Dvara E-Registry provides current and historical data about growth stage, health, yield and cultivation potential of landholding of farmers. This sharpens the lender's understanding of the farmer's borrowing capacity.
Dvara E-Registry has developed ML models for identifying land plots and georeferencing them. Using a proprietary android mobile application, we capture the georeferences of the land plots. The mobile application uses various sensors that are available onboard most android phones, such as the accelerometer, the compass and the GPS sensor, to capture the georeference points for a land parcel. The data captured by the phone, after reaching our servers over the cloud, is fed to a machine learning algorithm that then georeferences the land parcel. This also facilitates accurate measurements of the area of the land parcel.
Dvara E–Registry developed a platform called 'Doordrishti' (translated as far-sighted), which provides index-based land and crop analytics by leveraging the power of ML and AI on remote sensing data, weather data, GIS data and crop science. The analytics will ensure the provision of real-time tech-enabled advisory and access to financial products like credit and insurance for farmers.
These analytics are provided in the form of an index to ensure statistical rigour and operational efficiency in decision-making for lenders regarding sanction, review and renewal of agricultural loans. The indexing will be customised as per the requirement of lenders and credit providers across the following categories-
These are all valuable parameters of assessment during credit underwriting as well as for keeping track of agricultural loans. The analytics provided by us help monitor a credit provider's crop loan portfolio.
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