Insurers face an increasing workload due to the rising number of crop damage claims driven by climate change. Crop insurance for extreme events can play an important role in protecting agricultural production in order to insure future yield and business as well.
Many in the sector are trying new precision agriculture tools to make rapid, accurate, objective crop damage quantification to meet these new challenges.
Challenges for Crop Insurance Firms
Traditionally, insurers send crop insurance adjusters to the farm to assess the damage. Often this involves traveling to scattered and remote areas to reach their clients. Once at the farm, the crop insurance adjusters must also spend considerable time in manual field scouting for damage quantification, making the process expensive for the crop insurer.
Moreover, the damage measurements must be accurate and efficient so that neither the grower nor the crop insurer suffers losses. Currently, providing proof for the estimated damage quantification can be challenging.
Reliance on new technologies brings many benefits such as:
- Increased client retention & better risk management
- Standardized and accurate damage assessment
- Optimizing the time spent on the field
- Added value to the products and services
- Improved data access and traceability
Available Crop Insurances
In one study, 85% of respondents said getting protection from crop damage due to natural disasters such as drought, hail, floods, wind, frosts, and wildlife was the top reason for insuring their crops.
Depending on the market and legislation, growers can choose from different Indemnity based insurance schemes that cover a single named peril like hail damage or wind damage, or like in the US Multi-Peril Crop Insurance (MPCI) that covers natural disasters, wildlife, and pests. In these schemes, insurers make claim payments based on actual losses assessment at the farm.
Remote Sensing and AI for Crop Damage Quantification
Therefore, crop insurers increasingly rely on innovative technologies and tools instead of traditional workflows for crop damage quantification. Cutting-edge Ai technologies such as Agremo can solve the traditional issues that insurers face and provide additional benefits.
Claim Managers can acquire aerial imagery of crop damages through drones and cover large areas and several fields within a day compared to manual scouting.
“In recent years, the use of drones has strongly increased because of easier access, flexible data-acquisition possibilities, and reduced costs. Drones offer continuous coverage, collect data at centimeter resolution, require little training to operate, and can be deployed at short notice,”
according to a team of European scientists Rutten, Casaer, Vogels, Addink, Vanden, and Herwig.
Online software Agremo analyzes drone images using AI, machine learning, and computer vision and that enables crop insurance companies to:
- Gain insight into crop performance & yield to understand the financial stability of the client
- Review, analyze and evaluate client’s needs
- Audit large data sets
These aerial image analyses identify and calculate the area of damage accurately. Claim Managers or Crop Insurance Adjusters get reports with the analyzed map identifying damaged areas, the extent of damage, the crops affected, and supporting data. These reports provide an objective and unbiased basis for settling claims and the required proof to improve transparency.
“We were able to fly the drones and take pictures to document the damage,” says Shon Grimm, the area claims manager for Rural Community Insurance Services (RCIS). “We could even attach the images right to the claim. Sometimes the damage was even more than the farmer thought .”
Agremo has several products designed for insurance auditing.
- Crop Damage Detection includes three analyses to detect and quantify damage to annual crops. Hail Damage analysis can assist adjusters in settling claims over croplands due to hail. It is possible to identify the extent and percentage of broken plants by Green Snap Detection and lodged plants by Lodging Detection, due to storm and wind, for accurate crop loss assessment.
- Crop State Audit is suitable for agave, pine trees, orchards, bananas, and palm oil trees. Plant number analyses give the exact number of plants in the fields and provide an early yield estimate. This objective information allows the client to pay the insurance premium exactly for the accounted plants in the field, orchard, grove, nursery, or plantation.
Advantages of Remote sensing for Crop Insurance
Using remote sensing and analytics for crop damage claim validation can help both insurers and growers. Crop insurers can process more crop damage claims than before and more accurately. As a result, they can quickly offer fair and undisputable compensation to growers, who use insurance as a risk management tool to improve investment and income.