Fintech Manpower Development in Asia-Pacific Financial Centers with a Focus on AI and Big Data Prof by andrew tang

FINTECH MANPOWER DEVELOPMENT IN ASIA-PACIFIC FINANCIAL CENTERS WITH A FOCUS ON ARTIFICIAL INTELLIGENCE AND BIG DATA PROFESSIONALS

1Contents 2.1.EXECUTIVEACKNOWLEDGMENTSPREFACECONTENTSSUMMARYINTRODUCTIONARTIFICIALINTELLIGENCE AND BIG DATA TALENT DEVELOPMENT IN ASIA PACIFIC 2.1 Hong Kong 2.2 Singapore 2.3 Shanghai 2.4 Shenzhen 2.5 Tokyo 2.6 Sydney 3. COMPARING THE ARTIFICIAL INTELLIGENCE AND BIG DATA MANPOWER ECOSYSTEM OF THE SIX ASIA PACIFIC FINANCIAL CENTERS 4. POLICY RECOMMENDATIONS 5. REFERENCESCONCLUSION 6543 29262422189 57565232

About HKUST Business School

Founded in 1991, the HKUST Business School is young, innovative and committed to advancing global business knowledge. The School has forged an international reputation for world class education programs and research performance, and has received many top global rankings. It is one of the first Asian business schools accredited by both AACSB and EQUIS. The School strives to contribute to the economic and social advancement of the region by developing future leaders who possess an innovative and entrepreneurial spirit as well as a strong sense of responsibility. We also take active steps to promote knowledge advancement in many significant business areas. For more information, please visit www.bm.ust.hk. About Fintech Research Project

A team of researchers from HKUST and other universities with expertise spanning finance, information systems, statistics, computer science, accounting, and economics are tackling eight major research tasks that cover blockchain, cybersecurity, risk preference, robo-advising, artificial intelligence / machine learning, systemic risk, financial innovation policy, and manpower development.

The Fintech Research Project is funded by the Research Grants Council (RGC) under the Theme-based Research Scheme 2018/19, titled “Contributing to the Development of Hong Kong into a Global Fintech Hub”. The project aims at providing a roadmap for transforming Hong Kong into a global fintech hub through the delivery of policy recommendations, scholarly contributions, and industrial impacts.

In this Report, we completed an in-depth analysis using government-released data and information as well as data from LinkedIn profiles to assess the talent situation across six financial centers in Asia Pacific. While we were aware that not all AI and big data professionals are LinkedIn members, the profile data and their aggregates served as a reasonable proxy to get a snapshot of the rapidly evolving landscape for AI and big data talent pool in the region.

A key finding in the Report is that the shortage in AI and big data talent remains the greatest challenge to the digitalization of financial services across the region. As such, the Report recommends that all major stakeholders including the Government, education institutions and financial market participants to better understand the supply and demand of talent, while identifying gaps when formulating and implementing policy interventions.

The purpose of the Report is to offer a broad stroke comparison to look at what steps each of these six cities has taken to fill the talent gap. Then, it makes recommendations based on those findings and learnings, especially for Hong Kong.

3Preface PREFACE

The Report also makes several recommendations on how to close the talent gap. These include greater collaboration between the Government, education sector and the private sector to provide opportunities for education and upskilling, as well as to offer fintech professionals with a clearer roadmap for career development. We hope that readers will find this Report relevant as talent availability will continue to be the single most important factor when it comes to the successful adoption of AI and big data for the foreseeable future. If the region wants to succeed, addressing the talent issue will be a critical priority.

Prof. Kar Yan Tam School of Business and Management

There is no doubt that Artificial Intelligence (AI) and big data are the future for the financial industry.

The COVID-19 pandemic has accelerated the momentum of digitalization as companies are rapidly adjusting to a new business environment. In response, financial institutions today are innovating and adopting new technology, and rapidly apply it to products and services. This trend is only going to Forecastscontinue.

predict that global spending on AI will increase from US$50 billion in 2020 to US$110 billion in 2024. However, findings also show that there is a huge shortage of AI and big data talent with the right skill sets to fuel this demand. This is especially the case in the financial industry where professionals are further expected to have management, technical, and finance related skills. The talent gap remains wide and significant.

The Hong Kong University of Science and Technology

This Report benefits significantly from the discussions and inputs from major stakeholders of the finance industry including government offices, regulators, financial institutions, professional associations and education providers. Special thanks go to the Hong Kong Institute for Monetary and Financial Research of the Hong Kong Monetary Authority which offer valuable feedback to the initial draft of the Report. The research support provided by Winne CHAN, Ka Chun NG, Ka Chau WONG, Wai Nok YIM, Lionel MOK, and Athar MANSOOR and the editorial assistance of John POON and Christy YEUNG are very much appreciated. The Report also benefits from the services provided by LinkedIn to support our cross-city comparisons.

By studying what measures financial centers in the region take to close the talent gap, we hope that the Report can offer some insights into what the region needs to hone the necessary talent for AI and big data.

ACKNOWLEDGMENTS

4 Acknowledgments

The lack of AI talent is currently presenting a critical barrier to developing financial strategies and capacities in Hong Kong which are fit for the future. Securing Hong Kong’s position as a global financial center requires an immediate assessment of the gaps within the city’s AI and big data talent pool. Simply put, we need to understand why and how Hong Kong can develop its AI and big data talent pool to remain relevant in an increasingly automated and algorithmic, post-Covid world. This Report investigates the landscape for AI and big data talent in Hong Kong and the wider Asia Pacific region, to shed light on labor trends and dynamics, and to identify strategies which can enable Hong Kong to develop a competitive pool of AI and big data talent.

Artificial Intelligence (AI) and big data continue to shape the future of finance. COVID-19 drastically elevates the importance of the digital economy in driving Hong Kong’s social and economic development/recovery. Public and private sector entities quickly adopt digital, remote working practices and protocols to maintain competitiveness under the new normal. Parallel to the rise of big data, cloud computing and blockchain technologies, the centrality of AI to the likelihood of success within Hong Kong’s financial services sector is now beyond dispute.

The infrastructure surrounding AI and big data in the financial sector is expected to scale rapidly. The window of opportunity for Hong Kong to establish its standing as a future-proof financial center is closing. Now is the time to develop a comprehensive strategy for Hong Kong’s finance industry to navigate an increasingly digital world.

This Report is divided into three major sections. The first section presents a macro overview of trends and policies shaping AI and big data talent development in Hong Kong, Singapore, Shanghai, Shenzhen, Tokyo, Sydney. The subsequent section reviews the characteristics of AI/ big data talent manpower ecosystem and flows between those cities by analyzing LinkedIn profile data. Drawing on these two components, the third section provides policy recommendations that can plug fill gaps in Hong Kong’s talent pool. Among the six cities examined in this study, Hong Kong has experienced noticeable outflow of talent during the period studied. With eight universities offering undergraduate degrees in the fields of data science, data analytics and artificial intelligence, Hong Kong is helping to meet the AI and big data needs of financial institutions. Hong Kong’s status as an exporter of AI and big data talent suggests that our talent development pipeline/environment is generally recognized throughout the region. However, this situation also presents a potential threat to the competitiveness of Hong Kong’s financial sector where the AI/big data skill gap is expected to widen as more entities/institutions seek to develop their own algorithmic capacity. There is an urgent need to support the labor economics of AI and big data talent. Our policy recommendations point to expanding the supply of training programs in both universities and industry settings, whilst making Hong Kong a more attractive location for AI developers to develop longerterm careers. Simultaneously, the government can ease the flow of talent to meet growing demand by supporting co-operation between local universities and the financial sector so graduates and professionals can, and are incentivized to continue developing their careers in Hong Kong.

5Executive Summary EXECUTIVE SUMMARY

1.INTRODUCTION

6 Introduction

The finance industry contributes significantly towards the growth and development of the major financial centers situated within Asia Pacific. For example, in 2019, it contributed 21.2% towards the local GDP of 1. https://www.investopedia.com/articles/personal-finance/022415/top-10-countries-save-most.asp

Throughout history, crises have forced countries and economies to adapt and evolve. In the aftermath of the Asian Financial Crisis (1997-98) for example, Asia Pacific’s financial sector has evolved significantly. Financial institutions such as banks, insurance companies and pension funds installed robust mechanisms to strengthen their balance sheets to build resistance against external shocks. Since then, the region has emerged as a dynamic center for global growth with high savings rates across countries like China (44.9%) and Singapore (53.8%)1 as well as strong export economies such as China, Hong Kong, Japan and Singapore. It has also become an attractive place for investments and private capital since the potential of those domestic markets is huge.

This Report reviews the AI and big data talent situation across Asia Pacific’s finance industry focusing on six major financial hubs: Hong Kong, Singapore, Shanghai, Shenzhen, Tokyo and Sydney. For each of these cities, we have studied the overall demand and supply of AI and big data talent and the public policy initiatives and interventions that facilitate their development. We have observed that talent initiatives and targets exist at both the country and city levels for some financial centers, while they only exist at the national level for others. Nevertheless, they reflect the different aspirations, goals and plans of the six financial centers covered in this study.

The remainder of this Report is structured into four sections. In the next section, we carry out a macro-overview of AI and big data talent development in the six financial centers mentioned above. We delineate in-depth details of the demand and supply of AI and big data talent in the six cities. In the subsequent sections, we compare the AI and big data manpower ecosystem of the six financial centers through a more in-depth analysis using LinkedIn data pertaining to AI and big data professionals in these cities. The LinkedIn profiles of the relevant professionals offer a broad range of analyses including skills requirements, affiliation, mobility across cities, as well as the major suppliers of this talent. While we are well aware that not all AI and big data professionals are LinkedIn members, the profile data and their aggregates serve as reasonable proxies to the underlying populations of the targeted professional group for our investigation. The comparison section is then followed by policy recommendations for Hong Kong and finally a conclusion.

2. IDC (2020). | Worldwide Spending on Artificial Intelligence Is Expected to Double in Four Years, Reaching $110 Billion in 2024, According to New IDC Spending Guide. | https://www.idc.com/getdoc.jsp?containerId=prUS46794720 3. Artificial Intelligence in Society, OECD, 2019.

The pace of digitalization and the application of Artificial Intelligence (AI) has accelerated rapidly following the onset of the COVID-19 pandemic. Both public and private sector entities were forced to continue delivering goods and services while working from home/traditional economic modes shut down. The global spending on AI is forecast to increase to over 120% from US$50 billion in 2020 to approximately US$110 billion in 2024.2 AI and big data adoption in the financial industry especially in areas such as credit underwriting, algorithmic trading and asset management, is growing at a rapid pace, facilitated by an abundance of available data along with reliable, affordable and convenient computing capacity.

A report by the Organization for Economic Co-operation and Development (OECD) 3 showed that for suppliers, there’s great advantage in deploying AI and big data analytics in finance as it can give companies a competitive advantage by improving their efficiencies and profitability as well as reducing costs and increasing productivity through enhanced decision-making processes, automated execution and process optimization. Similarly, AI and big data can also enhance the quality of financial services and products offered through customization and new product rollouts. The report further shows that it’s not only the supply side that can benefit immensely from AI and big data, but there’s also huge advantage on the demand side by way of availability and improved quality of products as well as a larger variety of options along with personalized services. The benefits of utilizing AI and big data analytics in the financial industry are immeasurable, and their successful deployment would require a steady and sustainable supply of well-trained and adroit manpower.

Hong Kong. Similarly, in Singapore, Shanghai, Shenzhen, Sydney and Tokyo these figures were 13.3%, 18.52%, 15.1%, 15.1% and 4.1%, respectively. Except for Tokyo, the figures can be regarded as substantial, highlighting the important role that financial centers play in facilitating economic growth.

