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          Singapore introduces principles for use of AI, data analytics in finance

          Source: Xinhua| 2018-11-12 19:18:05|Editor: Shi Yinglun
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          SINGAPORE, Nov. 12 (Xinhua) -- The Monetary Authority of Singapore (MAS) released a set of principles to promote fairness, ethics, accountability and transparency, or FEAT, in the use of artificial intelligence (AI) and data analytics in finance, the MAS's Managing Director Ravi Menon said on Monday.

          He told the Singapore FinTech Festival 2018 that the set of principles is the first of its kind in the world, where the regulator and industry have come together to set guidance on the responsible use of AI and data analytics.

          "I am sure this is a living document that will be continually updated as we learn more," Menon added.

          According to a statement from the MAS, the FEAT principles provide guidance to the firms offering financial products and services on the responsible use of AI and data analytics to strengthen internal governance around data management and use.

          This will foster greater confidence and trust in the use of the two technologies, as firms increasingly adopt technology tools and solutions to support business strategies and in risk management, the statement added.

          The Singapore FinTech Festival 2018 opened on Monday. This year, the event attracted close to 40,000 participants from more than 100 countries and regions, said Menon.

          He also announced at the event that the MAS is joining hands with the Infocomm Media Development Authority of Singapore to create a cross-border innovation platform for small and medium-sized enterprises (SMEs), called Business sans Borders, and the platform will begin with a proof-of-concept next year, which will leverage on AI to facilitate the internationalization and digitalization of SMEs.

          To support SMEs, Menon also said the MAS and the Government Technology Agency of Singapore are working with the industry to facilitate financial institutes' credit assessment of SMEs by collecting and using trusted government data.

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