The project will be implemented with the National Anticorruption System of Mexico, which is responsible for the Anticorruption Digital Platform, a data intelligence initiative to manage and make interoperable data related to finance, public contracts and declarations, among other datasets.

Hands-on!: Data for Anticorruption in Public Finances will be implemented in three stages:

Preparation: Public officials will work together with organizers and experts to:

Clearly identify a question that can be solved through machine learning or AI.

Make sure that the data needed for the project is available and in the necessary quality to be directly used in the project.

Identify new datasets, and its sources, which could complement current data to promote better use of AI to fight corruption in Public Finances.

Workshop: that will take the form of short mentoring (a workday) where teams comprised of specialists in data science from academia will advise public officials about how to answer a well-defined question with the available data.

In this stage, specialists from the government, CAF and the IMF will select a project that can easily be escalated and completely implemented as part of the Anticorruption Digital Platform.

The team of the selected project will then work for a period between two weeks and a month, with an international expert, to adjust the proposal and develop a fully functional product to be implemented in the National Anticorruption System.

The final product will be made available as open-source tool for other governments, IMF and CAF to reuse.