8 Artificial Intelligence and Big Data Talent Development in Asia Pacific 2.ARTIFICIAL INTELLIGENCE AND BIG DATA TALENT DEVELOPMENT IN ASIA PACIFIC

5. Census and Statistics Department, Hong Kong Special Administrative Region (Jan 2021). | Hong Kong Monthly Digest of Statistics - The Four Key Industries in the Hong Kong Economy. | https://www.censtatd.gov.hk/en/data/stat_report/product/ FA100099/att/B72101FB2021XXXXB0100.pdf

The finance industry has identified that a shortage of AI talent will contribute the greatest challenge to the ongoing and upcoming digitalization of financial services in Hong Kong. According to a survey conducted by the Hong Kong Monetary Authority (HKMA) in 2019, financial institutions ranked internal research and development as key to enhancing their AI capabilities.7 Considering the banks’ domain knowledge and their specific business models, 75% of the respondent banks which planned to adopt AI solutions in their businesses would prefer to develop AI applications internally rather than outsourcing them to external parties. This indicates that banks would prefer to nurture an internal AI workforce to achieve better alignment between the bank’s business model, stage of AI development, and its strategic plans. This finding is echoed in yet another survey conducted by the Hong Kong Academy of Finance in 20208 which revealed that most banks have plans to recruit more talent and invest more in developing in-house AI applications in the future.

As of 2019, there were 272,600 employees working in the finance industry in Hong Kong.4 The finance industry contributed 21.2% to the local GDP (i.e. HK$580.1 billion).5 According to the projection of the Hong Kong Special Administrative Region (HKSAR),6 the city needs a considerable supply of talent with the right skills and knowledge related to big data analytics, cybersecurity, and AI to sustain its continuous economic development. A growing demand for AI and big data talent in the Information Technology and Information Services sector is anticipated, with an annual growth rate of 2.2% from 2017 to 2027 (Table 2.1). IT workers employed in sectors including financial services, import, export, wholesale and retail trades, as well as social and personal services will experience an annual growth rate of 2.5% to 119,000 during the same period (Table 2.2). This growth is the highest in the field of Innovation and Technology (I&T) with an annual rate of 4.3% from 2017 to 2027 (Table 2.3).

2.1 HONG KONG

8. Hong Kong Academy of Finance (2020, August). | Artificial Intelligence in Banking - The changing landscape in compliance and supervision. | https://www.aof.org.hk/docs/default-source/hkimr/applied-research-report/airep.pdf (p.12)

4. Census and Statistics Department, Hong Kong Special Administrative Region (Jan 2021). | Hong Kong Monthly Digest of Statistics - The Four Key Industries in the Hong Kong Economy. | https://www.censtatd.gov.hk/en/data/stat_report/product/ FA100099/att/B72101FB2021XXXXB0100.pdf

7. Hong Kong Monetary Authority and PwC. | Reshaping Banking with Artificial Intelligence. | https://www.hkma.gov.hk/media/ eng/doc/key-functions/finanical-infrastructure/Whitepaper_on_AI.pdf (p.37)

6. The Government of the Hong Kong Special Administrative Region (2019, December). | Report on Manpower Projection to 2027. | https://www.lwb.gov.hk/en/other_info/mp2027_en.pdf

10. Research Office, Legislative Council Secretariat (2019, October 23). | Study of development blueprints and growth drivers of artificial intelligence in selected places. | development-blueprints-and-growth-drivers-of-artificial-intelligence-in-selected-places-20191023-e.pdfhttps://www.legco.gov.hk/research-publications/english/1920in01-study-of11. Fintech Facilitation Office, Hong Kong Monetary Authority (2020, September). | Fintech Manpower Study. [Confidential] FinTech Career Accelerator Scheme (2019). | FinTech career accelerator scheme (Gap year placement programme). | http://www.fcas.hk/ 13. Innovation and technology (I&T) experts include 1) pharmaceutical and life science/biotechnology; 2) data engineering (e.g. data mining/data analytics), artificial intelligence, robotics, distributed ledger technologies, biometric technologies, industrial/ chemical engineering, etc.; and 3) materials science/nanotechnology Talent List Hong Kong, the Government of the Hong Kong Special Administrative Region (2019). | Immigration Facilitation. | https://www.talentlist.gov.hk/en/imf.html

2.1.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

In the area of fintech, the HKMA expects a shortfall of 20,000 tech workers compared to other financial centers. More skilled professionals will need to be trained in order to fill Hong Kong’s growing talent gap in AI, big data and data analytics.11

Hong Kong has five universities among the world’s top 150.9 They offer high-quality data science and computing programs. As of May 2021, there are 14 bachelor’s programs, 12 postgraduate programs and a wide range of non-degree and short certificate courses related to AI, big data, and data analytics offered by local universities and other institutes (Table 2.4). For engineering and science disciplines specifically, the city’s five universities currently rank among the top global 100, producing a steady stream of talent to support Hong Kong’s technological development (Table 2.5).

One of the main sources of AI, big data, and data analytics talent are graduates of local universities.

14.

Universities in Hong Kong also produce high quality research outputs in the area of AI and data science. They have produced highly-cited and impactful AI research. 10 Not only do these research activities establish a solid intellectual foundation in Hong Kong, but they also enhance the R&D training for local researchers in the field of AI and data science.

2.1.1 Supply and demand of AI, big data, and data analytics talent

10 Artificial Intelligence and Big Data Talent Development in Asia Pacific

The HKSAR Government and regulators have launched a number of initiatives in recent years to bridge the talent gap. In 2016, the HKMA launched the FinTech Career Accelerator Scheme (FCAS).12 By collaborating with the Hong Kong Applied Science and Technology Research Institute (ASTRI), the program offers a gap year placement for local university students to engage in FinTech-related projects in banks or to work at the HKMA for six months to one year. Participating banks could also consider co-university programs, i.e. they can choose to offer a one-year internship program to students to enlarge and sustain the fintech talent pipeline in Hong Kong. By rolling out incentives to meet the talent shortage challenge in AI and big data, the HKSAR Government has proposed initiatives and formulated policies to develop, retain, and attract talent locally and from overseas. In 2018, the HKSAR Government launched a talent list welcoming overseas talent who are most desired in Hong Kong for its future development. Data scientists, cybersecurity specialists, and Innovation and Technology (I&T) experts13 were on the list. Qualified overseas talent will be granted immigration facilitation under the Quality Migrant Admission Scheme (QMAS).14 The Scheme provides incentives to overseas data scientists and AI experts to come and contribute to Hong Kong.

9. Times Higher Education (2021). | World University Rankings 2021. | rankings/2021/world-ranking#!/page/0/length/25/sort_by/rank/sort_order/asc/cols/statshttps://www.timeshighereducation.com/world-university-

12.

11 15. The HKSAR Government (2020, Jan 30). | Government launches enhanced Technology Talent Admission Scheme. | https://www.info.gov.hk/gia/general/202001/30/P2020012900480.htm

18. Ho, K. (2021, February 24). Hong Kong Budget 2021: Gov’t to inject HK$500m to attract overseas STEM scholars. | Hong Kong Free Press. | https://hongkongfp.com/2021/02/24/hong-kong-budget-2021-govt-to-inject-hk500m-to-attract-overseas-stemscholars/ 19. Interactive Employment Service, Labour Department, The HKSAR Government. | Greater Bay Area Youth Employment Scheme. | https://www2.jobs.gov.hk/0/en/information/gbayes/ 20. The HKSAR Government (2017). Study Subsidy Scheme for Designated Professions/Sectors. | https://www.cspe.edu.hk/en/Thesssdp/sssdp.htmlGovernment

It has recently also expanded to include 5G communications, Internet-of-Things, integrated circuit design, microelectronics, digital entertainment and green technology.15

In terms of hardware enhancements, HK$1 million was granted to each secondary school to procure IT technology equipment and services as well as to organize IT-related extracurricular activities for students, so as to strengthen their IT foundation and skills.16 Announced in the HKSAR 2019-20 Budget, the Government injected HK$16 billion (US$2 billion) to strengthen or renovate university campuses in order to facilitate and allow students and researchers to engage in a modern and effective learning and research environment.17 Added to this, announcements were made in the HKSAR 2021-22 Budget plan to commit an additional HK$200 million (US$25 million) to primary schools to organize IT Innovation Labs similar to those in secondary schools. The “Knowing More About IT” program will be launched in subsidized primary schools with each getting HK$400,000 (US$50,000) in government support.18

also rolled out the Technology Talent Admission Scheme in June 2018 to provide a fast-track arrangement for the admission of overseas and Mainland technology talent to undertake R&D work in Hong Kong. Apart from the tenants and incubates of Hong Kong Science and Technology Parks Corporation (HKSTP) and Cyberport, the scheme was extended to local companies conducting R&D activities outside the premises of HKSTP and Cyberport in January 2020. The areas covered are biotechnology, AI, cybersecurity, robotics, data analytics, financial technologies and material science.

Nurturing talent with big data and AI skills is a long-term investment. Aside from policies to meet short and medium-term needs, the HKSAR Government has invested significantly in STEM education at the primary and secondary school levels. In 2019, the HKSAR Government committed HK$500 million (US$64 million) to Hong Kong secondary schools to help them organize IT Innovation Lab programs.

16. Yau, C. (2019, February 27). Hong Kong to spend HK$45 billion grooming the next leaders of technology and boosting innovation. | South China Morning Post. | spend-hk45-billion-grooming-next-leadershttps://www.scmp.com/news/hong-kong/hong-kong-economy/article/2187966/hong-kong-

The STEM Internship Scheme offers opportunities for STEM graduates to acquire relevant work experience in the early stages of their career. With the intention to enlarge the IT talent pool, the HKSAR Government provides allowances to undergraduates and postgraduates enrolled in a fulltime university STEM program funded by the University Grants Committee (UGC) to take up shortterm internships. This internship program serves as a training ground to hone and retain talent for AI, big data, and data analytics as well as to build a talent pipeline for the industry. Notably, in 2021, the Greater Bay Area Youth Employment Scheme intends to provide Hong Kong’s university graduates with around 700 internship places in Hong Kong and other GBA cities.19

Starting from the 2018-19 academic year, the Study Subsidy Scheme for Designated Professions/ Sectors (SSSDP)20 has increased its subsidized study places from 1,000 to about 3,000 places per cohort. In the same academic year, five computer science programs and four financial technology programs were subsidized under the Scheme, with 306 and 265 subsidized first-year places made

17. The Government of the Hong Kong Special Administrative Region (2019, February 27). | The 2019-20 Budget: Speech by the Financial Secretary, the Hon Paul MP Chan moving the Second Reading of the Appropriation Bill 2019. | https://www.budget.gov. hk/2019/eng/pdf/e_budget_speech_2019-20.pdf

The HKSAR Government has also organized a major initiative to transform Hong Kong into a worldclass research cluster. AIR@InnoHK is one of the research clusters focusing on the development of AI, robotics technologies, big data analytics and machine learning so as to attract first-class overseas and local researchers to conduct related research in Hong Kong.24

According to a report by the Vocational Training Council, the Government has invested and put in a lot of efforts into job opportunities and upskilling opportunities. For example, the Research Talent Hub has funded over 3,700 R&D positions. Over 3,500 employees of 1,800 companies have also received support for on the job training under the Re industrialisation and Technology Training Programme (RTTP).25 Information Technology and Information Services and its Sub-sectors in 2017 and 202726

12 Artificial Intelligence and Big Data Talent Development in Asia Pacific available, respectively.21 In January 2021, the Global STEM Professorship Scheme was launched in order to attract world renowned I&T scholars and research teams to join universities in Hong Kong to teach and conduct research in STEM-related disciplines.22

