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

7 6 Introduction 1. INTRODUCTION 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. 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 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. 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. 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. 1. https://www.investopedia.com/articles/personal-finance/022415/top-10-countries-save-most.asp 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.