How Capital Markets teams in Hong Kong automate repetitive work with AI while respecting the PDPO and sector rules — implemented by dgm on osFoundry.
dgm is an independent osFoundry integration partner — not affiliated with osFoundry’s maker (OS LLC), and dgm has no completed client integrations yet.
Automation is where AI pays for itself in capital markets — but the goal is a measurable reduction in manual work on a specific workflow, not ‘AI everywhere’. Here is a sensible way to approach it in Hong Kong.
What to automate first in capital markets
Good first candidates are high-volume, repeatable and text- or data-heavy: AI research summarisation, trade surveillance and market-abuse detection and document and disclosure automation are typical. Avoid starting with one-off or highly bespoke work — the return is harder to prove.
A practical automation sequence
- Pick one repetitive capital markets workflow — for example AI research summarisation — and write down the current steps and time spent.
- Set a baseline so you can measure improvement, and confirm where the data lives and whether it must stay in Hong Kong.
- Build a small automation with a human in the loop, check its output against the regulator expectations that apply, then expand.
| Stage | Focus |
|---|---|
| Scope | One workflow, current steps, time spent |
| Baseline | Measurable starting point + data-residency check |
| Pilot | Human-in-the-loop build, checked against compliance |
| Expand | Roll out once value is proven |
Compliance while you automate
Licensed corporations are regulated by the Securities and Futures Commission (SFC), whose November 2024 circular (ref 24EC55) sets four core principles for using AI language models — senior-management oversight, model risk management, cybersecurity and data risk, and third-party risk — with extra requirements for high-risk uses such as investment advice. Hong Kong is a leading international capital market, so AI used in regulated activities must meet the SFC’s circular — including human-in-the-loop review before AI output reaches an investor, and disclosure that the user is interacting with AI. Because there is no standalone binding AI Act in force in 2026, the constraints to design around are the PDPO (collection, use, security and the PCPD’s AI Model Framework recommendations) and the sector rules above.
Keeping automation in Hong Kong
Client and market data favour controlled, in-region or self-hosted environments. osFoundry’s managed cloud pins data to the US, EU or Japan — it does not currently offer a Hong Kong managed region (its nearest managed region is Japan). To keep data in Hong Kong, the honest path is self-hosting osFoundry (BYO Cloud) inside a Hong Kong cloud region such as AWS Asia Pacific (Hong Kong) ap-east-1, Microsoft Azure East Asia (Hong Kong SAR) or Google Cloud asia-east2 (Hong Kong), or running models locally on-device. osFoundry can run your chosen model under one layer and be self-hosted in a Hong Kong region or run locally for sensitive workflows.
Where dgm fits
dgm is an independent integration partner that helps Hong Kong businesses adopt osFoundry — scoping a first use case, handling the build, and connecting AI to the systems you already run. dgm can build the first capital markets automation with you and keep a human in the loop. dgm is independent of osFoundry’s maker (OS LLC) and has no completed client integrations yet, so everything described here is a service offered, not a past result. If you want to scope a practical first project, dgm can help you map it out.