Table Manpower2.1 Requirements of the

Sub-sector requirementsmanpowerActual in Number2017 requirementsmanpowerProjected in Number2027 2017changeProjectedfromto2027 (2017rateaverageProjectedannualofchange-2027) activitiesTelecommunication 21 000 24 500 + 3 600 + 1.6% Software publishing and servicestechnologyinformationrelated 51 300 65 500 + 14 200 + 2.5% Whole sector 72 300 90 000 + 17 800 + 2.2% Note: Individual figures may not add up to the totals due to rounding. 21. The HKSAR Government (2018, March 28). | LCQ22: Preparing for advent of an era of artificial intelligence. | https://www.info. gov.hk/gia/general/201803/28/P2018032800555.htm?fontSize=1 22. Innovation and Technology Bureau and Education Bureau (2021, January). | Legislative Council Panel on Commerce and Industry - Global STEM Professorship. | https://www.legco.gov.hk/yr20-21/english/panels/ci/papers/ci20210126cb1-482-3-e. pdf 23. Innovation and Technology Commission, the HKSAR Government (2020). | Hong Kong: The Facts. Innovation and Technology. | https://www.itc.gov.hk/en/doc/HK_factsheets_I&T_(EN)_Jun2020.pdf 24. Innovation and Technology Commission, the HKSAR Government (2019). | Technological Infrastructure: InnoHK Cluster. | https://www.itc.gov.hk/en/technological_infrastructure/innohk_clusters.html 25. Vocational Training Council (2021). | Reindustrialisation and Technology Training Programme (RTTP). | https://rttp.vtc.edu.hk/ 26. The Government of the Hong Kong Special Administrative Region (2019, December). | Report on Manpower Projection to 2027 (p.51). | https://www.lwb.gov.hk/en/other_info/mp2027_en.pdf

The Researcher Programme and the Postdoctoral Hub under the Innovation and Technology Fund (ITF) provides eligible organizations/companies with opportunities to recruit university graduates and postdoctoral talent to participate in industry and application-oriented research projects. As of November 2019, the two programs have created around 5,500 research positions.23

13 27. The Government of the Hong Kong Special Administrative Region (2019, December). ｜ Report on Manpower Projection to 2027 (p.52). ｜ https://www.lwb.gov.hk/en/other_info/mp2027_en.pdf Table Manpower2.2 Requirements of IT Workers by Economic Sectors in 2016 and 202727 Economic sector requirementsmanpowerActual in Number2016& requirementsmanpowerProjected in Number2027 2016changeProjectedfromto2027 (2016rateaverageProjectedannualofchange-2027) Import, andaccommodationretailwholesaleexport,andtrades,foodservices 16 700 16 700 + 100 ** Information communicationsand 38 200 59 600 + 21 400 + 4.1% Financial services, real professionalestate, and business services 17 100 19 100 + 2 000 + 1.0% Social and personal services 14 500 19 600 + 5 100 + 2.8% Others# 4 000 4 000 - 100 - 0.1% Total 90 400 119 000 + 28 500 + 2.5% & The actual manpower requirements of IT workers were compiled based on findings of the “2016 Manpower Survey on Information Technology Sector” conducted by the Vocational Training Council (VTC), which were the latest available information at the time the projection was being compiled. # “Others” include Manufacturing, Electricity, gas, water and waste management; Construction; Transportation, storage, postal and courier services. ** Rate of change within ±0.05% Note: Individual figures may not add up to the totals due to rounding.

14 Artificial Intelligence and Big Data Talent Development in Asia Pacific 28. The Government of the Hong Kong Special Administrative Region (2019, December). | Report on Manpower Projection to 2027 (p.55). | https://www.lwb.gov.hk/en/other_info/mp2027_en.pdf Table Manpower2.3 Requirements of Innovation and Technology Industries in 2017 and 202728 Selected industry requirementsmanpowerActual in Number2017 requirementsmanpowerProjected in Number2027 2017changeProjectedfromto2027 (2017-2027)rateaverageProjectedannualofchange informationtechnologyInformationandservices 72 300 90 000 + 17 800 + 2.2% Innovation industriestechnologyand 38 000 57 600 + 19 600 + 4.3% Cultural and creative industries 217 800 238 000 + 20 200 + 0.9% industriesEnvironmental 45 200 51 500 + 6 300 + 1.3% Testing servicescertificationand 14 500 16 600 + 2 100 + 1.3% Table Bachelor’s2.4 Programs: University School / Faculty Program 1 City University of Hong Kong School of Data Science Bachelor of Science in Data Science 2 Bachelor of Engineering in Data and Systems Engineering 3 Department of Electrical Engineering Bachelor of Engineering in Computer & Data Engineering 4 Hong Kong Baptist University An SchoolComputerbyprogramInterdisciplinaryjointlyofferedtheDepartmentofScienceandofBusiness Bachelor of Science in Business Computing and Data Analytics 5 Lingnan University Department of Computing & Decision Sciences Bachelor of Science (Honors) in Data Science

The Hong Kong University of Science and Technology School of Science Science (Group A) with an Extended Major in Artificial Intelligence School of Business and Management, School of Engineering, and School of Science

The Open University of Hong Kong Bachelor of Science with Honors in Data Science and Artificial Intelligence Bachelor of Science with Honors in Statistical Analysis and Data Science

The Chinese University of Hong Kong Faculty of Social Science Data Science and Policy Studies Department of Computer Science and Engineering Bachelor of Engineering in Artificial Intelligence: Systems and Technologies

City University of Hong Kong School of Data Science Master of Science in Data Science Department of Computer Science Master of Science in Computer Science

Bachelor of Science in Risk Management and Business Intelligence School of Engineering Engineering with an Extended Major in Artificial Intelligence

The University of Hong Kong Department of Statistics & Actuarial Science Bachelor of Arts and Sciences in Applied Artificial Intelligence

The Hong PolytechnicKongUniversity School of Professional Education and Executive Development Bachelor of Science (Honors) in Applied Sciences (Statistics and Data Science)

The University of Hong Kong Department of Statistics and Actuarial Science (host) and Department of Computer Science Master of Data Science

15 6

Postgraduate Programs: University School / Faculty Program

16 Artificial Intelligence and Big Data Talent Development in Asia Pacific 4 The Hong Kong University of Science and Technology Department of Computer Science and Engineering and the Department of Mathematics Master of Science in Big Data Technology 5 School of Business and Management Master of Science in Business Analytics 6 Master of Science in Information Technology Department of Physics Master of Science in Data-Driven Modeling 7 The Chinese University of Hong Kong Business School Master of Science in Business Analytics 8 Department of Statistics Master of Science in Data Science and Business Statistics 9 Master of Science in Risk Management Science and Data Analytics 10 Hong Kong Baptist University Department of Computer Science Master of Science in Data Analytics and Artificial Intelligence 11 The Hong PolytechnicKongUniversity Department of Computer Science Master of Science in Information Technology 12 Department of Applied Mathematics Master of Science in Data Science and Analytics Non-degree Programs / Upskilling Short Courses: University School / Faculty Program 1 The Hong PolytechnicKongUniversity Hong Kong Community College Associate in Statistics and Data Science 2 The University of Hong Kong HKU SPACE Community College Higher Diploma in Data Science 3 Advanced Diploma in Big Data Analytics and Applications

17 4 The University of Hong Kong HKU SPACE Community College Advanced Diploma in Accounting and Big Data 5 Certificate for Module (Applied Big Data in Digital Healthcare, Big Data Analytics for Smart Property Management, Big Data and AI for HR Analytics, Big Data Governance and Data Compliance) 6 Postgraduate Diploma in Finance and Data Analytics 7 UOW College Hong Kong Associate of Science in Data Analytics and Management 8 The Chinese University of Hong Kong School of Continuing and Professional Studies Certificate in Data Mining and Machine Learning 9 The Open University of Hong Kong Data Warehousing and Knowledge Management 10 Hong ProductivityKong Council Academy29 A wide range of courses in data mining, machine learning, coding, AI, cloud security, etc. Table Ranking2.5of Universities in Hong Kong by Subject in 202130 Subject University (Rank) Computer Science & Information Systems HKUST (30), CUHK (31), HKU CityU(43),(68) 29. For the details of the courses offered by Hong Kong Productivity Council Academy, please visit https://www.hkpc.org/en/hkpc-academy/latest-training-programmes 30. QS Top University (2021). | QS World University Rankings by Subject 2021. | https://www.topuniversities.com/subjectrankings/2021

31.

32.

The data analytics industry contributes to the nation’s economic development generating at least SG$1 billion per year.34 Big data and business analytics services provide high-value business to Singapore, and the economic value generated is estimated to reach SG$37 billion by 2022. The pandemic in the past two years has provided an opportunity for Singapore to rethink how it can embrace technology and nurture data-driven mindsets. It is worthy to note that 89% of Singapore employers expressed that the pandemic has accelerated the adoption of Cloud Computing/Machine Learning technologies in their companies.35 However, one of the main obstacles to adopting Machine Learning technologies is the lack of in-house IT support, and employees do not have sufficient Cloud Computing and Machine Learning skill sets.36 https://www.businesstimes.com.sg/government-economy/three-in-four-new-jobs-in-financial-sector-go-to-locals-mas https://www.businesstimes.com.sg/government-economy/three-in-four-new-jobs-in-financial-sector-go-to-locals-mas

33. https://www.statista.com/statistics/625794/gdp-of-the-finance-and-insurance-industry-in-singapore/ 34. https://www.edb.gov.sg/en/business-insights/insights/singapore-s-big-ambitions-for-big-data-in-2019.html 35. https://www.media-outreach.com/View/64002/ntuc-learninghub-survey-reveals-accelerated-business-needs-in-cloud-computing-and-machine-learning-outpacing-singapore-talent-supply-skills-gap-a-hindrance-to-implementing-these-technologies 36. https://www.media-outreach.com/View/64002/ntuc-learninghub-survey-reveals-accelerated-business-needs-in-cloud-computing-and-machine-learning-outpacing-singapore-talent-supply-skills-gap-a-hindrance-to-implementing-these-technologies

18 Artificial Intelligence and Big Data Talent Development in Asia Pacific

2.2 SINGAPORE There were more than 170,000 employees working in the financial sector in 2019, 31 contributing to 13.3% of Singapore’s GDP in 201932 amounting to SG$68.17 billion.33 2.2.1 Supply and demand of AI, big data, and data analytics talent

