SEA FinTech Has Only a 3.1% Penetration of AI & ML

  • Artificial Intelligence
  • 30.03.2023 10:25 am

In 2022, the share of FinTech companies in the SEA region officially using AI and ML technologies in their stack reached 3.09% (807 out of 26,105 companies), steadily increasing from 2.88% in 2020 and from 3.03% in 2021.

The Digital Insurance sector holds the highest penetration rate of AI&ML technologies. The number of companies using AI&ML in this sector is growing at an average of 35.6% per year. This is followed by the Digital Accounting (33.5%) and Digital Banking (31.5%) sectors.

Other FinTech industries have seen the following average increase in growth: Cryptocurrencies & Blockchain - 28.7%, Digital investments - 21.4%, E-Commerce - 19.4%, Alternative Lending - 19%, Business management - 18%, HR & Payroll - 17.8%, Cybersecurity - 17.5%, E-Wallets - 17%, Payments & Transfers - 15.4%, Financial Advisors - 14%.   

Singapore currently has the highest rate of AI&ML penetration in FinTech, at an impressive 5.36%. The country has seen a high overall economic development (about 0.5% of world GDP). Also its level of digitalization is one of the highest in the region: in 2022, 97% of the population had internet access, 94.4% had smartphones, and 97% had financial accounts. Lastly, there is a high level of private investment in FinTech (1.4% of all time in the world) and in AI technology (0.7%).

Laos also showed a high AI&ML penetration rate in FinTech at 4.08%. The development of FinTech is still in its infancy in Laos, with only 49 companies out of 26,105 in the region. Therefore, even a small penetration of AI & ML in the FinTech sector can be considered significant in this country.

Robocash Group analysts comment: “Artificial Intelligence & Machine Learning integration in the Southeast Asian FinTech domain went through its peak period between 2016 and 2019. The FinTech world has attained a “plateau”, though it may not last for long. Businesses are beginning to leverage the potential of AI&ML actively. This can result in an improved output. Nevertheless, AI and ML-based technology are not a one-size-fits-all solution that can guarantee success itself. So businesses must tailor them to their own operations and objectives to reach the greatest possible benefits.”

Related News