Singapore launches AI scheme in financial services, invests extra S$180 million in AI research

Singapore AI FSI Investment

Singapore is launching a new artificial intelligence (AI) scheme to deepen AI capabilities in financial services.

The National Artificial Intelligence (AI) Programme in Finance was launched at the Singapore FinTech Festival in November.

A joint initiative by the Monetary Authority of Singapore (MAS) and the National AI Office (NAIO), the programme aims to build deep AI capabilities in Singapore’s financial sector to strengthen customer service, risk management, and business competitiveness.

It is part of Singapore’s broader national strategy on AI to enable financial institutions to research, develop and deploy AI solutions. It aims to increase Singapore’s productivity through the adoption of AI and create new jobs through increased AI innovation and upskilling.

A new technical platform called NovA! will generate risk insights and help financial institutions leverage AI to assess companies’ environmental impact and emerging environmental risks. NovA! will be developed in the initial phase by Temasek’s AI centre of excellence Aicadium, local fintechs and Singapore-based banks.

Heng Swee Keat, Deputy Prime Minister and Coordinating Minister for Economic Policies, said an estimated US$100 trillion of climate-aligned funding will be needed over the next three decades to achieve the Paris Agreement targets on greenhouse gas emissions.

“NovA! will better enable financial institutions to assess these investments and their associated risks, and check against greenwashing,” he said in a speech at the FinTech Festival.

Singapore is also boosting investment in AI research by S$180 million to accelerate fundamental and translational AI research, adding to the S$500 million committed so far.

“One of the areas where we will invest more funds is resource-efficient AI,” Heng said.

“As a small country, our datasets are also small. So we need to better train our machines to learn from small but high-quality datasets. Our investment in AI R&D is not large relative to global investments in this field. But by focusing on where we can make the greatest impact, we can make every effort count.”