Skip to main content
SpringerLink
Log in

Hong Kong’s Fintech Automation: Economic Benefits and Social Risks

  • Chapter
  • First Online:
Regulating FinTech in Asia

Part of the book series: Perspectives in Law, Business and Innovation ((PLBI))

Abstract

This chapter examines the rise of fintech, its regulation, and the particular challenges these present for an international financial center (IFC), specifically an IFC with limited economic breadth. Fintech offers automation opportunities for financial institutions, and such automation will in most cases make banks more competitive and lower their labor needs. The Hong Kong government has actively embraced fintech to ensure competitiveness, and its regulation tracks leading international positions on ICOs, cryptocurrency and electronic payment. However, Hong Kong regulators have not facilitated fintech activities that would stimulate the local economy, such as equity crowdfunding. Automation will generally translate into a reduction of human labor, particularly in mid-level jobs. In a large and varied economy, persons laid off from jobs at banks can seek engagement elsewhere. This is not necessarily true in an IFC with a less diversified economy. Hong Kong presents the highly unusual case of persons in a small IFC who have access to a large and diverse economy in mainland China yet may refuse to seek new positions in the larger workplace for cultural or political reasons. The Hong Kong government has blithely followed a ‘market leads, government facilitates’ philosophy of laissez-faire for decades and thus also has failed to prepare for the social costs of fintech. While such preparation would indeed constitute social planning, an activity generally discouraged in Hong Kong, circumstances dictate that the HKSAR government begin to act socially, rather than merely facilitate the largest businesses.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Z/Yen Group (2007) through (2019) and World Economic Forum (2014) through (2019).

  2. 2.

    CCAF (2019), pp. 15–16.

  3. 3.

    Cambridge Dictionary (2019), ‘automation’.

  4. 4.

    Snyder (2019).

  5. 5.

    KPMG (2017), p. 6.

  6. 6.

    ‘McKinsey Global Institute estimates that the transportation-and-warehousing industry has the third-highest automation potential of any sector.’ Dekhne (2019).

  7. 7.

    ‘[T]he evil that occurs is an inevitable result of the best…. To permit the evil, as God permits it, is the greatest goodness.’ Leibniz (1710), p. 195.

  8. 8.

    Malito (2018).

  9. 9.

    Ford (2015), pp. 32–38.

  10. 10.

    See https://trends.google.com/trends/explore?date=all&q=fintech. Accessed 25 February 2020.

  11. 11.

    See https://trends.google.com/trends/explore?date=now%204-H&q=blockchain. Accessed 25 February 2020.

  12. 12.

    CCAF 2019, pp. 15–18.

  13. 13.

    Soriano et al., p. 23.

  14. 14.

    Gartner 2018.

  15. 15.

    Ernst and Young (2016), p. 24.

  16. 16.

    Davenport 2019.

  17. 17.

    Strogatz (2018).

  18. 18.

    Strogatz (2018).

  19. 19.

    Browne (2018).

  20. 20.

    Rauchs et al. (2018), p. 67

  21. 21.

    For example, the World Bank’s Doing Business Report 2019 ranked Hong Kong 4th out of 190 jurisdictions examined, World Bank (2019) p. 5, and Hong Kong has ranked in first place on the ‘Index of Economic Freedom’ for a quarter-century. Heritage Foundation (1995) through (2019).

  22. 22.

    See Donald (2015), pp. 192–193.

  23. 23.

    Chen and Lee 2017.

  24. 24.

    HKSAR (2016), p. 6.

  25. 25.

    Lam (2018), p. 46

  26. 26.

    Memoranda of understanding have been signed with XXX

  27. 27.

    SFC (2014).

  28. 28.

    Sec. 38D Companies (Winding Up and Miscellaneous Provisions) Ordinance (CWUMPO), CAP 32.

  29. 29.

    Secs. 2 and 103(1) Securities and Futures Ordinance (SFO), CAP 571.

  30. 30.

    Sec. 2(1) CWUMPO in connection with Schedule 17, pt. 1, sec. 1 CWUMPO, in connection with Schedule 1, pt. 1, sec. 1 SFO, in connection with sec.397 SFO.

  31. 31.

    Sec. 2(1) CWUMPO in connection with Schedule 17, pt. 1, sec. 3 and pt. 2 CWUMPO, in connection with Schedule 1, pt. 1, sec. 1 SFO.

  32. 32.

    Sec. 2(1) CWUMPO in connection with Schedule 17, pt. 1, sec. 2 CWUMPO, in connection with Schedule 18,pt. 3 CWUMPO. Other exemptions limiting the total proceeds raised and setting a floor for the minimum consideration collected from each investor are less well adapted to the needs of crowdfunding.

  33. 33.

    FSDC (2016).

  34. 34.

    An additional problem was raised that crowdfunding platforms may violate the monopoly of registered stock exchanges under sec 19 SFO. Under this provision, only a recognized exchange company may operate a stock market, which includes ‘a place at which facilities are provided for bringing together sellers and purchasers of securities.’ SFO sec 19(1) in connection with Schedule1, Part 1, s 1.

  35. 35.

    MAS (2015).

  36. 36.

    ‘According to the Hong Kong Census Reports, Hong Kong’s Gini coefficient based on original monthly household income rose from 0.533 in 2006 to 0.539 in 2016… In May 2018, the total net worth of the wealthiest 21 mega-tycoons in Hong Kong amounted to HK$1.83 trillion.’ Oxfam Hong Kong (2018), p. 1. The net worth of those 21 billionaires thus constituted about 64% of the Hong Kong GDP for the seven million residents of Hong Kong in 2018 (which was about HK$2.84 trillion).

