MAS unveils AI tool to help financial institutions curb greenwashing

The AI utility is part of the National Artificial Intelligence Programme in Finance.

The Monetary Authority of Singapore (MAS) revealed the first use case of an AI utility, NovA!, which will help financial institutions (FIs) evaluate the sustainability efforts of the real estate industry and curb greenwashing.

NovA! is part of the National Artificial Intelligence Programme in Finance, which deals with FIs using AI to look into financial threats.

The programme will focus on improving FIs’ ability to assess firms’ environmental impact and determine environmental risks in its initial phase.

“FIs would be able to tap on NovA! for their Environmental, Social, Governance (ESG) risk assessment for originating, underwriting and servicing of sustainability linked loans,” MAS said in a press statement.

Under loan origination, FIs can use NovA! to determine real estate corporate borrowers, who could still improve their sustainability metrics by comparing their historical environmental performance.

During underwriting, NovA! will aid FIs to implement appropriate sustainability performance targets for the borrowers “by comparing borrowers’ sustainability performance targets (SPTs) with the SPT Industry Benchmark generated by NovA!.”

For servicing of loans, NovA! will compare the actual sustainability performance indicators against the borrower’s self-declaration to uncover greenwashing.

The NovA! ESG use case will also cut the amount of time for FIs to collect, process, and analyse data by using the natural language processing technique to automatically extract relevant information from documents.

Ultimately, this will also reduce the overall cost of operations for FIs.

To back FIs’ sustainability shift, the AI utility’s ESG case will be included with MAS’ Project Greenprint,

The AI's utility ESG case will be included in MAS' Project Greenprint, a collection of digital data utilities and initiatives that aims to enable a "transparent, trusted and efficient" ESG ecosystem through the use of technology and data.

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