AI project on sustainable buildings here to have access to green real estate data

The Monetary Authority of Singapore said the initiative would be extended to support sustainable financing in other areas, such as power and manufacturing industries. ST PHOTO: LIM YAOHUI

SINGAPORE – A Singapore government-led artificial intelligence (AI) project looking at improving the sustainability of buildings here will soon have access to countrywide data on green real estate.

The Monetary Authority of Singapore (MAS) on Tuesday said a consortium it leads would tap the Building and Construction Authority’s (BCA) database in the second phase of Project NovA!, a platform that leverages AI and data analytics. This would help banks identify prospective green building projects, monitor real-time sustainability performance targets and accelerate green financing within the real estate sector.

MAS said the initiative would be extended to support sustainable financing in other areas, such as power and manufacturing industries.

Project NovA!, announced at the Singapore Fintech Festival two years ago, is a collaboration between Singapore-based banks and other entities to help financial institutions better assess companies’ environmental impact and identify risks.

The tie-up between the MAS-led consortium and BCA was announced at the Singapore Fintech Festival 2023 by Senior Minister of State for National Development and Communications and Information Tan Kiat How.

“Such a development promises to significantly accelerate green financing within the real estate sector,” he said at the festival’s policy dialogue on Tuesday.

He added that the NovA! platform promotes greater transparency and convergence of data, as well as the use of automation.

Buildings account for nearly 40 per cent of carbon emissions globally. In Singapore, they account for more than 20 per cent of emissions, so making buildings here more environment-friendly can move the needle in the Republic’s low-carbon transition, said Mr Tan.

He said that under the Singapore Green Building Masterplan, 80 per cent of buildings here are to be green by 2030.

In the same period, 80 per cent of new developments are to meet super low energy standards and 80 per cent of best-in-class buildings are to achieve an improvement in energy efficiency over 2005 levels.

To meet these goals, businesses and investors can play a leading role by channelling funds into green initiatives and low-carbon building projects, he added.

Besides the BCA collaboration, the consortium also created a basic version of a new product that assists banks to tap AI when issuing sustainability-linked loans in the real estate sector.

MAS said this new product was developed in the first phase of the project.

The newly developed basic product would address three challenges identified in the first phase of the project, including inaccurate settings for sustainability performance targets due to data scarcity and inconsistency, and greenwashing concerns, which affect about half of sustainability-linked loans.

To address the challenges, the product would set performance targets for sustainability-linked loans in the real estate sector through peer and industry benchmarking. It would also monitor against selected key performance indicators to curb greenwashing, and beef up the processing of sustainable finance transactions through an autonomous documentation insights engine.

The consortium also published a White Paper that documents the methodology used in the system of the new product.

Both MAS chief fintech officer Sopnendu Mohanty and BCA group director of environmental sustainability Ang Kian Seng noted that the tie-up would help the industry move closer to Singapore’s net-zero and decarbonisation goals.

The MAS-led consortium comprises 23 entities, including Singapore’s three local banks, Bank of China, Hitachi Asia, the National University of Singapore’s Asian Institute of Digital Finance, real estate services firm Savills, Singapore’s investment company Temasek, and Tsinghua University’s Institute for Internet Industry.

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