INE Uses AI to Detect Risks, Enhance Judicial Candidate Oversight

The National Electoral Institute (INE) will implement AI to detect financial inconsistencies and possible links to organized crime in candidates for judicial office, strengthening oversight mechanisms.

"This is a relatively simple program, practically one of those that can be acquired free of charge, which will use data from social networks, media, and open sources to search for information regarding candidates and find out what has been said about them," says David Ramírez, Head of the Auditing Unit, INE.

INE seeks to reinforce the processes of control and verification of the background of aspiring judges, magistrates, and ministers. The measure responds to the need to increase transparency in selection processes and reduce the risks of infiltration of illicit interests in the Mexican judicial system. Data analysis technologies are increasingly being used in electoral and oversight processes internationally, reports Excelsior.

The Audit Commission, chaired by Carla Humphrey, Electoral Advisor, INE, will approve in the coming days the use of the AI-based risk measurement model. This tool will allow for the integration of information from different sources and the detection of patterns, potentially alerting about inconsistencies or possible risks related to candidates.

The risk model will use information from open sources, social networks, and media, which will be crossed with official databases such as bank reports and tax returns before the Tax Administration Service (SAT). In cases where there are allegations of corruption, collusion with criminal groups, or financial non-compliance, specific databases will be created for detailed analysis.

The data will be cross-checked with income reports that applicants submitted when registering with the INE, as well as with data from the Executive Ministry of the National Public Security System. The indicators will be weighted within a risk model that will evaluate both the regional context and the type of position to which the candidates aspire.

INE has previously incorporated AI-based technologies for the operation of electoral processes. In 2024, it applied text recognition tools to streamline the data capture of the Preliminary Electoral Results Program (PREP) during the presidential elections. According to Jorge Torres Antuñano, General Coordinator of the Technical Unit of Computer Services, INE, this system allowed the automatic capture of information from the tallying and counting of the ballot boxes.

The system also contemplates contingency measures to guarantee data integrity, such as sending unreadable tally sheets to verification centers where they can be reviewed by up to three capturists or verifiers, and if necessary, classified as unreadable.