ID Ward blockchain based universal ID for privacy preserving personalisation
In an overcrowded digital space, personal data is key to match individual consumers with the information, products and services they want. However, the data market suffers from extreme consolidation and concentration. On one side,...
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PID2020-113995GB-I00
DESAFIOS ACTUALES DEL REGISTRO DE LA PROPIEDAD: BLOCKCHAIN Y...
42K€
Cerrado
Información proyecto ID Ward
Duración del proyecto: 6 meses
Fecha Inicio: 2019-11-15
Fecha Fin: 2020-05-31
Líder del proyecto
ID WARD LTD
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
71K€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
In an overcrowded digital space, personal data is key to match individual consumers with the information, products and services they want. However, the data market suffers from extreme consolidation and concentration. On one side, a handful of social platforms and search engines monopolise personal data to provide highly personalised products, services and content. On the other side, most content and service providers have so little data that they waste billions in mistargeted marketing, uncompetitive products, and slow innovation cycles. In this scramble, consumers have little or no control over their personal information and struggle to protect their privacy: their data (what they read, watch and buy online, where they live, the places they visit and the things they care about) is often collected, stored and transacted without their knowledge and consent. They experience content overload and look for original and relevant content from trusted sources.
ID Ward solves these problems by making personal data an asset owned and shared directly by the consumer, who can use it to receive personalised content on publishers’ apps and websites. ID Ward works as a universal profile that aggregates data from a network of websites. Its entry point is a simple login that is used to identify the consumer and tracks activities across a network of apps and websites. The data generated by the consumer is made private using end-to-end encryption (E2EE) and used to train AI for personalisation. This reduces content overload and eliminates the need to create multiple profiles and repeatedly accept cookies, while a simple interface gives the consumer control over who can use their data for personalisation. For the companies, privacy-preserving personalisation increases traffic, improves marketing and drives ad revenue. Three large European media companies have agreed to pilot the technology and pay for the development of a prototype.