19 37. https://www.oxfordinsights.com/ai-readiness2019 38. https://jfgagne.ai/global-ai-talent-report-2020/ 39. https://techwireasia.com/2020/09/is-singapore-facing-a-tech-talent-crunch/ 40. Chew, H.M. (2021, May 24). Financial tech workers in demand in Singapore, getting multiple job offers and pay increments. | CNA. | https://www.channelnewsasia.com/news/business/finance-tech-jobs-singapore-salary-fintech-14875418 41. https://www.media-outreach.com/View/64002/ntuc-learninghub-survey-reveals-accelerated-business-needs-in-cloud-computing-and-machine-learning-outpacing-singapore-talent-supply-skills-gap-a-hindrance-to-implementing-these-technologies 42. https://www.smartnation.gov.sg/why-Smart-Nation/NationalAIStrategy 43. AI/MachineexpectedSingaporehttps://www.smartnation.gov.sg/docs/default-source/default-document-library/national-ai-strategy.pdf?sfvrsn=2c3bd8e9_4(p.54)rankedfirstintheGovernmentArtificialIntelligenceReadinessIndexin2019,37andistohaveacomparativelystrongertalentpipelineregionally.Asof2020,thereareover1,700LearningengineersandAI/DataProductizationemployees,respectively,inSingapore.38Itisestimatedthat60,000professionalsareneededintheInformationCommunicationsTechnology(ICT)sectorby2023inordertomeetthesector’stalentdemand.39However,thesixuniversitiescanonlyprovide2,800ICTgraduatesannually.Evenincludingtheinstitutesoftechnicaleducationandotherpolytechnicswhichsupply4,500graduateseachyear,thetalentgapremainslarge.Itisestimatedthattherewillstillbeashortfallof51,600talentinthesector.Thelocaltechnologytalentpoolsimplycannotmeetthefinancialsector’sFintechdevelopment.TheMonetaryAuthorityofSingapore(MAS)highlightedthattherewere21,000jobscreatedinthefinancialsectorinthelastfiveyears,and25%ofthosewererelatedtotechnology.While75%ofthetotalnumberofjobsinthefinancialsectorweretakenupbySingaporeans,only35%ofthetechnologyjobsweretakenupbySingaporeans.40TotackletheAIandbigdatatalentdemandchallenges,employerstendtolook“inward”toincreaseandsustainthetalentpool.55%oftheemployerssaidthattheyhadupskilledemployeeswhoalreadyhavesimilarskillsets,while44%ofthemexpressedthattheyinvestedtoreskillthosewhohavenoAIskillsets.41

2.2.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

The Singapore Government has proactively pushed AI as a national strategic focus identifying five key areas to start its National AI projects. The purpose is to drive national development in AI, guide investments and generate a talent pipeline to support a digital infrastructure. By working on the five areas: transport and logistics, smart cities and estates, healthcare, education, as well as safety and security, the Government hopes that it will encourage collaborations to develop and deploy AI solutions.

The Singapore Government realized very quickly that a critical bottleneck for AI development was its talent gap, and therefore it now aims to nurture AI and big data talent covering different sectors including R&D, data engineering, AI engineers for product development and application developers, infrastructure engineers/developers and systems integrators for implementing machine learning systems.43

The Singapore Government also proactively supports small and medium enterprises (SME) by providing them with financial support to upgrade their ICT manpower capacities.

The Government has introduced a number of policy instruments to attract, retain and sustain AI and big data talent. On upskilling Singaporeans to meet the AI job requirements, the Government provides Postgraduate Scholarships by collaborating with large corporations like Alibaba, Nvidia, Sensetime, and Grab, to provide relevant skills and training for R&D personnel in the AI industry.45 Indeed, universities in Singapore have also been partnering with AI companies to provide first-hand training for their students in the area of data science and AI. The National University of Singapore (NUS) collaborated and jointlyinvested SG$6 million (US$4.4 million) with Grab to set up the Grab-NUS AI Lab, which provides a platform for researchers and students to research smart mobility solutions. In 2017, Nanyang Technological University (NTU) also established its Data Science and Artificial Intelligence Research Centre.46 In addition to partnering with universities, the Government also offers a number of AI on-the-job training programs. For instance, the AI Apprenticeship Programme (AIAP) plans to equip 500 AI engineers with essential skills in the next five years.47 The AI Data Apprenticeship Programme (AIDP) is another six-month apprenticeship program that provides on-the-job training to workers who are interested in data curation and AI solutions. There is another training program that targets more general workers who are eager to equip themselves with ICT skills to prepare themselves for the digital economy. The program includes job placements and upskilling training for participants so as to promote ICT skills among Singaporeans. The Government also partners with technology corporations to organize the SkillsFuture for Digital Workplace program. The Government has set an ambitious target to train 25,000 AI professionals to be equipped with AI coding and application skills by 2025.48

Artificial Intelligence and Big Data Talent Development in Asia Pacific

44. https://techwireasia.com/2020/09/is-singapore-facing-a-tech-talent-crunch/ 45. https://www.smartnation.gov.sg/docs/default-source/default-document-library/national-ai-strategy.pdf?sfvrsn=2c3bd8e9_4(p.55) 46. https://www.globalbrandsmagazine.com/%E2%80%8Bntu-launches-research-centre-for-big-data-analytics-and-artificial-intelligence/ 47. https://aisingapore.org/industryinnovation/aiap/ 48. https://www.smartnation.gov.sg/docs/default-source/default-document-library/national-ai-strategy.pdf?sfvrsn=2c3bd8e9_4(p.59)

The Government has increased its ICT federal budget to SG$3.5 billion (US$2.52 billion) in 2020 and 80% of the ICT budget has been allocated to the country’s SMEs. This empowers SMEs with the manpower support that is needed in cloud and data analytics, AI, and IoT sensors.44

21 49. Institute of Technology Singapore. | Technology in Finance Immersion Programme (TFIP). | https://www.digipen.edu.sg/ academics/continuing-education/technology-in-finance-immersion-programme 50. fillProgrammeEconomicAnothertoAItertiaryAIThefinancewillInstituteprogramProgrammeThehttps://www.smartnation.gov.sg/docs/default-source/default-document-library/national-ai-strategy.pdf?sfvrsn=2c3bd8e9_4(p.59)InstituteofTechnologySingaporehasalsolaunchedtheTechnologyinFinanceImmersion(TFIP)toofferopportunitiesforindividualstoacquirefintechrelatedtechnicalskills.TheisfullysupportedbytheInfocommMediaDevelopmentAuthority(IMDA)andMAS,withtheofBankingandFinance(IBF)andWorkforceSingapore(WSG)ascollaborators.Traineesreceivetrainingonhowtobuild,test,deploy,andmaintainAItoolsandalgorithmsrelevanttotheindustry.49SingaporeanGovernmentputsgreatemphasisoncomputationalthinking,computingskillsandinitsformaleducationcurriculum.Forthetertiarylevel,theSingaporeanGovernmentencourageseducationinstitutestodevelopdomain-specificAIcoursesandtoteachstudentshowtoapplyintheworkplace.50Forthegeneralpublic,theGovernmentalsostrivestoprovideAIliteracycourses100,000adultsandschool-attendingchildrenby2025.waytoincreasethesupplyofAItalentistoattractAItalentfromoverseas.Assuch,theDevelopmentBoard(EDB)andEnterpriseSingapore(ESG)organizedtheTech@SGtostreamlineemploymentpassapplicationstofacilitatetheemploymentofAItalenttothetalentgapforfast-growingtechnologycompanies.

It was estimated that Shanghai will have 200,000 AI talent by 2021,55 a dramatic increase from 10,592 AI talent in 2017.56 According to the 2019 China AI & Big Data Talent Employment Trend Report, 57 Beijing, Shanghai, and Shenzhen are ranked top three among the top 20 cities in China in terms of AI talent demand, accounting for 29.11%, 21.53%, and 12.36%, respectively. The same three cities are also ranked the top in terms of AI talent supply with a distribution of 26.61%, 20.40%, and 10.57%, respectively.

22 Artificial Intelligence and Big Data Talent Development in Asia Pacific 51. 上海市第四次经济普查主要数据公报（第三号） (2020). | https://www.thepaper.cn/newsDetail_forward_6659666 52. 2020年上海市国民经济和社会发展统计公报 (2021). | http://www.thepaper.cn/newsDetail_forward_11765409 53. https://multimedia.scmp.com/news/china/article/2166148/china-2025-artificial-intelligence/index.html 54. http://www.sppm.tsinghua.edu.cn/eWebEditor/UploadFile/China_AI_development_report_2018.pdf 55. https://www.shine.cn/biz/tech/1908311228/ 56. http://www.sppm.tsinghua.edu.cn/eWebEditor/UploadFile/China_AI_development_report_2018.pdf (p.42) 57. 猎聘发布《2019年中国AI&大数据人才就业趋势报告》. | http://www.chinanews.com/business/2019/08-30/8942645.shtml 2.3 SHANGHAI At the end of 2018, there were 10,054 financial enterprise legal entities in Shanghai with 47 million employees. 51 In 2020, Shanghai's financial industry contributed 716.6 billion yuan to the city, accounting for 18.52% of its GDP.52 2.3.1 Supply and demand of AI, big data, and data analytics talent in the city Shanghai is the second most popular location for AI companies in China53 and Shanghai Jiao Tong University is ranked the 10th in AI research output among institutions in the world.54 As both are a major industry and financial center, Shanghai has been building up its manpower capacity in AI development.

58. 政策: 关于印发修订后的《中国（上海）自由贸易试验区临港新片区集聚发展人工智能产业若干政策》的通知 (2020). | http:// www.thepaper.cn/newsDetail_forward_9638311 59. 数据观. (2018). 上海市北高新园区发布三年行动计划全力打造大数据产业之都: 上海: 数据观: 中国大数据产业观察_大数据门户. | http://cbdio.com/BigData/2018-09/24/content_5888027.htm 60. People.cn. 25 条创新举措！上海加快推进金融科技中心建设 . | http://money.people.com.cn/n1/2020/0115/c4287731550359.html

The action plan strives to position Shanghai as a big data industry cluster with regional (Yangtze River Delta) influence by 2020 and to become the "data core" of the Shanghai Global Science and Technology Innovation Center. It also aims to make the city a "data port" as part of a world-class urban agglomeration in the Yangtze River Delta.59

The ten supported items are: innovation at the source of key technologies, the construction of an open-source deep learning platform, the construction of public data sets for AI, the optimization and improvement of infrastructure, the application of technology, the construction of the industrial ecology, the large-scale development of enterprises, the settlements of enterprises in new areas, the deep integration of industry, university and research, and the protection of intellectual property.

In order to accelerate the formation of financial technology enterprise clusters, Shanghai has been aggressively attracting financial institutions and large technology companies to set up financial technology subsidiaries, financial technology R&D centers, and to open innovation platforms in the city. For financial technology enterprises registered in the Lin Gang Special Area in the Free Trade Zone, talent can be employed under the key talent introduction institutions and they can enjoy certain subsidies.60

Under the "Several Policies for the Agglomeration and Development of Artificial Intelligence Industry in the Lingang New Area of China (Shanghai) Pilot Free Trade Zone",58 ten major support measures were proposed to further accelerate the agglomeration and development of the AI industry in Shanghai.

Regarding the "Action Plan for Building Artificial Intelligence Shanghai Highland and Building a Firstclass Innovation Ecosystem (2019-2021)", the plan outlines Shanghai's AI vision to build a "first-class innovation ecology" by 2021. The vision includes Shanghai’s determination to create an innovation ecosystem to layout the construction of 4+X integrated innovation carriers, and the deployment of ten world-leading innovative application scenarios; strengthening the original innovation power, promoting the opening of the five hub innovation platforms, and cultivating a group of top international innovation teams; improving the ability to support innovation, building ten leading innovative enterprises, one hundred innovative benchmarking enterprises, and creating 100 billion yuan worth of output value for key Shanghai’sindustries.big

data industry base and the Shibei High-tech Park released its “Three-year Action Plan for Building China’s Big Data Industry Capital and Promoting High-quality Development” at a forum focusing on the implementation of eight major innovation actions and 19 specific action plans.

2.3.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

In 2019, Shenzhen ranked 3rd in terms of demand and supply of AI and big data talent in China. The city contributed 10.57% to the overall AI and big data talent supply in China and attracted 12.36% of AI and big data talent to work in Shenzhen.64 The financial industry ranked 4th after internet, electronics and communications, and mechanical and manufacturing in terms of supply and demand of AI talent in Shenzhen. By analyzing the distribution of overseas AI & big data talent across cities in China, (2021).

Intelligence

2.4 SHENZHEN Shenzhen’s financial industry contributed 418.96 billion yuan of economic value to the city in 2020, a year-on-year increase of 9.1%, accounting for 15.1% of the city’s GDP.61 The number of employees in the financial industry in Shenzhen is 1.22 million.62

| http://jr.sz.gov.cn/sjrb/xxgk/sjtj/sjsd/content/post_8588527.html 62. 深圳市第四次全国经济普查主要数据公报1-7号(2020). | http://www.sz.gov.cn/cn/xxgk/zfxxgj/tjsj/tjgb/content/ post_7801448.html 63. 数据观(2020). 工业和信息化部人才交流中心发布《人工智能产业人才发展报告（2019-2020年版）》. | http://www.cbdio.com/BigData/2020-07/06/content_6157950.htm 64. 猎聘 2019 年中国 AI&大数据人才就业趋势报告 (2019). | http://www.cbdio.com/image/site2/20190902/ f42853157e261ed6c9e638.pdf

Artificial and Big Data Talent Development in Asia Pacific

61. 深圳金融业2020年运行数据

2.4.1 Supply and demand of AI, big data, and data analytics talent Similar to other major cities in China, Shenzhen has been experiencing a talent gap in AI and big data. 63 Currently, there is pressing demand for talent specializing in AI algorithm research and application development. The Beijing-Tianjin-Hebei region, the Yangtze River Delta region, the Guangdong-Hong Kong-Macao Greater Bay Area, and the Sichuan-Chongqing region are the main regions for developing the AI industry in China. They are also the regions attracting the most AI talent to work and live in. The scale of demand in those regions account for 90.9% of the total national demand, and the scale of talent supply accounts for 82.9% of the total national supply, which translates to a talent gap in all AI areas.

25 Shenzhen ranked 3rd accounting for 8.83% of the total overseas talent, while Shanghai attracted most of the overseas AI & big data talent accounting for 26.02%. Beijing ranked 2nd accounting for 21.60%.

2.4.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

| http://www.sz.gov.cn/szzt2010/zdlyzl/jjshzc/content/ post_8391314.html 67. 深圳市人民政府关于印发新一代人工智能发展行动计划 (2019－2023年) 的通知 (2019). | http://www.sz.gov.cn/zwgk/ zfxxgk/zfwj/szfwj/content/post_6576972.html 68. 深圳市工业和信息化局关于组织开展2020年大数据产业发展试点示范项目申报工作的通知 (2019). | http://gxj.sz.gov.cn/ xxgk/xxgkml/qt/tzgg/content/post_2023594.html

These three cities are the first ladder cities for overseas AI and big data talent to settle in China.

65. https://www.scmp.com/news/china/politics/article/3106023/shenzhen-given-new-powers-attract-key-foreign-workers-and 66. 深圳市数字经济产业创新发展实施方案(2021-2023年)

The Central Government grants autonomy to Shenzhen to develop policy on developing big data and AI to strengthen itself as a tech hub in China.65 This includes streamlining visa applications to attract more overseas AI talent to work and live in Shenzhen.

The "Shenzhen New Generation Artificial Intelligence Development Action Plan (2019-2023)" intends to build more than ten innovative carriers by 2020, organizing and implementing more than 20 major technological industry development projects, and introducing and cultivating 3-5 international toplevel labor intelligent teams. They would also build 5-10 technology-leading research institutions, and cultivate ten leading technology companies. The scale of the core AI industry will exceed 10 billion yuan and the scale of related industries will reach 300 billion yuan.67

In 2021, Shenzhen released the "Shenzhen Digital Economy Industry Innovation Development Implementation Plan (2021-2023)", which outlined Shenzhen’s direction for the development of its digital economy in the next three years. In the field of AI, Shenzhen will formulate policy measures and provide support for developing industrial intelligence algorithms, AI chips, and AI products including unmanned driving, smart homes, and image recognition. At the same time, the Government will utilize various AI industrial bases in Shenzhen such as the Nanshan Park, High-tech Zone, and other areas to establish an ecosystem linking corporate headquarters with R&D incubation and high-end manufacturing.66 In the next three years, Shenzhen will implement the "1" + "4" + "2" AI strategy: to build "1" AI industry information system platform; to establish "4" benchmarks: People's Fair, AI Standards, AI industrial park, the establishment of AI industry fund; to establish "2" AI talent systems: a certification training system and the construction of an AI testing and a certification center.

Furthermore, the Ministry of Industry and Information Technology has published a notice on “Organizing and Carrying out the Application for the Big Data Industry Development Pilot Demonstration Project in 2020”, focusing on four categories and seven subdivisions. These include the industrial big data integration application, people's livelihood big data innovation application, big data key technology pilot application, and big data management capability improvement. A number of big data industry development pilot demonstration projects will also be selected.68 (2021).

In 2016, the total number of employees working in Tokyo’s financial industry was about 400,000.69 The finance industry contributed 4.1% to Japan’s GDP in 2019.70 2.5.1 Supply and demand of AI, big data, and data analytics talent In 2018, the Japanese Government announced that the country will not be able to fill 220,000 technology-related job vacancies.71 There is a growing shortage for big data, AI and IoT workers in Japan. It is estimated that there will be a shortfall of 48,000 and 200,000 in the areas of big data and AI/IoT/information security, respectively. 72 It is also estimated that Japan will have a shortfall of 120,000 workers in the AI sector by 2030.73 The general shortage of IT workers could escalate to 790,000 in 2030, which is an alarming signal as this prediction already included former Prime Minister Shinzo Abe’s plan to train 250,000 people in AI annually.74

26 Artificial Intelligence and Big Data Talent Development in Asia Pacific 69. https://www.sangyo-rodo.metro.tokyo.lg.jp/toukei/c8cdaf213387cae120e1754b8d448c59.pdf 70. https://www.statista.com/statistics/1176518/japan-contribution-of-finance-and-insurance-to-nominal-gdp/ 71. https://medium.com/quantumblack/why-japan-offers-a-perfect-storm-for-advanced-analytics-fcd6fffecc92 72. https://www.computerfutures.com/en-gb/blog/2018/09/positive-outlook-in-japans-market-as-tech-hiring-continues-to-boom/ 73. https://asia.nikkei.com/Business/Business-trends/Japan-s-shortage-of-AI-talent-opens-doors-for-disabled-workers 74. https://www.reuters.com/article/us-japan-tech-labour-focus-idUSKCN1UU0PX 75. https://www.computerfutures.com/en-gb/blog/2018/09/positive-outlook-in-japans-market-as-tech-hiring-continues-to-boom/ 2.5

TOKYO

Technology companies in Japan admitted that it is currently very challenging to retain employees. Some companies plan to provide training in cryptography and robotics to upskill their employees in order to meet the market demand and their business needs.

75 Corporations like Toyota and Fujitsu

The Japanese Government has not formulated a national AI talent development plan. Instead, it tends to utilize AI in its overall policies to address societal and development issues through a plan named Society 5.0 81 Society 5.0 sets out a roadmap for AI integration into society and industry. It can be incorporated into different areas of development such as healthcare, industrialization, and energy policies. In particular, after reviewing the scarcity of AI talent, the Japanese Government plans to attract 250,000 AI experts from overseas by internationalizing its education programs. Furthermore, by providing funds and establishing special working visas, the Government hopes to make Japan more attractive to overseas talent.82 The Government has also been promoting English as the working

27 76. https://www.rvo.nl/sites/default/files/2020/12/Artificial-Intelligence-in-Japan-final-IAN.pdf 77. https://opentoexport.com/article/japan-big-data-for-a-bigger-economy/ 78. 八木康史 (2018, May). AI 人材育成のための教育プログラム：人工知能技術戦略会議での議論. [Education Program for AI Human Resource Development: Discussion at Strategic Council for AI Technology] (In Japanese). https://jsai.ixsq.nii.ac.jp/ej/?action=repository_action_common_download&item_id=9201&item_no=1&attribute_id=22&file_no=1| 79. https://www.rvo.nl/sites/default/files/2020/12/Artificial-Intelligence-in-Japan-final-IAN.pdf 80. https://www.computerfutures.com/en-gb/blog/2018/09/positive-outlook-in-japans-market-as-tech-hiring-continues-to-boom/ 81. https://www.rvo.nl/sites/default/files/2020/12/Artificial-Intelligence-in-Japan-final-IAN.pdf 82.

havehttps://blog.gloture.co.jp/ai-market-japan/alreadyinvestingheavilyinto

AI Research & Development (R&D). Japan's exports of industrial robots is top in the world, and its expenditure in AI R&D is the third, following China and the United States. However, due to the country’s aging population, its biggest weakness continues to be the lack of human resources.76 Supply and demand for tech-savvy talent knowledgeable in big data and data analytics are very similar to those in the AI industry. The aging population negatively influences both supply and demand. The Government has allocated 7.7 trillion yen to develop big data services, and it is planning to allocate more funding for big data R&D. 77 These investments will open numerous positions for software engineers and data scientists, which will inescapably accelerate the demand for this talent.

2.5.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

As of 2020, there was a shortage of about 50,000 IT workers who could master AI technology in Japan. However, it is apparent that the Japanese AI workforce could not be supported by the local talent pipeline as the total number of graduates majoring in AI from all universities in Japan was about 3,000, according to a study published in 2018.78 However, in reviewing the data on talent flow, Japan does not seem to be very successful in attracting overseas talent. In the meantime, it is expected that Japan will lose one-third of its current workforce by 2065 because of its aging population.79 it is predicted that by 2030, the elderly will make up 40% of Japan’s population. As such, the Government is putting more efforts into training local talent and upskilling incumbent employees.80 They are doing this by providing them with more training, while at the same time modifying hiring approaches and retention strategies to make the Japanese companies more competitive.

The Government has also been relieving some of the barriers for technology skilled immigrants in order to let them get permanent residency easier. These include shortening the residency period in Japan from five to one year, as well as relaxing the Japanese language requirement. These policies would facilitate tech companies and startups to recruit more foreign talent so as to compensate for the shortage of AI and data analytics talent in Japan.

85.

languagecom/2017/05/tokyo-turns-up-volume-in-foreign-fintech-talent-hunt/andencouragingresearchersfromoverseas

Artificial Intelligence and Big Data Talent Development in Asia Pacific European Union. (2019). Overview of Artificial Intelligence (AI) in Japan. Tokyo: Delegation of the European Union to Japan 84. https://www8.cao.go.jp/cstp/english/moonshot/top.html https://asia.nikkei.com/Business/Technology/With-eye-on-Amazon-and-Google-Japan-joins-Asia-data-center-race 86. Peyton, A. (2017, May 18). Tokyo turns up volume in foreign fintech talent hunt. | Fintech Futures. | https://www.fintechfutures. to take up management positions in Japan.83

83.

Tokyo is a major financial center in Asia but there is yet a comprehensive manpower policy to address the AI and big data talent gap in the finance industry. The Tokyo Metropolitan Government (TMG) has launched some initiatives to attract technology companies to Tokyo to encourage the development of high-value operations in the city. TMG also launched projects to attract technology companies in the fields of fintech and asset management to locate their headquarters and R&D centers in the Special Zone for Asian Headquarters.86

The Japanese Government also initiated policy programs to tackle future talent issues. The Japanese Moonshot Program, a research and development initiative, promotes high-impact R&D aiming to address future societal issues. As for AI development, the program also involves multiple universities and government collaborations to educate the future generation to meet the needs of the AI industry.84

Another plan is related to foreign investments in data centers in Japan. The Government's Growth Strategy Council will offer tax breaks and other assistance to foreign investors, and the Council hopes to provide a stable supply of data-related jobs for the country.85

29 87. https://www.sgsep.com.au/assets/main/SGS-Economics-and-Planning-Economic-performance-fo-asutralias-cities-and-regions-report.pdf(p.19) 88. https://www.afr.com/technology/australia-faces-a-pandemic-led-crunch-in-ai-industry-warns-20200709-p55aiy 89. https://www.afr.com/technology/tech-talent-crunch-hits-home-amid-border-closures-20210422-p57ll8 2.6 SYDNEY

As of 2016, there were 88,451 employees in the finance industry in Sydney, accounting for 17.7% of total employment. The Financial & Insurance Services made up 15.1% of Sydney’s economy in 201718.87 2.6.1 Supply and demand of AI, big data, and data analytics talent Along with the growing ecosystem of technology startups in the city, Sydney is also transforming itself into a technology hub. It is the focal point for businesses in Australia, and AI is one of the fastest growing sub-sectors of the IT industry in Sydney.88 Observing that the demand for AI and machine learning services has been skyrocketing, the country's startups are racing against each other to recruit the best talent with the right skills. However, the supply of AI and big data talent has not been able to meet the surging demand. In the past, Australia has always been welcoming immigrants with skills to increase its labor force by offering them easy access to its work visa and permanent residency. However, there is now a demand for these tech-savvy talents globally. It is expected that Australia needs about 156,000 new technology workers by 2025 to ensure that its labor shortage does not have any adverse impacts on the country’s economic growth.89

The Australian Government has designed a clear roadmap for grooming AI, big data, and data analytics talents. For instance, the Government has released a policy named “An AI Action Plan for all Australians”96 to outline its vision and policy initiatives to train, retain and attract AI, big data, and data analytics talent. The policy has several goals including to increase the diversity and number of talented AI researchers and engineers in Australia, ensuring Australians have foundational AI education and skills, fostering lifelong learning within Australia’s existing workforce, and improving business and government leaders’ understanding of the use and impact of AI. This is a comprehensive strategy to sustain the talent supply in Australia.

Both the supply and demand for talent will go up alongside the growing investments into the big data sector in Sydney.

2.6.2 Initiatives/Government, Industry and Education sector policies that address the demands of AI, big data, and data analytics talent

Concerning the supply of AI talent in Australia, the increase in AI and Machine Learning talent in Australia in 2020 was 2,820 representing a 25.9% growth. However, there was a decrease in both AI/ Data Productization and Data engineering/Architecture talent in 2020, corresponding to a decrease of 52.8% and 9.5%, respectively.95 The drop could be attributed to the economic disruptions caused by the pandemic.

30 Artificial Intelligence and Big Data Talent Development in Asia Pacific 90. https://www.prnewswire.com/news-releases/australia-data-center-market-investment-analysis-report-2021-sydney-leads-the-market-with-the-presence-of-30-facilities---forecast-to-2026-301300154.html 91. https://www.businesswire.com/news/home/20200210005460/en/Australian-Data-Analytics-Market-is-Projected-to-Grow-at-a-CAGR-of-20-During-the-Forecast-Period---ResearchAndMarkets.com 92. https://www.hiringlab.org/au/blog/2019/04/30/data-scientists-au/ 93. https://oliver-uploads-aus.s3.amazonaws.com/2020/04/29/00/17/28/865/Data%20Science%20Snapshot%202020.pdf 94. https://consult.industry.gov.au/digital-economy/ai-action-plan/supporting_documents/AIDiscussionPaper.pdf 95. https://jfgagne.ai/global-ai-talent-report-2020/ 96. Inhttps://consult.industry.gov.au/digital-economy/ai-action-plan/supporting_documents/AIDiscussionPaper.pdftermsofbigdataanddataanalytics,Sydneyleadsinthenumberandthesizeofdata centers in Australia with over 30 facilities and an occupancy rate of over 85%. 90 It is estimated that the data analytics market in Australia will grow with a compound annual growth rate (CAGR) of 20% from 2021 to 2025.91

When it comes to upskilling the existing workforce with AI and data skills, the Australian Government believes that it requires the collaboration between government, businesses, and individual workers, and that it also needs to adopt a more flexible and multi-faceted approach. Industry-led training, a culture

Job postings for data scientists in Australia have increased dramatically by 58% in 2018. 80% of the job postings were from New South Wales (where Sydney is located) and Victoria (where Melbourne is located).92 The job titles "Data Scientist" and "Data Analyst" were the most advertised in 2020 in Australia and New Zealand.93 Commonwealth Scientific and Industrial Research Organisation (CSIRO) estimated that the Australian industry will need 32,000 to 161,000 AI professionals, including experts in computer vision, robotics, human language technologies, data science and other AI related fields, by 2030.94

Finally, when it comes to attracting global AI and big data talent, the Australian Government has streamlined the Global Talent Visa Program 100 to attract professionals specializing in ten target sectors101 to work and live in Australia. In 2020-2021, the program offered a total of 15,000 places for global talent. 97. https://digitaleconomy.pmc.gov.au/sites/default/files/2021-05/digital-economy-strategy.pdf 98. https://www.digitaltechnologieshub.edu.au/ 99. 101.100.https://www.industry.gov.au/funding-and-incentives/inspiring-australia-science-engagement-in-australiahttps://immi.homeaffairs.gov.au/visas/working-in-australia/visas-for-innovation/global-talent-independent-programThetentargetsectorsare:Resources:Agri-foodandAgTech,Energy,HealthIndustries,Defence,AdvancedManufacturingandSpace,CircularEconomy,DigiTech,InfrastructureandTourism,FinancialServicesandFinTechandEducation.TherearethreesectorsrelatingtotheapplicationsofAI,bigdataanddataanalytics.Fordetails,pleasevisit:https://immi.homeaffairs.gov.au/visas/working-in-australia/visas-for-innovation/global-talent-independent-program/eligibility

The Australian Government also proposed to integrate AI and big data capabilities into the existing and future workforce. The Government plans to put more effort into upskilling Australia’s workforce in order to enhance the transferability of displaced workers to other jobs and industries. The Government is also paying close attention to the current and future needs of the industry and is keeping its tertiary education and training systems flexible and responsive to the needs of growing and emerging industries related to AI and big data.

31 of lifelong learning, and business investments into workforce training are salient elements in the talent policy. The Australian Government has already injected A$1 billion into the JobTrainer Fund and has partnered with different states and territories to provide more Australians with advanced digital skills training for free or at a low cost. Within the program are other funding strategies such as the Job Ready Graduates Package, Digital Skills Organization, and Industry 4.0 Advanced Apprenticeship Pilot. These initiatives provide the right environment and resources for graduates.97

In addition to formal and vocational training, the Australian Government also explores innovative education programs such as the Digital Skills Organization (DSO) program to enhance citizens’ digital skills and provide digital training products to related industries. Regarding career information dissemination, the National Careers Institute is an official source of information on vocational careers and higher education training. Australians are provided with skill matching recommendations based on their studies and careers and they are also able to access up-to-date labor market information.

On AI education, policy initiatives are provided to different community groups in Australia. For instance, the Digital Technologies Hub98 provides online digital and technology skills education and resources to teachers, students and school workers. The Australian Government is also proactively engaging all citizens in science by promoting various STEM education programs to different communities. 99

In order to foster homegrown talent, the Australian Government has established a PhD Scholarship program to sustain a talent supply for a data-skilled workforce and to ensure a steady supply of data talent is in the pipeline for a future digital world.

32 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers 3.COMPARING THE ARTIFICIAL INTELLIGENCE AND BIG DATA MANPOWER ECOSYSTEM OF THE SIX ASIA PACIFIC FINANCIAL CENTERS

It is observed that AI and big data talent is concentrated in the tertiary education and financial sectors in Hong Kong, while in other cities, the distribution of talent is more balanced across different industries. This may reflect the low diversity of Hong Kong’s economy and that the main career path for AI and big data professionals continues to lie in higher education and, to some extent, in the banking sector. On the contrary, professionals in other cities have multiple career options, creating mobility across industries which can help to spread new ideas and innovations to and from the finance industry. This vibrant exchange of AI and big data talent across industries is missing in Hong Kong, which could limit the cross-fertilization of ideas and innovations.

To supplement the macro analysis of AI and big data manpower development in the six Asia Pacific financial centers, we conducted an analysis based on the aggregate statistics derived from LinkedIn member profiles. While the ideal approach is to conduct census studies across the six centers, it is not practical given the rapid development in each financial center. As an alternative, we resorted to analyzing professional profiles of those who possess AI and big data related skills. Findings from the profile analysis shed light on the unique situation of each financial center, allowing a broad-brush comparison of the general characteristics of manpower development across the six financial centers. These aggregated member profiles are extracted from talent reports from LinkedIn and are further analyzed. Using the filter criteria provided by LinkedIn, we extracted aggregated profiles of talent that meet the following specifications: Locations: Hong Kong, Singapore, Shanghai, Shenzhen, Tokyo, and Sydney Skills: Big Data, Big Data Analytics, Data Science, Data Mining, Data Analysis, Statistics, Predictive Analytics, Data Visualization, Statistical Data Analysis, Predictive Modelling, Statistical Modelling, Business Analytics, Analytics, Google Analytics, Web Analytics, Data Analytics, Data Ethics, Business Intelligence (BI), Data Modelling, Artificial Intelligence (AI), Natural Language Processing (NLP), Deep Learning, Machine Learning, Neural Networks, TensorFlow, Artificial Neural Networks, Convolutional Neural Networks (CNN), and Conversational AI Industry: Banking, Investment Banking, Investment Management, Venture Capital and Private Equity, Insurance, Financial Services, and Capital Markets

We identified the top ten employers of AI and big data professionals of each city in two ways. Firstly, we identified the top ten employers of the overall talent pool in each city. These professionals are employed in different industry sectors and are not necessarily in the finance industry. The results are shown in Table 3.1. It is interesting to note that in Hong Kong, most of the AI and big data professionals work in universities, while in the other five cities they work in more diverse industries.

In Singapore and Sydney, four out of the top ten employers are financial institutions. AI and big data professionals work mainly in the industrial, technology, and social media sectors in Shanghai and Shenzhen. In Tokyo, they work mainly for US technology and internet firms.

