Study: APAC Financial Institutions Embrace AI/ML

Study: APAC Financial Institutions Embrace AI/ML

by November 19, 2020
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In Asia Pacific (APAC), adoption of artificial intelligence (AI) and machine learning (ML) in financial markets is accelerating. Though organizations in the Americas still lead in terms of AI/ML maturity and investment levels, those in APAC follow closely behind, according to a new research by Refinitiv, a leading provider of financial market data and infrastructure.

Refinitiv, which surveyed more than 420 data scientists, quants, technology and data decision-makers, found that 69% of respondents in APAC view AI/ML as a core component of their business strategy, and 78% are making significant investment in AI/ML.

Regional AI/ML trends via The Rise of the Data Scientist: Machine learning models for the future, Refinitiv, Source: AI/ML survey, August 2020

Regional AI/ML trends via The Rise of the Data Scientist: Machine learning models for the future, Refinitiv, Source: AI/ML survey, August 2020

COVID-19 is expected to further push adoption of AI/ML. According to the study, 31% of respondents in Asia said that AI/ML has become more important in their organization as a result of the pandemic, and 35% anticipate increased investment in AI/ML amid the public health crisis.

In particular, the research found that a much larger proportion of APAC respondents have deployed AI/ML for investment research and idea generation (40%) when compared to Europe, the Middle East and Africa (EMEA) (19%) and the Americas (35%).

Additionally, since APAC is home to several global trading hubs, more companies in the region are leveraging commodities, supply chain and shipping data compared to their international counterparts, the study found, making Asia’s AI/ML poised to shape the future of supply chain insights.

More companies in Asia use commodities, supply chain and shipping data, Refinitiv, October 2020

More companies in Asia use commodities, supply chain and shipping data, via The Rise of the Data Scientist: Machine learning models for the future, Refinitiv, Source: AI/ML survey, August 2020

China leads in AI innovation

Organizations in Northeast Asia, in particular, are investing heavily in AI/ML and protecting their intellectual properties (IPs) relentlessly. China and South Korea, specially, have significantly increased their filing of AI patent applications over the past two years.

According to data compiled by RS Components, a leading provider of industrial components and tools, China currently leads the world with 4,636 new applications between 2018 and 2019, representing 64.8% of all AI patent applications. South Korea ranks third after the US with 532 applications, representing 7.4% of all applications.

LG Electronics, from South Korea, made 731 AI patent applications over the two-year period. The figure is more than double of the company that has made the 2nd highest amount of applications, Ping An Technology, from China. Samsung Electronics, from South Korea as well, ranks third with 275 applications.

AI Innovators- The countries and companies in AI Patents, RS Components, January 2020

AI Innovators: The countries and companies in AI Patents, RS Components, January 2020

The Chinese government has declared its ambition for the country to become the world’s leading AI innovator by 2030. In July 2017, the State Council of China released the New Generation Artificial Intelligence Development Plan, outlining China’s strategy to build a domestic AI industry worth nearly US$150 billion in the next few years.

Government authorities have allocated lots of resources to pursue these ambitions: Beijing announced a US$2.1 billion AI-centric technology park, and Tianjin city plans to set up a US$16 billion AI fund.

Other findings

Data quality remains the biggest challenge for financial institutions (54%), followed by data availability (45%), two issues that have grown in prominence over the past two years, the Refinitiv research found. Meanwhile, issues related to talent, funding and talent appear to be fading.

Barriers to AI:ML adoption 2018 vs. 2020

Barriers to AI/ML adoption 2018 vs. 2020, via The Rise of the Data Scientist: Machine learning models for the future, Refinitiv, Source: AI/ML survey, August 2020

Over the next one to two years, financial institutions cited the three most critical areas of focus for their businesses as being extracting more value from data (63%), extracting better quality information (62%), and staying ahead of the competition (57%).

Which factors will become more important in the next one to two years?

Which factors will become more important in the next one to two years? via The Rise of the Data Scientist: Machine learning models for the future, Refinitiv, Source: AI/ML survey, August 2020

Join Refinitiv’s webinar taking place during the Singapore FinTech Festival, They will dig into the Asia Pacific results of the report to pick out the top AI and ML trends that the rest of the world needs to watch.

Register here

The Asia Pacific trends the world needs to watch

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