DESCRIPTION
ClimateByte targets the needs of insurance companies providing agricultural coverage. This sector is familiar with climate data. However, a gap remains between the wealth of available data and the actual use during the day-by-day operations in the industry.
One of the main reasons for this is the lack of high-resolution data (e.g. MARCO D.6), such that the insurance policy is specifically tailored to the single agriculture plot (1 km2 or less).
This is needed to carry out a dedicated risk assessment for the design of the insurance policy, incorporating vulnerability and climatological data at high-spatial resolution. ClimateByte improves the process of pricing and managing insurance products by collecting in a single place a complete set of climate-related information necessary for the risk profiling.
ClimateByte will use big data and ML approaches, such as Decision Trees and Convolutional Neural Networks, to reach the spatial resolution required by the insurance industry.
The main innovations of ClimateByte can be summarized by the following points:
the design and implementation of a proprietary set of cutting-edge AI techniques; The most advanced Big Data Architecture; a new high-resolution dataset, the integration of the three above mentioned innovations will in an existing platform, and the opportunity of testing the solution on the business case of forage together with insurance companies.
ClimateByte will generate a high resolution (downscaled) climate dataset on the region covered by the CINECA MISTRAL dataset.
ClimateByte will be the only SaaS in the market that automatically assesses climate risk over different time horizons with a resolution suitable for agriculture risk analysis.
ClimateByte has identified 4 Key Exploitable Results: 2 technical and 2 business related.
1) Downscaling technique for climate data up to 100m of horizontal resolution.
2) Integration of the ClimateByte module into an existing platform.
3) 3)Testing the solution in Italy with insurance companies.
4) Definition of a Business model for exploiting ClimateByte
1) Downscaling technique for climate data up to 100m of horizontal resolution.
2) Integration of the ClimateByte module into AMIGOclimate.
