Swiss Money Map
The project "Swiss Money Map" provides a spatial analysis of cash access points in Switzerland. We map and monitor automated teller machines (ATM), bank branch locations, and post offices in Switzerland. We combine these data with population characteristics to provide information on how far Swiss residents have to travel to reach the closest cash access point. We further calculate how much time it takes to access cash by car and public transport. As digital transactions become more widespread, understanding the spatial dynamics of cash access is crucial to anticipate risks of financial exclusion and design inclusive solutions. We therefore hope to contribute to a comprehensive understanding of optimal cash circulation.
The Swiss Money Map is a project of the Center for Financial Services Innovation at the University of St.Gallen.
ATMs and Bank Branches in Switzerland over time
Access to ATMs
Distance and travel time to the nearest ATM
Distance and travel time to the nearest ATM by population share
Access to Bank Branches
Distance and travel time to the nearest bank branch
Distance and travel time to the nearest bank branche by population share
Access to Post Branches
Distance and travel time to the nearest post branch
Distance and travel time to the nearest post branch by population share
Travel time
Filters
Distribution of average travel time by region
Travel time distribution by municipality type
Car Travel Distance
Filters
Distribution of average distance by region
Distance distribution by municipality type
Swiss Money Map
The project "Swiss Money Map" provides a spatial analysis of cash access points in Switzerland. Our aim is to provide an analytical tool to monitor cash access points. As digital transactions become more widespread, understanding the spatial dynamics of cash access is crucial to anticipate risks of financial exclusion and design inclusive solutions. We therefore hope to contribute to a comprehensive understanding of optimal cash circulation.
The Swiss Money Map is a project of the Center for Financial Services Innovation at the University of St.Gallen and is led by Dr. Tobias Trütsch.
The project was inspired by similar analyses 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?
We encourage other researchers to join our initiative. This involves collecting and sharing data on cash access points in other countries. This would enable us to harmonise and measure cash accessibility across different countries.
See, for example:
A Cross-Country Comparison of the Spatial Distribution of Cash Access Points in Switzerland and France
Data, Definitions & Calculations
Data Sources
Population
The number of residents in a hectare is based on the BFS dataset STATPOP . At the time of update, the most recent version of STATPOP is used. The dataset provides information on the population residing within a specific hectare. The sum of the hectare values can slightly deviate from the total population in a municipality as a) not all persons of a municipality can always be clearly assigned to a hectare what results in "residual population" and b) for data privacy reasons, there is a minimum displayed value. These statistical properties of the data should not have a strong impact on the overall results.
ATMs
The list of ATMs containing all Swiss ATMs provided by SNB.
Bank Branches
Bank branches contain all bank branches that offer cash service (banknotes/coin deposit/withdrawal) provided by SNB.
Post Branches
Post branches contain all post branches and post agencies that offer cash service (banknotes/coin).
Calculations of Distances/Travel Times
Distances are measured from the center of each hectare to the nearest access points, categorized by type, service, and transport mode.
For locations within a 500-meter radius of an access point, we calculate Euclidean distance based on the assumption that individuals will walk. Beyond this 500-meter threshold, driving travel times and road distances are calculated using the OSRM routing engine. For each hectare and each access point type/service combination, up to 15 geographically nearest candidate access points were identified. OSRM then calculated the actual driving travel time and road distance to each of these 15 candidates. The candidate with the lowest travel time was selected as the nearest access point, and its travel time and road distance are reported. These car-based calculations assume an 8:00 AM departure with free-flowing traffic conditions.
For public transport, travel times were calculated using the opentransportdata.swiss API. Up to 5 geographically nearest candidate access points were evaluated per hectare and access point type/service combination, with the candidate with the lowest travel time selected. These estimates assume an 8:00 AM departure on a typical Monday morning, excluding initial waiting times and assuming no service delays.
Contact
Dr. Tobias Trütsch:
tobias.truetsch@unisg.ch
Data preparation, calculation & dashboard:
Novalytica AG