  37. 37.

    Piketty describes this phenomenon in turn-of-the-century US: ‘one consequence of increasing inequality was virtual stagnation of the purchasing power of the lower and middle classes in the United States, which inevitably made it more likely that modest households would take on debt.’ Piketty (2011), p. 297.

  38. 38.

    Sec. 5 Pawnbrokers Ordinance, CAP 166.

  39. 39.

    Secs. 2 and 7, Money Lenders Ordinance, CAP 163.

  40. 40.

    Sec. 11(5) MLO.

  41. 41.

    HKMA (2018).

  42. 42.

    HKMA (2018), pars 12, 14.

  43. 43.

    HKMA, ‘Remote on-boarding of individual customers’ (1 February 2019).

  44. 44.

    Chan (2018b).

  45. 45.

    Ibid.

  46. 46.

    See e.g., Campbell (2017).

  47. 47.

    Schmidt and Bain (2019).

  48. 48.

    SFC (2017a).

  49. 49.

    Chan (2018a).

  50. 50.

    ‘Money’ is the concept that triggers application of the Payment Systems and Stored Value Facilities Ordinance, CAP 584, L.N. 145 of 2004, amended 2015. Money is also a prerequisite to ‘taking deposits’ under the Banking Ordinance, CAP 155, 1986, E.R. 1 of 2013.

  51. 51.

    SFC (2018).

  52. 52.

    SFC (2018).

  53. 53.

    FCA (2015).

  54. 54.

    These are listed on the HKMA website for its Fintech Supervisory Sandbox, www.hkma.gov.hk/eng/key-functions/international-financial-centre/fintech-supervisory-sandbox.shtml.

  55. 55.

    SFC (2017b).

  56. 56.

    SFC (2017b).

  57. 57.

    Information on the IA’s sandbox is available at the IA’s Insurtech Corner, www.ia.org.hk/en/aboutus/insurtech_corner.html#1

  58. 58.

    Guideline Eight, On the Use of Internet for Insurance Activities.

  59. 59.

    ‘Anima Anandkumar, director of machine learning research at Nvidia, a maker of graphics processing units, said workers should evaluate the future of their own roles by asking three questions: Is my job fairly repetitive? Are there well-defined objectives to evaluate my job? Is there a large amount of data accessible to train an AI system?’ Liu (2019).

  60. 60.

    BBC (2019).

  61. 61.

    This observation is made by Yuval Harari, as he observes, ‘it took more than a century of terrible wars and revolutions to experiment with these models, separate the wheat from the chaff, and implement the best solutions,’ as agricultural gave way to industrial society, and ‘given the immense destructive power of our civilization, we just cannot afford more failed models, world wars, and bloody revolutions’ in the 21st century. Harari (2018), p. 34.

  62. 62.

    Ford (2015), pp. 37–41.

  63. 63.

    Muro et al. (2019), p. 5.

  64. 64.

    Fleming et al. (2019), p. 17.

  65. 65.

    HKSAR Census and Statistics Department (2019).

  66. 66.

    The discussion of the Hong Kong economy relies on figures from the HKSAR Census and Statistics Department, available at https://www.censtatd.gov.hk/hkstat/sub/sp80.jsp?tableID=188&ID=0&productType=8

  67. 67.

    See e.g., Chen (2014) and Oxfam Hong Kong (2018).

  68. 68.

    See e.g., Harris (2017).

  69. 69.

    According to the Hong Kong Tourism Board, visits to Hong Kong dropped in August and September 2019 by 39% and 34%, respectively. See https://partnernet.hktb.com/en/research_statistics/latest_statistics/index.html.

  70. 70.

    Lockett and Hammond (2019).

  71. 71.

    This finding of Fleming et al., referred to above, is also affirmed in a study conducted a Brookings Institute, which uses the phrase ‘hollowing out’ in its findings on automation. See Muro et al. (2019), p. 24.

  72. 72.

    See e.g., Hui (2018).

  73. 73.

    Muro et al. (2019), pp. 50–56.

  74. 74.

    Undergraduate tuition in all Hong Kong universities is supported with public funds and was in 2018 uniform at about HK$42,000 (about US$5,400), considerably less than that of an average US university.

  75. 75.

    See e.g., Ren (2019).

  76. 76.

    Lam (2018).

  77. 77.

    Donald (2014), pp. 44–45.

  78. 78.

    See e.g., Yip (2018).

References

Download references

Author information

Authors and Affiliations

  1. Faculty of Law, The Chinese University of Hong Kong, Shatin, Hong Kong

    David C. Donald

Authors
  1. David C. Donald
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David C. Donald .

Editor information

Editors and Affiliations

  1. Graduate School of Law, Kyushu University, Fukuoka, Japan

    Mark Fenwick

  2. Graduate School of Law, Kyushu University, Fukuoka, Japan

    Steven Van Uytsel

  3. Zhejiang University, Hangzhou City, China

    Bi Ying

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Donald, D.C. (2020). Hong Kong’s Fintech Automation: Economic Benefits and Social Risks. In: Fenwick, M., Van Uytsel, S., Ying, B. (eds) Regulating FinTech in Asia. Perspectives in Law, Business and Innovation. Springer, Singapore. https://doi.org/10.1007/978-981-15-5819-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-5819-1_3

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5818-4

  • Online ISBN: 978-981-15-5819-1

  • eBook Packages: Law and CriminologyLaw and Criminology (R0)

Publish with us

Policies and ethics

Search

Navigation