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Estimating carbon footprints from large scale financial transaction data.

Anna Trendl^1,2, Anne Owen³, Lara Vomfell^1,2

¹Behavioural Science, Lloyds Banking Group, 25 Gresham Street, London, EC2V 7HN UK.

Journal of Industrial Ecology

|April 20, 2026

Summary

Estimating carbon footprints using financial transactions is a scalable method. This study validates transaction data against survey data, finding it a credible and objective alternative for carbon profiling.

Keywords:

big data carbon footprint consumption greenhouse gas emissions household expenditure industrial ecology

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Area of Science:

Environmental Science
Economics
Data Science

Background:

Financial transactions are increasingly used to estimate consumption-based carbon emissions.
This method offers a scalable approach for carbon profiling at various policy levels.
Research on the validity of financial transaction data for carbon profiling is limited.

Purpose of the Study:

To describe an approach for estimating carbon footprints from micro-level financial transaction data.
To quantitatively compare emission estimates from transaction data with those from household expenditure surveys.
To qualitatively compare the advantages and disadvantages of transaction data versus alternative sources for carbon profiling.

Main Methods:

Utilized micro-level transaction data from over 100,000 UK retail bank customers.
Compared transaction-based emission estimates with data from a large UK household expenditure survey.
Conducted a qualitative analysis of data availability, quality, and detail for transaction and survey data.

Main Results:

Financial transactions provide a credible alternative to traditional survey-based carbon footprinting.
Transaction data offers objective, micro-level insights into consumption behaviors.
Transaction data enables larger sample sizes and frequent, longitudinal data capture.

Conclusions:

Financial transaction data presents significant advantages for carbon profiling.
Increased accessibility of financial transaction data could enhance emissions measurement and policy interventions.
This approach supports more accurate and detailed carbon footprint analysis.