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

doi:10.1007/978-3-031-82431-9_21

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	British English
Title of host publication	Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications
Subtitle of host publication	COMPLEX NETWORKS 2024 - Volume 2
Editors	Hocine Cherifi, Murat Donduran, Luis M. Rocha, Chantal Cherifi, Onur Varol
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	251-263
Number of pages	13
ISBN (Print)	9783031824302
DOIs	https://doi.org/10.1007/978-3-031-82431-9_21
State	Published - 2025
Event	13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024 - Istanbul, Turkey Duration: 10 Dec 2024 → 12 Dec 2024

Publication series

Name	Studies in Computational Intelligence
Volume	1188 SCI
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

Conference

Conference	13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024
Country/Territory	Turkey
City	Istanbul
Period	10/12/24 → 12/12/24

Keywords

financial ecosystem
professional network
regulatory data

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-82431-9_21

Cite this

AlKetbi, A., Marti, G., AlNuaimi, K., Jaradat, R., & Henschel, A. (2025). Mapping Hong Kong’s Financial Ecosystem: A Network Analysis of the SFC’s Licensed Professionals and Institutions. In H. Cherifi, M. Donduran, L. M. Rocha, C. Cherifi, & O. Varol (Eds.), Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2024 - Volume 2 (pp. 251-263). (Studies in Computational Intelligence; Vol. 1188 SCI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-82431-9_21

AlKetbi, Abdulla ; Marti, Gautier ; AlNuaimi, Khaled et al. / Mapping Hong Kong’s Financial Ecosystem : A Network Analysis of the SFC’s Licensed Professionals and Institutions. Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2024 - Volume 2. editor / Hocine Cherifi ; Murat Donduran ; Luis M. Rocha ; Chantal Cherifi ; Onur Varol. Springer Science and Business Media Deutschland GmbH, 2025. pp. 251-263 (Studies in Computational Intelligence).

@inproceedings{5021ac6c26c3475c98cea1b60aeab8eb,

title = "Mapping Hong Kong{\textquoteright}s Financial Ecosystem: A Network Analysis of the SFC{\textquoteright}s Licensed Professionals and Institutions",

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{\textquoteright}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{\textquoteright}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.",

keywords = "financial ecosystem, professional network, regulatory data",

author = "Abdulla AlKetbi and Gautier Marti and Khaled AlNuaimi and Raed Jaradat and Andreas Henschel",

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AlKetbi, A, Marti, G, AlNuaimi, K, Jaradat, R & Henschel, A 2025, Mapping Hong Kong’s Financial Ecosystem: A Network Analysis of the SFC’s Licensed Professionals and Institutions. in H Cherifi, M Donduran, LM Rocha, C Cherifi & O Varol (eds), Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2024 - Volume 2. Studies in Computational Intelligence, vol. 1188 SCI, Springer Science and Business Media Deutschland GmbH, pp. 251-263, 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024, Istanbul, Turkey, 10/12/24. https://doi.org/10.1007/978-3-031-82431-9_21

Mapping Hong Kong’s Financial Ecosystem: A Network Analysis of the SFC’s Licensed Professionals and Institutions. / AlKetbi, Abdulla; Marti, Gautier; AlNuaimi, Khaled et al.
Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2024 - Volume 2. ed. / Hocine Cherifi; Murat Donduran; Luis M. Rocha; Chantal Cherifi; Onur Varol. Springer Science and Business Media Deutschland GmbH, 2025. p. 251-263 (Studies in Computational Intelligence; Vol. 1188 SCI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Mapping Hong Kong’s Financial Ecosystem

T2 - 13th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2024

AU - AlKetbi, Abdulla

AU - Marti, Gautier

AU - AlNuaimi, Khaled

AU - Jaradat, Raed

AU - Henschel, Andreas

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

KW - financial ecosystem

KW - professional network

KW - regulatory data

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DO - 10.1007/978-3-031-82431-9_21

M3 - Conference contribution

AN - SCOPUS:105002383813

SN - 9783031824302

T3 - Studies in Computational Intelligence

SP - 251

EP - 263

BT - Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications

A2 - Cherifi, Hocine

A2 - Donduran, Murat

A2 - Rocha, Luis M.

A2 - Cherifi, Chantal

A2 - Varol, Onur

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 10 December 2024 through 12 December 2024

ER -

AlKetbi A, Marti G, AlNuaimi K, Jaradat R , Henschel A. Mapping Hong Kong’s Financial Ecosystem: A Network Analysis of the SFC’s Licensed Professionals and Institutions. In Cherifi H, Donduran M, Rocha LM, Cherifi C, Varol O, editors, Complex Networks and Their Applications XIII - Proceedings of The 13th International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2024 - Volume 2. Springer Science and Business Media Deutschland GmbH. 2025. p. 251-263. (Studies in Computational Intelligence). doi: 10.1007/978-3-031-82431-9_21