COVID -19 has accelerated an unprecedented level of technological change in financial markets and it has ushered scaled Artificial Intelligence (AI)/Machine Learning (ML) as the new normal in financial services in 2020.
Refinitiv has launched the findings of its second annual AI/ML Report, which explores the current market landscape for AI and ML, as well as the impact of COVID-19 on AI/ML.
The report reveals that 72% of firms’ AI/ML models were negatively impacted by COVID-19 and 40% of firms globally expect to increase investment in AI/ML as a result of the pandemic. Please find the full report attached and key APAC findings below for your reference.
Sanjna Parasrampuria, Head of Refinitiv Labs in Asia, says:
“Setting up AI/ML capabilities has become less of a problem, as talent and investment that were previously difficult to secure are more easily available this year. The maturity curve has moved up since our 2018 survey and we are now putting plans into production rather than creating capabilities. Since Asia never had the same historical data as the west to build their models and has levelled up its knowledge of unstructured data, this new status quo in the post-COVID world might even help Asia build new models, better and faster than their Western counterparts.”
Key Asia-Pacific (APAC) findings include:
ML advances move from ‘hype’ to reality
• ML continues to be a core component of business strategy, with significant investment in this area.
o Organizations in the Americas are leading in terms of ML maturity and investment levels, followed by those in Asia-Pacific.
o For 69% of APAC respondents, AI/ML is a core component of their business strategy
o 78% of APAC organizations make significant investment in AI/ML
• As ML adoption increases globally, ML and data science teams have also expanded, including APAC.
o Over one-third (39%) of APAC respondents expect an increase in number of data science roles in 2021
Asia set to capitalise on AI/ML investment research, idea generation
• Majority of APAC respondents deployed ML for investment research and idea generation, which is significantly higher than EMEA and Americas
o AI/ML for Idea Generation trumps Risk Management in APAC: 40% of APAC respondents deployed ML for investment research and idea generation, which is significantly higher than EMEA (19%) and the Americas (35%)
o Unstructured data is racing ahead in APAC due to the lack of structured data: 16% of APAC respondents use unstructured data in 2020, as compared to 1% in 2018
o As global trading hubs, more companies in APAC are leveraging commodities, supply chain and shipping data compared to other the Americas and EMEA
Barriers to adoption
• However, poor data quality and data availability continue to be the biggest barriers to successful adoption and deployment of ML
o Other barriers to delivering ML solutions such as talent and funding are progressively being overcome
o The APAC region experiences more barriers to AI/ML adoption than other regions
o Poor data quality is the biggest barrier cited by 62% of APAC respondents, and this is especially high compared to 50% in the Americas and 49% in EMEA