Social action innovations Bank

Big Data tool to predict the risk of chronic social exclusion
Universidad Politécnica de Madrid

Algorithm developed using Big Data and machine learning techniques, which foresees the risk that public aid beneficiaries may suffer chronic social exclusion. The algorithm was created based on anonymized analysis of more than 16,000 cases and 60 predictive factors. Through machine learning, ten main risk factors have been determined, and an on-line application, accessible to Social Services professionals from any device, computer, tablet or mobile phone, has been developed. It allows these professionals to accurately know the risk of social exclusion of a person, to facilitate them taking decide professional actions to take.

In addition, in the framework of the PACT project, a software for the active management of cases has also been implemented, based on the analysis of personal risks. This analysis allows to better identify the training needs of each person to facilitate their social and labor market integration.

Foto: Mark Bende, Unsplash

Type of activity:

Instrumental improvement

Location:

Castilla and Leon Autonomous Community

Partners / Funders:

Elisava

Genesis:

The project is part of the PACT Project of the Junta de Castilla y León, an initiative aimed at testing a new model for the care of people at risk of social exclusion based on two strategies, 1) the alliance between public and private entities to organize the services in an innovative way that integrates information, resources, answers, and learning; and 2) the proactive and preventive social investment able to detect, situations and profiles of people and families that require comprehensive care before the aggravation or chronicity of exclusion occurs.

Implementation level:

The project has been integrated into the 2016-2020 autonomous community integration plan to promote employability and access to the labor market of the most vulnerable people.

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