Dynamische Risikoprofilierung mit Graphbasiertem Digitalem Doppelnetzwerk und Generativer Künstlicher Intelligenz für Landwirtschaftliche Versicherung

Details

Veröffentlichungs-Nr.

EP4822634

Anmeldetag

13. März 2026

Veröffentlichung

14. Oktober 2026

Rechtsraum

EP

IPC

G06Q40/08

Abstract

The present disclosure leverages a graph-based digital twin network and generative artificial intelligence for solving problems of generalized and static risk assessments to create a dynamic risk profile by combining intrinsic farm risks with propagated risks from neighboring farms. This ensures that risk assessments reflect both local and networked influences. The dynamic risk profile is continuously adapted based on real-time data and interconnected farm relationships. Each farm is modeled as a node in the graph-based digital twin network, where edges represent risk propagation pathways influenced by factors such as pest migration, shared resources, and weather dependencies. Further, a real-time, dynamic premium recalibration is implemented for addressing inefficiencies of static premium model, based on the dynamic risk profile, compliance of farm users with risk mitigation advisory recommendations, and unforeseen risk factors. Furthermore, claims validation is performed by integrating remote sensing, IoT sensor data, and crowd-sourced inputs to resolve inaccuracies and fraud.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete