Research and Innovation | News | 07/03/2023

Financial models, Machine Learning & Circular Economy coming together!

Financial models, Machine Learning & Circular Economy coming together!

Circular economy in practice has, many hurdles to overcome and one of them is the fluctuations in prices of secondary/recycled materials used in the production process. These fluctuations impose a great financial risk for industries which use them and are one of the main prohibiting factors in adopting a circular economy business model. But what if there would be a way to mitigate these risks? Applying data analytics, machine learning and financial modelling we can develop, finetune and use hedging techniques in order to hedge all these risks. 

This is Hypertech’s role in the recently launched DigInTraCE ΗORIZON EUROPE project, aiming to promote circularity and achieve low emissions through the reduction of waste and the use of secondary raw materials. For the complete tracking of materials and products, DigInTraCE will use innovative tracking, tracing and classification techniques to develop a common multi-functional and interoperable Decentralised Traceability platform. The project will also include the development of a dynamically updated Digital Product Passport that will support certification, quality validation, and AI-based decision-making mechanisms for process and life-cycle optimisation, to improve the use of secondary raw materials through “up-cycling, reuse and upgrade” technologies.

In the DigInTraCE project, the financial technology unit of Hypertech SA is responsible for the design, development and testing of a financial services toolkit that will be integrated into the decentralised traceability platform developed within the project. This toolkit will help circular economy participants to create strategies against fluctuations in the prices of secondary/recycled materials they use in the production process with the aim of mitigating the risk from these fluctuations. The toolkit will support advanced price data analysis, visualisation of historical prices as well as trends of secondary material prices and correlations with raw material prices, while providing forecasting and volatility risk/hedging capabilities.

The DigInTraCE consortium includes 22 organisations from 6 EU members, including 7 organisations from Greece, and 1 associated country (8 Academic and Research Technology Organisations, 6 Industrial partners, 3 digital technology providers, 1 Standardisation Organisation, 2 Certification Organisations and 2 pioneering Small and Medium Enterprises).

The project will last 4 years and has a budget of €7.6 million.

The project is funded by the European Union's HORIZON 2020 research and innovation programme 
The project is funded by the European Union's HORIZON 2020 research and innovation programme

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