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

41 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 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. Table 3.8 Top Ten Skills of AI and Big Data Professionals 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 Business Analysis Banking Finance Python Financial Analysis Financial Analysis Analytics Financial Analysis Analytics Analytics Banking Banking Finance Analytics Business Analysis SQL Python Python Banking Risk Management Risk Management Financial Analysis Risk Management Data Representation Financial Services Business Analysis SQL Risk Management Financial Modeling Risk Management Risk Management Financial Modeling Financial Analysis Business Analysis SQL Statistics Stakeholder Management Python Python Banking Statistics SQL SQL SQL Business Intelligence Machine Learning R Financial Modeling Business Intelligence 3.7 Inflow and outflow of AI and big data professionals among the six financial centers 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). 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. 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.