Phase 2 of NovA! Addresses Key Concerns Faced by, and Supports Sustainable Finance in Real Estate Sector

15 November 2023

NovA! is a platform that leverages artificial intelligence (“AI“) and data analytics to support financial institutions and companies on their sustainability journey. The Monetary Authority of Singapore (“MAS“) announced on 14 November 2023 that the NovA! consortium has developed a Minimum Viable Product (“MVP“) from Phase 1 of the project that helps banks gain greater transparency and accuracy on borrowers’ sustainability profiles and performances when issuing Sustainability-Linked Loans (“SLLs“) in the real estate sector. In turn, borrowers’ (e.g. real estate owners and developers) can access green funds more easily and at an earlier stage.

In Phase 2, MAS will work with the Building and Construction Authority (“BCA“) to tap on BCA’s Super Low Energy Building (SLEB) database so that NovA! can access country-wide data on green buildings. This will allow banks to identify prospective green building projects, achieve real-time Sustainability Performance Targets (“SPTs“) monitoring, and accelerate green financing within the real estate sector. NovA! will also extend its AI capabilities to support sustainable financing in other sectors (e.g. power and manufacturing industries).

Key challenges	Core features of MVP addressing the corresponding challenges
Inaccurate settings for SPTs due to data scarcity and inconsistency	Setting of SPTs for SLLs in real estate sector via peer and industry benchmarking. AI technology helps to harness data from government sources and to conduct property-specific peer and industry comparisons, thereby enabling banks to judiciously set Key Performance Indicators (KPIs) and develop practical SPTs for a more accurate sustainability assessment.
Greenwashing concerns which affect about 50% of SLLs	Control greenwashing by monitoring against selected KPIs/SPTs Using buildings’ energy consumption data on a continuous basis at-source, NovA! allows banks to compare borrowers’ current sustainability performance with the agreed SPTs on a timelier basis, and allows risk assessment teams from banks to quickly identify discrepancies, ensure SLLs maintain their intended impact, and curb greenwashing.
Inefficient processes leading to manual errors in reading and interpreting disclosures from lenders	Improve processing sustainable finance transactions through Autonomous Documentation Insights Engine (ADIE) Using Natural Language Processing, banks’ relationship managers, know your clients (KYC) teams, and sustainable finance units can quickly and accurately extract sustainability insights from diverse sources. This moves away from manual processing of disclosure documents and enables informed decision-making based on comprehensive data extracted from borrower disclosures.