FAQs
1. What are your data sources? How do you source data? How do you ensure data quality?
Part of our IP includes our own proprietary ESG data platform across a wide range of relevant ESG data factors. Examples include regulations, physical climate risk, advisory & recommendations library, bio diversity, ethical labour & human rights, emissions, adverse incidents etc. We constantly build our data sources from public sources and at times we also work with our data partners. Our customers have the ability to access our data and risk
models into their own private instances to combine with their internal data. Our preconfigured, plug and play data lake & data mesh eliminates manual data engineering process and automates data aggregation complemented with unified dashboards. The benefits we bring is - our customers don't have to search for data or buy from fragmented sources, instead we automate and bring them the most complete, relevant and accurate data for them with consistent data refresh.
2. How do you get visibility to the lower segment of the supply chain beyond Tier 1-2?
We have developed unique methodologies as part of our IP which is constantly improvised. A combination of various data sources including trade data, geo spatial technologies, entity tracking techniques, public data monitoring etc combined with our proprietary AI models
help our customers with deeper visibility and traceability of ESG performance in their value chain.
3. What type and size of companies do you track? How big is your coverage?
Presently we are focused on SMEs, Midcaps and Enterprises from high intensity industries such as Food & Agri, Metals & Mining, Oil & Gas, Fashion & Apparel, Real Estate, Retail, Automotive, Electronics, Healthcare-Life Sciences Pharma, Transportation Logistics- Shipping. Our coverage is global with extensive focus on Asia.
4. How do your risk models work? What are the ESG risk factors?
We are a team of ESG experts, data scientists, modelers, and software developers building the
Data Commons, a federated library of libraries of corporate and ESG factor data, plus ESG
analytics tools to derive the actionable decision metrics crucial for asset allocation, portfolio
construction, sustainable financing, incident analysis, exposure analysis, risk & compliance
analysis, corporate engagement, supplier engagement, strategic planning and transition
investments, and financial sector supervision. ESG data is an important enabler, but just that - an enabler. We never forget that we’re not only solving a data engineering problem for our customers, but also workflow, process,
information exchange and decisioning problems in their business. As far as we and our customers are concerned, data is a utility, and the value is in the deep software layer above it. Of course, we make money from data services as a side-effect of the usage of our platform, which is great, but, the value perceived by customers is primarily in the ESG workflows. Our
AI models map appropriate data elements with relevant external assurance frameworks & internal policies > at customer level first and transaction level real-time with risk indicators and decision support recommendations.
5. How do you track ESG regulations ?
ESG regulations are constantly changing. The RM's / Risk / Legal managers currently are
doing manual google search to find out ESG regulations for each transaction approvals /
supplier selections. We consolidate all ESG regulations into a structured data model. We consistently update and
maintain it up-to-date by tracking constant regulatory changes. Our customers can filter/
slice applicable regulatory info by country, region, industry and map it with customer / supplier entities and internal policies - aggregate & asset level. The system will flag compliance risks - at supplier / transaction / entity level and offers Recommended actions.
6. Who are your competitors? How are you different from others such as MSCI, Maplecroft, Ecovadis, RepRisk, Event Stream ?
We are developing accessible codeless AI technology to help banks and brands automate all
aspects of their sustainability and augment their decision-making in a world of infinitely complex ESG data. Our codeless AI infrastructure currently comprises 120+ proprietary AI models that provide stakeholders with robust plug-and-play AI products without having to write a single line of code. I have attached a diagram of our AI flow. We don't compete with them. We complement most of the ESG solutions. We offer a best in class solution across every product area. We fundamentally reject the rationalization that
siloed products exist because they are “best of breed” and platforms can’t truly solve the whole problem. We’re committed to delivering the breadth and depth of the solution that
allows companies to manage 100% of their ESG risk and decisioning insights in one platform without any compromises when they move from point solutions. We’ve been able to do that
rapidly because when you approach ESG management in a holistic way, it allows you to reuse a lot of the common platform elements (E.g. pre-approval workflows, blended intelligence and the infrastructure to sync data). An integrated platform also allows us to
innovate in completely new ways - like assigning vendor specific ESG insights to purchase
orders, and low carbon trade transactions in a dynamic way based on ESG data and incidents across a number of different counterparties.
7. Who are your customers? What is your current traction? What is your pricing model?
We work with global FI’s and corporates. We have a flexible engagement model. Our product this customisable as per our customer needs. We propose to do a workshop with stakeholders to understand pain points an critical needs. Based on that we can co-pilot a module or do a
PoC to begin with. Depending on the use case, our platform is licenced based on number of
users or number of transactions or number of entities / suppliers in a SaaS subscription
model. A typical co-pilot engagement could start from 0 to 50k and or a software licencing could range from $30k to $200k.
8. How old is your start-up? How long have you been working together on this? How big is your team? What stage is your start-up?
Currently we are a fast growing team of 8 in our leadership team and 6 tech engineers based in 3 cities. We have an international team with complementary expertise in Sustainability, Tech, FI's, Corporates & Start-ups. We have spent nearly 2 years of R&D on our ESG AI tech
dev, use case validation and UX development. Our team has come together to formally introduce GreenFi to early adopters in early 2023. We have raised seed funding and are on our path to series A.