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

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