Date: Mid-July 2021 3.1 Employers of AI and big data professionals

34 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Table 3.1 Top 10 Employers of AI and Big Data Professionals Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney HSBC DBS Bank Rakuten GroupTrip.com Huawei BankCommonwealth The University of Hong Kong UniversityNational of Singapore Amazon ByteDance Tencent Westpac The HongUniversityChineseofKong CharteredStandard Bank Google SAP Morningstar University of Sydney The Hong Kong University of Science Technologyand UniversityTechnologicalNanyang Accenture Huawei S.F. Express Co., Ltd. UNSW The Hong UniversityPolytechnicKong Shopee IBM IBM Walmart Westpac Group Ernst & Young Google Deloitte Alibaba Group Foxconn GroupMacquarie City University of Hong Kong Citi UniversityThe of Tokyo Tencent IBM University SydneyTechnologyof Citi UOB Microsoft Apple OPPO GroupWoolworths Cathay AirwaysPacific Accenture Amazon Web Services Microsoft ByteDance Optus Bank of China Hong Kong Grab JAPANYahoo! Ernst & Young GroupBusinessConsumerHuawei Transport for NSW

35 3.2 Employers of AI and big data professionals in the finance industry We probed deeper to examine the affiliations of AI and big data professionals in the finance industry of each city. Table 3.2 depicts the top ten employers of each city. What we found is that most of the employers in Hong Kong, Singapore, Tokyo, and Shanghai are large financial institutions with a global presence. In Shenzhen and Sydney, employers are largely leading financial institutions in the country and the region. Large financial corporations such as HSBC, Standard Chartered, and Citi have operations in multiple cities with a sizeable number of AI and big data employees in each city. Table 3.2 Top 10 Employers of AI and Big Data Professionals in the Financial Industry Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney HSBC DBS Bank Nomura HSBC Morningstar BankCommonwealth Citi CharteredStandard Bank LPBloomberg Citi Ping An Westpac Bank of China Hong Kong Citi MUFG Ping An BankMerchantsChina Westpac Group Hang Seng Bank UOB AIG KPMG China SecuritiesGuosen GroupMacquarie Morgan Stanley OCBC Bank Mizuho UBS Ping An Bank Co., Ltd. IAG Goldman Sachs Credit Suisse CorporationPayPay CharteredStandard Bank WeBank AMP DBS Bank UBS SachsGoldman Bank Ltd.cationsCommuni-ofCo.,London HSBC NAB AIA ChaseJPMorgan&Co. StanleyMorgan Fosun Co.,SecuritiesMerchantsChinaLtd. ANZ CharteredStandard Bank GIC MetLife StanleyMorgan Ping Ltd.Company,SecuritiesAn Suncorp Group J.P. Morgan SingaporeCompanyAssurancePrudential AXA UnionPayChina KPMG China QBE Insurance

To understand the AI and big data skills of finance professionals, we estimated the proportion of professionals with (1) banking/finance-related skills only, (2) AI/big data-related skills only, and (3) both sets of skills in the finance industry. We first extracted the number of professionals in the finance industry based on the seven sectors of each of the six financial centers provided by Linkedln. This gives us the total population of finance professionals in each city. We then extracted common banking/finance-related skills from each financial center and aggregated them into a combined list.

36 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers

We identified the top 100 skills that are related to banking or finance only. By merging these 100 skills with the filter on AI and big data skills we presented earlier, we extracted the talent whose skills fall into one of the following categories:

Table Proportion3.3 of Professionals with AI/Big Data-related and/or Banking/ Finance-related Skills in the Financial Industry

Proportion Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney With relatedAI/bigonlydata-skills 0.79% 1.05% 1.17% 1.15% 0.87% 0.86% With both sets of skills 9.41% 12.84% 7.46% 6.56% 3.72% 14.41% With relatedfinance-business/onlyskills 89.80% 86.11% 91.37% 92.29% 95.41% 84.72%

(1) Banking/finance-related skills only (without AI/big data-related skills) (2) AI/big data-related skills only (without banking/finance-related skills) (3) having both AI/big data and banking/finance skills Table 3.3 summarizes the analysis results. Within the finance industry, only a very small proportion of professionals possess only AI/big data-related skills, with Hong Kong having the smallest proportion. For Hong Kong, the proportion of professionals having both skill sets is a modest percentage of 9.41%. For all financial centers, the majority of the professionals possess only finance and banking related skills but not AI and big data skills.

3.3 AI/big data-related vs. business/finance-related skills comparison among the six financial centers

51.65% 63.56% Capital Markets 2.21% 1.11% 1.15% 6.02% 7.11% 1.05% Note: % of

is shown in the parentheses.

37 3.4 Categories of AI and big data professionals in the financial industry

Table 3.4 shows the breakdown of AI and big data talent in the seven finance industry sectors. In general, the financial services sector has the highest proportion of AI and big data talent in all six cities. Banking is the second largest sector for all cities except Tokyo where Insurance ranks 2 nd Insurance comes in 3rd place for Hong Kong, Singapore, Shanghai, Shenzhen, and Sydney. For Tokyo, Banking ranks third. The investment sector ranks 4th in all cities, while Investment Banking, Venture Capital and Private Equity, and Capital Markets rank from 5th to 7th in different cities. It is evident that the distribution of AI and big data talent depicts a fairly consistent distribution across the different sectors in the finance industry in the six cities. Kong Singapore Tokyo Shanghai Shenzhen 12.90% 13.00% 8.33% 9.83% 51.55% total It is worthwhile to note that the breakdown in Table 3.4 does not add up exactly to the total number of AI and big data professionals in the finance industry as shown in Table 3.3. This is because some LinkedIn members may hold multiple positions in the same firm, leading to more than one count of the same individual in the Report. However, the difference is small (< 2%) and does not have a significant impact on the general observations.

17.63% BankingInvestment 2.88% 0.78% 3.00% 7.58%

Table Proportion3.4 of AI and Big Data Professionals in each Financial Sector Financial Sectors Hong

0.61% ManagementInvestment 7.98% 7.63% 6.48%

7.84% 3.41% Venture Capital & Private Equity 2.34% 3.83% 6.56% 5.23% 4.54% 1.49% Insurance 10.71% 9.46% 16.33% 8.41% 8.77% 13.81% Financial Services 55.34% 43.68% 59.93%

Sydney Banking 20.24% 35.32% 7.74%

38 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers In Table 3.5, we break down AI and big data talent into three levels – junior, middle and senior - based on a broad and general classification of titles among AI and big data professionals in these cities. We focused on the top 100 most common titles in each city. Hong Kong has a relatively uniform distribution of professionals across the three levels. Singapore and Tokyo have the highest distribution at the senior level, with Singapore having the highest percentage of senior professionals among the six cities. This may reflect the fact that Singapore financial institutions attach a higher level of strategic importance to AI and big data. On the other hand, Shanghai, Shenzhen, and Sydney have the largest share at the middle level. Table Proportion3.5 of AI and Big Data Professionals at Different Managerial Levels in the Finance Industry based on the Top 100 Job Titles City Junior Middle Senior Hong Kong 28.34% 36.60% 30.14% Singapore 21.96% 30.60% 41.24% Tokyo 18.42% 34.30% 37.58% Shanghai 29.06% 40.71% 24.13% Shenzhen 29.55% 43.05% 21.63% Sydney 19.25% 46.99% 27.25% In addition to managerial levels, we also did a breakdown of the titles among AI and big data professionals into technical and management positions based on a broad categorization approach (Table 3.6). Table Proportion3.6 of Management and Technical AI and Big Data Professionals in the Finance Industry based on the Top 100 Job Titles City Management Technical Hong Kong 79.59% 16.33% Singapore 76.07% 18.94% Tokyo 72.55% 19.09% Shanghai 75.94% 18.70% Shenzhen 71.33% 23.21% Sydney 70.23% 25.77%

The Hong Kong University of Science Technologyand UniversityManagementSingapore UniversityKeio UniversityShanghai of Finance Economicsand UniversityPeking University SydneyTechnologyof City University of Hong Kong PolytechnicTemasek UniversityKyoto UniversityShanghai UniversityWuhan UniversityMacquarie

Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney The University of Hong Kong UniversityNational of Singapore UniversityThe of Tokyo UniversityFudan UniversityShenzhen UNSW

The HongUniversityChineseofKong UniversityTechnologicalNanyang UniversityWaseda Shanghai Jiao Tong University Sun UniversityYat-Sen University of Sydney

Table 3.7

As shown in Table 3.7, most of the AI and big data talent are graduates of local universities. Local universities understand the needs of their financial industries and can incorporate them into the program curricula. Students and graduates are also better informed about career opportunities via oncampus seminars, alumni engagement, and internship opportunities. Local universities remain the major source of AI and big data talent in the medium and long term for each city.

Top 5 Education Affiliations of AI and Big Data Professionals in the Financial Industry

3.5 Academic Affiliations of AI and big data professionals in the financial industry

The Hong UniversityPolytechnicKong University of London UniversitySophia UniversityTongji The HongUniversityChineseofKong Western UniversitySydney

For Tables 3.5 and 3.6, position titles were retrieved from LinkedIn profiles and were classified into managerial level (junior, middle, and senior) and function (management vs technical) by two independent coders who discussed and resolved any discrepancies between them. Note that the classification was based on general practices and did not take into account the specific circumstances and locations of individual firms. There were titles that were not classified into either category. This explains why the ratios add up slightly below 100%.

Table 3.8 shows the top ten skills of AI and big data professionals in each city. Note that a member profile can list multiple skills, and the ranking depicted in Table 3.8 is based on the number of members mentioning a particular skill in his/her profile. It is evident that data analysis, which is ranked top of the list in all cities, is the most important skill for AI and big data professionals. This is understandable as many fintech applications are data-driven, requiring a good level of competence in data processing and analysis. Other skills are general finance, banking, and risk management skills. Coding and database knowledge, including Python and SQL, are also listed as important skills for the profession. 3.8 Top Ten Skills of AI and Big Data Professionals

Table

40 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers 3.6 Popular skills of AI and big data professionals in the financial industry

in the Finance Industry Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney Data Analysis Data Analysis Data Analysis Data Analysis Data Analysis Data Analysis Finance Banking Finance Finance Finance AnalysisBusiness Banking Finance Python AnalysisFinancial AnalysisFinancial Analytics AnalysisFinancial Analytics Analytics Banking Banking Finance Analytics AnalysisBusiness SQL Python Python Banking ManagementRisk ManagementRisk AnalysisFinancial ManagementRisk RepresentationData ServicesFinancial AnalysisBusiness SQL ManagementRisk ModelingFinancial ManagementRisk ManagementRisk ModelingFinancial AnalysisFinancial AnalysisBusiness SQL Statistics ManagementStakeholder Python Python Banking Statistics SQL SQL SQL IntelligenceBusiness LearningMachine R ModelingFinancial IntelligenceBusiness

Tokyo maintains a relatively balanced inflow and outflow with Singapore, Hong Kong, Shanghai, and Sydney. The level of talent mobility is also low for Tokyo. Shanghai is able to recruit AI and big data talent from other financial centers. It has net inflow from the other five cities during the same period. For Shenzhen, it has net inflows from Sydney and Singapore, and net outflows to Hong Kong and Shanghai. The situation in Sydney is interesting. It has net outflows to Hong Kong, Singapore, Shanghai, and Shenzhen and a very small inflow from Tokyo. As a reference, the total inflow and outflow of talent during the period between the six cities are also shown at the bottom of each network.

All six financial centers are proactively recruiting AI and big data talent in recent years. As discussed in Section 2, policy measures are developed to recruit and retain AI and big data professionals in each city. It would be interesting to understand the flow of these professionals across cities. We made use of the Linkedln data collected for the six cities and conducted a talent flow analysis between them over a 12-month period ending June 2021. Note that this period coincides with the COVID-19 outbreak which has caused major disruptions to the mobility of professionals as overseas travel and assignments have largely been suspended. The talent flow diagrams for the six financial centers are depicted in Figure 3.1. We also reported the total number of AI and big data professionals flows (both inflow and outflow) between the focal financial center and all other cities/regions (not limited to the six financial centers during the same period).

41 3.7 Inflow and outflow of AI and big data professionals among the six financial centers

As shown in Figure 3.1a, there is a noticeable net outflow of talent from Hong Kong to Singapore over the investigation period. The ratio of outflow to inflow is 1.7:1. There is also a net inflow from Shenzhen to Hong Kong, yet the ratio is more moderate. A net inflow of talent from Sydney to Hong Kong is observed with a ratio of 1.6:1. Overall, there has been a net outflow of talent from Hong Kong and the primary destination is Singapore during this period.

For Singapore, the inflow and outflow of AI and big data professionals are more balanced. There are net inflows to Singapore from Hong Kong and Sydney, and a small net outflow to Shenzhen and Tokyo.

