Multi-Party Computing

Poverty is a challenging problem in many municipalities. Heerlen often ranks high on poverty lists. There is a strong motivation to detect poverty early, or even prevent it. This is relevant for the municipality, but also a broader societal challenge.

Generally the approach to tackle poverty is after-the-fact: it starts when someone is already in poverty. There is too little insights into the influence of other factors on poverty and payment problems, such as the use of utilities, health costs, income and demographic factors. The expectation is that data from multiple parties, including CZ, CBS and the municipality may be able to help getting better insight into these relations, and predict poverty at an earlier stage. However, often such data cannot be readily shared, due to privacy and confidentiality of this data. The goal of this use case is to develop an dashboard, using Multi-Party Computation to enable gaining relevant insights into the different factors influencing poverty without revealing or sharing data at the individual level, preserving privacy of individuals.

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