We are making some major changes to the emissions modelling and emissions data on the Emmi web app.

- Emissions data from new machine learning models will replace existing emissions data

- New emissions nowcast data based on 2022 financials

- Replacing reported emissions with estimated emissions

We have finalised our data sources and methodologies to quantify carbon liabilities for sovereign bonds, making it possible to include Government Bonds as an asset class in Carbon Diagnostics..

Financial data gathering and estimating carbon emissions for infrastructure assets is difficult but is the starting point to build a scalable PCAF aligned approach to quantifying carbon liabilities for infrastructure assets. To overcome customer data gathering hurdles, we have built a range of PCAF-aligned corporate carbon footprinting methods with the lowest amount of information needed.

We have now standardised our methods to quantify property and infrastructure asset and portfolio-level emission reductions under 1.5degC, 2degC and 4degC scenarios, temperature alignment and potential carbon liabilities. This adds to our capacity to deliver on multi-asset footprint and carbon liabilities for financial institutions.

Financial data gathering and estimating carbon emissions for financials property assets is difficult but is the starting point to build a scalable PCAF aligned approach to quantifying carbon liabilities for property assets. To overcome customer data gathering hurdles, we have built a range of PCAF-aligned corporate carbon footprinting methods with the lowest amount of information needed.

Our data pipeline brings in reported financial and carbon data via three different data providers. We have built a tool that checks previous data to new data to help with understanding outliers and where data changes.

Emmi was awarded the Best Research Paper in climate finance at the 5th Annual GRASFI - Global Research Alliance for Sustainable Finance and Investment Conference.

After more than one year collaborating with the University of Otago on machine learning models to better predict corporate carbon emissions, we’ve published a working paper in the United States Association for Energy Economics.

We listened to our customers and they said there’s too many tabs and charts - so we’ve simplified the journey around the core metrics they told us

Two new tabs are available for funds: Snapshots, and Insights.

We've released an easier tool for you to upload or build your funds (previously called portfolios).

You can now upload companies or funds data for different years.