42 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1aDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Hong Kong Talent Flow Total flow of talents to/from Hong Kong: 1,663 6441 54 48 22 36 5 4 15995

43 Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1bDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Singapore Talent Flow Total flow of talents to/from Singapore: 1,758 2511 3214 16 44 37 15995 9

44 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1cDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Tokyo Talent Flow Total flow of talents to/from Tokyo: 326 42 14316 5 4

45 Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1dDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Sydney Talent Flow Total flow of talents to/from Sydney: 1,556 44 3637 9 2 3 7 19 22

46 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1eDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Shenzhen Talent Flow Total flow of talents to/from Shenzhen: 478 4841 37 11 40 9 9 2

47 Hong Kong Shanghai Shenzhen Tokyo Sydney Singapore Figure Network3.1fDiagrams Showing the Flow of AI and Big Data Talent in the Finance Industry across the Six Cities - Shanghai Talent Flow Total flow of talents to/from Shanghai: 1,191 25 40 32 54 64 4 2 7 3719

48 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers AnalystData PresidentVice Director Analyst Associate AnalystBusiness Co-founder AnalystBusinessSenior Founder ManagerProduct ManagerProject EngineerSoftware Manager PresidentViceAssistant OfficerExecutiveChief DirectorManaging ManagerSenior DirectorAssociate Consultant DirectorExecutive AnalystSenior AdvisorFinancial Note. The results are based on aggregated data from all six financial centers. Apart from that, we also calculated the talent flow between finance and other industries for each financial center as shown in Table 3.9. We observed that there are generally more inflows from nonfinance to the finance industry for all cities, and the net inflow of talent from non-finance to finance is the largest in Hong Kong with a ratio of 2:1, followed by Sydney with a ratio of 1.96:1 during the period. Table 3.9 The Talent Flow of AI and Big Data Professionals between Finance and Other Industries Talent Flow Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney From Non-Finance to Finance 1,222 2,510 215 770 157 3,259 From Finance to Non-Finance 611 1,598 148 508 118 1,666 Net Inflow Ratio 2:1 1.57:1 1.45:1 1.52:1 1.33:1 1.96:1 100012008006004002000

49 ManagerProjectSenior AnalystQuantitative ScientistData EngineerSoftwareSenior ManagerAccount ManagerGeneral ManagerInvestment SpecialistData ManagerMarketing ManagerAnalytics AnalystFinancial AssociateSenior AnalystInvestment Member OwnerProduct AnalystDataSenior ManagerPortfolio MemberBoard ManagerRelationship ManagerAssistant Partner OfficerOperatingChief AnalystBankingInvestment ManagerProductSenior Trader Intern EngineerData Researcher

Figure 3.2

The Distribution of the Top 50 Job Titles of AI and Big Data Professionals in the Financial Services Sector 3.8 Job titles and skills analysis in the financial services industry

In this section, we focus on the financial Service sector since it employs the largest proportion of AI and big data talent in each city (Table 3.4). We report the job title distribution and the associated top skills for each job title. We further aggregated the data over the six financial centers. Figure 3.2 depicts a bar chart showing the distribution of the top 50 job titles of AI and big data professionals.

The most common job title is data analyst with more than 1,000 AI and big data professionals associated with this title. Table 3.10 shows the top five skills associated with each job title. Other than data analysis, knowledge in banking and finance are also very common and important business-related skills.

Regarding technical skills, the top skills are data analysis, followed by programming languages including SQL and Python.

50 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Table 3.10 The Top 5 Skills Associated with the Top 15 Job Titles of AI and Big Data in the Financial Services Sector Job (RankedTitlesby Number of Professionals) Data Analyst Data Analysis SQL Vice President Data Analysis Finance Director Finance Banking Analyst Data Analysis Finance Associate Data Analysis Finance Business Analyst Business Analysis Data Analysis Co-Founder Finance Analytics Senior Business Analyst Business Analysis Requirements Gathering Founder Finance Analytics Product Manager Product Management Data Analysis Project Manager Business Analysis Data Analysis Software Engineer Software Development SQL Manager Data Analysis Finance Assistant Vice President Data Analysis Banking Chief Executive Officer Finance Analytics Note. The results are based on aggregated data from all six financial centers.

51 Skills Data Analytics (ProgrammingPython Language) Analytics Banking Business Analysis Analytics Risk Management Analytics Data Analysis Financial Analysis Python (Programming Language) SQL Financial Analysis Banking SQL SQL Banking Requirements Analysis Data Analysis Banking Financial Services Business Process Requirements Analysis Data Analysis Data Analysis Banking Financial Services Finance Banking Business Analysis Banking Project Delivery Risk Management Java Python (Programming Language) JavaScript Financial Analysis Business Analysis Banking Finance Business Analysis Financial Analysis Risk Management Financial Services Banking

52 Policy Recommendations 4.POLICY RECOMMENDATIONS

Furthermore, continued education programs for working professionals who are seeking to upskill should be made readily available. The Hong Kong Government may, therefore, consider implementing policies to encourage financial firms to collaborate with the city’s world class knowledge infrastructure – universities and other institutes – to develop and upskill their internal talent so that it can become ready to assume technical posts related to AI and big data within enterprises.

2. Increasing the supply of AI and big data talent

Hong Kong has an opportunity to leverage its highly educated workforce to support the city’s standing as a global financial center and as an Asia’s world city. The finance industry has historically played an important role in the economy of Hong Kong, contributing 21.2% of GDP in 2019 and providing ample employment opportunities to workers in various IT-related fields. Other economic sectors including import/export, wholesale and retail trades, and social and personal services are also expected to see annual growth in the workforce of 2.5% till 2027.

Talent availability is an extremely important consideration for successful adoption of AI and big data technologies in the finance sector. Hong Kong’s financial industry needs a continuous supply of manpower that is adequately skilled in all the three relevant skills – AI, big data and finance. In addition to the existing generalized policy framework for developing workforce in STEM and IT at the school and higher education levels, targeted policies for the training of manpower in AI, big data and finance are required. This will be applicable to undergraduate and postgraduate programs to ensure that there is a healthy balance between seats available to students and the quality of instructions provided.

1. The Hong Kong Government should better understand the existing and anticipated talent gap for AI and big data technologies in the financial services sector

This section outlines six key policy recommendations for the Hong Kong Government. These steps will enhance the readiness of Hong Kong’s financial industry for future challenges and keep it on a healthy growth trajectory.

In the wake of the ongoing pandemic and rapidly evolving market, the financial industry across Asia Pacific including Hong Kong has been adopting AI and big data technologies to create and deliver value to its customers. Talent development, in the areas of AI and big data is imperative for successfully deploying these technologies in the finance sector. A shortage of AI and big data talent poses the greatest challenge to the digitalization of financial services. It is vital for major stakeholders including the government, education institutions and financial market participants to better understand the supply and demand of the relevant AI talent and identify any gaps for formulating and implementing suitable policy interventions.

5. Develop well rounded, multidisciplinary talent

4. Leverage AI to solve other sustainable development challenges in Hong Kong Hong Kong also needs to create diverse employment opportunities for its AI and big data manpower as most of them are concentrated within universities and the banking sector. This can be made possible by widening the view of how AI can help solve economic, societal or environmental problems in Hong Kong. Policies, not only for university industry linkages, but also industry to industry contacts for allowing the mobility of AI and big data talent across industries will be immensely valuable. This can spur innovation in many industries outside of the financial services sector and enhance the overall quality and opportunities available to AI and big data manpower in Hong Kong.

Hong Kong is also facing a challenge from the perspective of the professionals working in the financial industry who possess both management and technical skills. Only 9.41% of the professionals have these three skills in the finance sector. Policy interventions should, therefore, encourage development of a package of skills. At the university level, academic programs being run especially by the business schools can be redesigned for nurturing AI and big data talent for the finance sector in Hong Kong.

54 Policy Recommendations

3. Match students with opportunities

At least five major universities in Hong Kong along with some banks are amongst the top ten employers of AI and big data professionals in the city. This affords a huge opportunity for the Hong Kong Government to strengthen the university industry linkages through relevant policy framework so that the talent pool from the universities can be placed into the financial industry. Through these linkages, firms in the financial services sector can also give their input regarding development and evolution of the courses and curricula being taught at the universities. Students of these universities can also be placed as interns and apprentices in the financial industry. This will open the doors for their employment after their graduation as they can develop the requisite AI and big data skills during their internships and apprenticeships with the financial firms. Besides, technology incubators like Cyberport, ASTRI and HKSTP should continue playing their roles in Hong Kong’s innovation ecosystem in developing domestic talent pipelines in AI and big data.

A large portion of professionals in Hong Kong’s financial industry has only business and finance related skills (89.89%). These professionals can be motivated and encouraged through policies for pursuing non-degree, upskilling short courses and customized professional training in AI and big data offered by universities and training institutions across Hong Kong.

Before the start of the pandemic, it was plausible to roll out policies such as tax incentives, subsidies and immigration schemes to attract AI and big data talent from overseas into the finance sector.

Hong Kong should also monitor and manage the overall talent outflow of AI and big data manpower.

However, all stakeholders must come together to devise long-term career growth prospects for the retention of local and international talent. It becomes easier to retain talent if an attractive roadmap for their career development is set out, and this needs to be done on a priority basis in Hong Kong.

However, given the current uncertainties around the pandemic and continued restrictions on overseas travel, policies that capitalize on local universities and Hong Kong’s knowledge infrastructure can actually bring about greater dividends. Moreover, a reliance on the domestic institutions for a supply of potential employees and nurturing AI and big data talent is beneficial as these institutions are embedded in Hong Kong’s economy and society, and most of them are in a good position to understand the practices, policies and strategic directions of the local financial industry. They can, therefore, offer tailor-made programs as per the needs of Hong Kong’s financial industry.

Retention of talent within a geographic domain may depend on several factors i.e., political, social, economic and culture. Hong Kong has been taking measures to provide comfortable multilingual living environments along with other facilities such as health infrastructure and educational institutions for the children of international workers in an attempt to retain AI and big data talent in the financial industry.

55 6. Support Retention of AI and big-data talent in Hong Kong

It is clear that demand for AI and big data talent in the financial sector will continue to grow. Strategies to foster such talent development in Hong Kong will help narrow the skills gap and enable talent recruitment and Hongretention.Konghas already launched various AI and big data talent development initiatives to support financial innovation, create incentives and streamline procedures for overseas talent recruitment.

5.CONCLUSION

1. Better understand the existing and anticipated talent gap for AI and big data professionals in the financial services sector.

2. Increase the supply of AI and big data talent by delivering and incentivizing skills development opportunities and training.

5. Develop well rounded, multidisciplinary talent by promoting AI and big data skills development among financial professionals and vice versa.

This Report has also recommended that the Hong Kong Government should:

3. Match students with AI and big data career opportunities by facilitating academia-industry collaborations, networking, and career matching.

6. Support the retention of AI and big data talent in Hong Kong by exploring other incentives to make Hong Kong an attractive location for AI and big data professionals.

Ultimately, AI and big data talent development will be a critical priority for international financial centers and Hong Kong is no exception. Integrating AI and big data technology functions into the financial sector will be critical to keeping Hong Kong as a leading international financial centre.

AI and big data have enabled Asia Pacific’s financial services sector to adapt and respond to the challenges posed by COVID-19. This will be critical to ensure that the financial industry continues to provide value to its customers and society at large. This Report has highlighted the rapidly evolving landscape for AI and big data talent in six Asia Pacific financial centers, identifying trends in the AI and big data talent pool, as well as the steps taken in other major cities across the region to fill the growing talent gap facing each market.

56 Conclusion

4. Leverage AI to solve other sustainable development challenges in Hong Kong by exploring how AI can be applied to other economic, social, or environmental challenges.

Educational institutions have provided fintech training programmes, and accelerated careers by providing and promoting continued education. These steps will go a long way to ensure a steady supply of skilled AI and big data talent.

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