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Revolutionising Crop Insurance: DAS Unveils Cutting-Edge Data Tool

Enhancing Policy Accuracy with Machine Learning and Geospatial Data

Revolutionising Crop Insurance: DAS Unveils Cutting-Edge Data Tool?w=400

The information on this website is general in nature and does not take into account your objectives, financial situation, or needs. Consider seeking personal advice from a licensed adviser before acting on any information.

Digital Agriculture Services (DAS) has introduced an innovative crop insurance solution in Australia, leveraging machine learning, automapping, and geospatial data to improve policy accuracy.
This tool is designed to assist insurers, underwriters, brokers, and loss adjusters by precisely locating insured paddocks and identifying crop types, yields, and other critical details.

Anthony Willmott, founder and CEO of DAS, emphasised the tool's potential to prevent premium leakage, reduce errors in policy issuance, minimise fraud, and expedite claims processing. He highlighted Australia's suitability as a test case for using geospatial data to enhance the viability of crop insurance without the need for subsidies. DAS plans to scale this solution globally, aiming to benefit both insurers seeking to decrease loss ratios and costs, and producers desiring competitive insurance rates for their land.

Since its launch five years ago, DAS's Rural Intelligence Platform has attracted over 140 customers, including IAG, the Australian Bureau of Statistics, and Cargill. The platform offers comprehensive data on locations, climate, productivity, sustainability, risk, and carbon, providing the intelligence needed to insure, lend, invest, and sell more effectively.

For Australian farmers, this advancement signifies a move towards more accurate and efficient crop insurance policies. By integrating advanced technologies, DAS aims to address longstanding challenges in the industry, offering a win-win solution for both insurers and producers.

Published:Saturday, 22nd Nov 2025
Source: Paige Estritori

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A professional who analyzes the financial costs of risk and uncertainty using mathematics, statistics, and financial theory.