutions
• RegTech, LegalTech and compliance technology
• Financial market infrastructure, data and analytics providers