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Mapping Hong Kong's Financial Ecosystem: A Network Analysis of the SFC's Licensed Professionals and Institutions

Abdulla AlKetbi, Gautier Marti, Khaled AlNuaimi, Raed Jaradat, Andreas Henschel

TL;DR

The first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission is presented through the lens of complex network analysis, with preliminary findings offering new insights into the dynamics of Hong Kong's financial landscape.

Abstract

We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with daily granularity, provides a unique view of the evolving social network between licensed professionals and their affiliated firms in Hong Kong's financial sector. Leveraging large language models, we classify firms (e.g., asset managers, banks) and infer the likely nationality and gender of employees based on their names. This application enhances the dataset by adding rich demographic and organizational context, enabling more precise network analysis. Our preliminary findings reveal key structural features, offering new insights into the dynamics of Hong Kong's financial landscape. We release the structured dataset to enable further research, establishing a foundation for future studies that may inform recruitment strategies, policy-making, and risk management in the financial industry.

Mapping Hong Kong's Financial Ecosystem: A Network Analysis of the SFC's Licensed Professionals and Institutions

TL;DR

The first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission is presented through the lens of complex network analysis, with preliminary findings offering new insights into the dynamics of Hong Kong's financial landscape.

Abstract

We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with daily granularity, provides a unique view of the evolving social network between licensed professionals and their affiliated firms in Hong Kong's financial sector. Leveraging large language models, we classify firms (e.g., asset managers, banks) and infer the likely nationality and gender of employees based on their names. This application enhances the dataset by adding rich demographic and organizational context, enabling more precise network analysis. Our preliminary findings reveal key structural features, offering new insights into the dynamics of Hong Kong's financial landscape. We release the structured dataset to enable further research, establishing a foundation for future studies that may inform recruitment strategies, policy-making, and risk management in the financial industry.

Paper Structure

This paper contains 25 sections, 5 equations, 4 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Dataset Description
  3. Origin of the Dataset
  4. Dataset Acquisition and Overview
  5. Exploratory Data Analysis
  6. Key Statistics
  7. License Types and Professional Specializations
  8. Job Market Dynamics: License Creations and Terminations
  9. Firm Licensing Structures and Top Entities by Licensee Count
  10. Further Opportunities for Exploration
  11. Data Enrichment using Large Language Models
  12. Country of Origin
  13. Gender
  14. Buy-Side vs. Sell-Side
  15. Firm Classification
  16. ...and 10 more sections

Figures (4)

  • Figure 1: Overview of License Distribution and Dynamics in Hong Kong's Financial Sector. The left panel shows the distribution of regulated activities, highlighting the centrality of securities trading. The right panel illustrates trends in license issuance and termination, reflecting the industry's response to major events.
  • Figure 2: Licenses Issued vs. Terminated in Hong Kong for UK expatriates
  • Figure 3: Key Network Properties of Hong Kong's Financial Ecosystem: (a) Degree distribution comparison between real and random networks; (b) Visualization of employee network clustering.
  • Figure 4: Top 10 Countries of Origin