Singapore Regulator Deploys AI-Powered Tool For ESG Assessment

Published on: 22 June 2022 12:35 PM
by KnowESG
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The Monetary Authority of Singapore (MAS) is deploying API-powered NovA! to help financial institutions (FIs) assess the sustainability performance of Singapore’s real estate sector.

NovA! is part of the National Artificial Intelligence (AI) Programme in Finance and is aimed at helping FIs harness AI to generate insights on financial risk.

Leveraging the AI-powered programme, financial institutions in Singapore can perform environmental, social, and governance (ESG) risk assessments for originating, underwriting, and servicing sustainability-linked loans.

Singapore’s financial watchdog explained the use case for financial institutions, from origination, underwriting, and servicing of loans:

  • At loan origination, FIs can use NovA! to identify real estate corporate borrowers whose sustainability metrics can be improved, by comparing their historical environmental performance to that of their peers;

  • During underwriting, NovA! will assist FIs to set appropriate sustainability performance targets (SPTs) for the borrowers, by comparing the borrowers’ SPTs with the SPT Industry Benchmark generated by NovA!;

  • For loan servicing, NovA! will compare the actual sustainability performance indicators (through direct use of metres or sensors) against the borrower’s self-declaration to detect greenwashing.

Sopnendu Mohanty, Chief FinTech Officer, MAS, commented:

“NovA! will provide a valuable tool to help FIs generate prompt and actionable insights using structured and unstructured datasets and advanced computing. This will better enable financial institutions to direct financing towards sustainable projects and companies that meet sustainability performance targets.”

The solution also leverages natural language processing (NLP) to automatically extract relevant information from documents. This will reduce the overall cost of operations and the amount of time it takes to collect, process, and analyse data.

Source: Finance Feeds

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