GreenFi provides an AI-enabled software platform for financial institutions and brands to automate ESG due diligence and risk assessment. The system aggregates complex, siloed sustainability data to generate automated decisioning recommendations. This platform simplifies regulatory compliance and accelerates data-driven decisions across investments and supply chains.
Funding
Funding not disclosed
Founders
Product
Problem
ESG risk assessment is complex, costly, and unclear due to constantly evolving global regulations, multiple data sources, manual processes, and limited access to real-time, traceable information. Businesses face challenges in tracking and complying with regulations, managing fragmented data, and making informed decisions due to a lack of decision support insights. This results in resource-intensive processes and increased compliance risk.
Solution
Greenfi provides an AI-enabled ESG due diligence software platform that automates sustainability performance monitoring and risk identification. The platform aggregates and analyzes unstructured data from various sources, including ESG reports, disclosures, carbon emissions data, news, regulatory information, and geospatial data, to generate real-time insights and recommendations. By using explainable AI and a no-code AI infrastructure, Greenfi helps financial institutions and corporations identify and quantify risks and opportunities associated with sustainable investments, transition, insurance, and supply chains, enabling faster and more informed ESG decisions.
Target Audience
The primary target audience includes financial institutions and corporations involved in sustainable financing and supply chain management.
Features
- Comprehensive 360-degree unified view of ESG aspects for businesses, customers, portfolios, transactions, investments, and suppliers.
- Traceable, transparent, and configurable risk assessment combining blended expertise with data and AI technology.
- No-code AI infrastructure with proprietary deep learning models for automated decisioning recommendations.
- Automated data aggregation from various sources, including ESG reports, disclosures, certificates, and regulatory information.
- Real-time sustainability performance monitoring and risk identification.
- Integration of physical climate risk and biodiversity data.
- "Sustainability Control Tower" for ingesting siloed unstructured data and generating insights.