Svalna is creating a more conscious society – one user at a time

Svalna launched with one goal: to help consumers slash their carbon footprint. Using financial data, the app helps users understand the environmental impact of their day-to-day purchases – and make simple changes that make a big difference to the planet.

Svalna footprint calculator

The environmental impact of our consumption habits is a global concern, and many of us are trying to find ways to reduce it bit by bit. Using Tink’s aggregation and data enrichment tech, Svalna is helping Swedish users become more aware of the sustainability of their purchasing decisions (or lack of) – and help them make better ones.

Going green

With the Svalna app or online service, users can connect to their bank account in seconds. This aggregates their transaction data, which is then categorised. The transaction data can show everything from shopping to travel, and the type of energy that’s consumed at home. 

Svalna’s custom scoring model then gets to work, helping consumers calculate how green their lifestyle is.

Once the results are in, Svalna encourages its users to set goals and gives them personal suggestions on how to reach them. They can also create groups, so users can work together to have a bigger positive environmental impact.

Build vs. buy

Before partnering with Tink, Svalna had built connections to Sweden’s four biggest banks on its own. But it took too much time and focus to maintain. Their users wanted to connect to more banks. So using Tink’s API, their users can now connect to more than 2,500 banks across Europe.

This means the startup is fast expanding its reach beyond Sweden – developing the tools so that it works well in other countries. The algorithm developed for Sweden can’t make the same assumptions about people’s behaviour in one society versus another. So there’s exciting work to be done.

Svalna’s CEO David Andersson says that ‘by getting a complete overview of a person’s transaction history from any bank, we don’t need to worry about how to get accurate data anymore. Instead, we can spend our time focusing on developing our scoring models and our core platform.’

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