A European Network helping companies in distress
Each year more than 200.000 EU businesses are facing insolvency, and 1,7 million jobs are lost in the EU due to insolvency. Moreover, the risk of bankruptcy is what Europeans fear most about setting up a new business: 43% of Europeans would not start a business if it might fail compared to just 19% in the United States.
Early Warning Europe establishes Early Warning mechanisms in four EU Member States: Poland, Spain, Italy and Greece, providing support to 3500 companies in distress in 2017-2019. We also support the establishment of Early Warning mechanisms in five additional EU Member States in 2017-2019 – the Second Wave countries. The ultimate goal of the project is to establish Early Warning mechanisms in all EU Member States.
Simultaneously, we are establishing a European Network of experts, authorities, associations and chambers of commerce for improving framework conditions for SMEs and entrepreneurs across Europe. This work will be further strengthened by the development of an innovative, data-driven method to identifying companies in distress. The ambition is to present a Next Generation monitoring and early warning method based on machine learning and big data to identify companies that are in risk of a bankruptcy.
Team UVisit website
Unione Industriale di TorinoVisit website
new EW mechanisms
Based on European Best Practice
Early Warning Europe builds new best practice and draws on existing experience from Early Warning Denmark, TEAM U in Germany and Dyzo in Belgium showing that free and impartial guidance for companies in distress has a positive impact - not only on the survival chances and financial performance of the companies, but also on society. The implementation of Early Warning mechanisms across Europe uses and develops European best practice, and will help save jobs, promote growth and improve public finances.
On this webpage we continuously share the latest news for the Early Warning Europe project.
In two weeks the upcoming expert network meeting will be held.
The tool for identification of companies in distress based on big data is undergoing its final test before we roll it out