Overview: Spatial Access to Financial Services

Distribution of distance to ATM

Share of households by travel distance to nearest ATM (in m)

Distribution of distance to bank branch

Share of households by travel distance to nearest bank branch (in m)

Distance to nearest ATM & municipality type

Share of households by travel distance to nearest ATM (in m)

Distance to nearest bank branch & municipality type

Share of households by travel distance to nearest bank branch (in m)

Municipality Overview: Spatial Access to Financial Services

Average travel distance on municipality level (in m)


Zoom-In: Municipality Analysis

Average travel distance on hectare level (in m)

Swiss Money Map

The project “Swiss Money Map” has the aim to provide an analytical tool to monitor cash access points. This is particularly relevant in the era of decreasing transactional cash usage and increasing costs of cash withdrawals, respectively. We therefore hope to contribute to a comprehensive understanding of optimal cash circulation.

The project is a collaboration between researchers at the University of St.Gallen and is led by Prof. Dr. Martin Brown and Dr. Tobias Trütsch.

The project was inspired by similar initiatives in other countries such as:
Austria: OeNB A spatial analysis of access to ATMs in Austria
UK: Access to cash coverage in the UK
Australia: How far do Australians need to travel to access cash?

Data, Definitions & Calculations

Data Sources


The number of households in a hectare is based on the BFS dataset STATPOP (2020). The dataset provides information on the number of households residing within a specific hectare. The sum of the hectare values can slightly deviate from the total number of households in a municipality as a) not all households of a municipality can always be clearly assigned to a hectare what results in “residual households” and b) for data privacy reasons, the minimum displayed value for the number of households in hectare is 3. These statistical properties of the data should not have a strong impact on the overall results.


The list of ATMs contains all ATMs listed by SIX, Travelex and Postfinance.
Time of update: 01.09.2021

Bank Branches

Bank branches contain all banks from Google Maps, local.ch and OpenStreetMap. We further pull branches directly from the financial institutions’ websites in case of Credit Suisse, Postfinance, Raiffeisen and UBS. We overlay the different data sources, drop entries that are not regular banks and investigate cases that do only show up in a single source. The analysis focuses on retail banks. We therefore limit the bank branches to the following groups of banks: Cantonal banks, big banks, Raiffeisen banks, regional and savings banks, selected banks of the category “other banking institutions” that serve retail clients. Please download the dataset below for the full overview.
Time of update: 01.09.2021

Calculations of Distances

The distances are calculated from the center of the hectare to the closest ATM or bank branch. For hectares within the radius of 500m around the ATM we display the Euclidean distance assuming that people walk to the ATM. For hectares outside of the 500m radius, we use the TomTom travel API to calculate the car travel distance to the closest ATM or bank branch. For travel distances that are at least twice as long as the Euclidean distance, we obtain the travel distance to the second closest ATM or bank branch. Afterwards, we run several smoothing algorithms to detect outliers that were not correctly processed by TomTom’s routing API. Overall, the methodology allows for a very detailed analysis of the results. We would like to point out that there are still specific cases where the methodology is not fully able to capture the real circumstances and behavior of households.

Download Dataset


Dr. Tobias Trütsch: tobias.truetsch@unisg.ch
Prof. Dr. Martin Brown: martin.brown@unisg.ch

Data preparation & Dashboard: Novalytica AG