Northern Trust survey: AI adoption gaining steam in Asia-Pacific

Nearly 60 percent of Australian-based institutional investors and asset managers expect meaningful adoption of artificial intelligence (AI) technologies for institutional financial services within two years. Singapore and Hong Kong-based institutional investors and asset managers anticipate it happening in two to five years.

These are the latest findings from a survey of investment manager and institutional investor clients attending Northern Trust events in its Sydney, Hong Kong and Singapore offices during the first quarter of 2018.

Half the respondents at the events in Hong Kong and close to 40 percent in Singapore highlighted that greater clarity was required in understanding the regulatory landscape in order for the financial services industry to adopt blockchain technologies. Meanwhile, half those surveyed in Australia noted high-level stakeholder engagement and counter-party cooperation as vital to financial services’ adoption of blockchain.

“In Asia-Pacific we have seen regulatory changes either built within existing policy frameworks, or shifted, as the market landscape transforms. Amidst the fast-evolving financial market ecosystem and the growing importance of technological innovation, collaboration amongst financial institutions, technology enablers, regulators and governments is vital to supporting the efficiency, security and transparency emerging technology can bring,” said Caroline Higgins, head of Global Fund Services for Asia at Northern Trust.

Northern Trust’s Market Advocacy and Innovation function drives interaction with key industry bodies, regulators and governments to positively influence market change in line with the organization’s strategic direction, and to support industry challenges.

Danielle Henderson, head of Market Advocacy & Innovation Research, Asia-Pacific at Northern Trust, said: “Market developments may include machine learning capabilities for faster and deeper data consumption, advanced analytics for better decision making and natural language generation for automated report commentary.”

Read the release

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