The platform update includes an expanded universe of 46,000 public companies for 2022 and tweaks in modelling that impact Scope 1, 2, and 3 estimates. Use of historical data is improved for model stability. Changes are less pronounced for the ASX300 portfolio.

Before this update, customers would have coverage gaps as a result of ISINs not finding their corresponding companies. These changes improve both the coverage and quality of carbon calculations within our customers' portfolios.

Assets Under Management (AUM) amount is now directly associated with each fund. This major update alleviates the unnecessary hassle of switching between funds and updating the AUM to get accurate financed emissions data.

As a follow-up from recent updates to the temperature alignment methodology, we have made some minor improvements to the Potential Carbon Liability modelling in the Emmi methodology.

As part of resolving a data incident involving data ingestion, we have made a number of notable improvements to the temperature alignment algorithm to help provide more accurate results.

As part of ongoing work to simplify the Emmi app, we have removed a calcualtion option around financed emissions, and opted for the EVIC approach as our default.

We have published a number of changes to better align Emmi's Carbon Intelligence app with our broader Carbon Diagnostics product. This update is largely terminology, content location and structure changes.

We have released a significant upgrade in our methods to predict carbon emissions for the global equities universe using machine learning.

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.