From advanced calculations to settlements, agri-insurance challenges are simplified using technology.

Synopsis:

Agric insurers are tasked with completing states processing quickly, a pressing need. They are constrained by false claims, and they require data-driven insights to determine the best advanced fixing and insurance. This website explores how advanced technologies like remote sensing and data analysis techniques can assist agri-insurers in overcoming these challenges. It deep-dives into how Cropin alternatives provide data-driven insight, support assess and evaluate says, estimate potential costs, and assess risks during screening. This shortens the time and costs involved in processing claims and increases plan management’s overall effectiveness.

Agriculture is fundamentally a product of its dependence on nature, making it essentially prone to risks. Producers frequently experience unpredictable weather patterns, from droughts and floods to sudden rainfall and hailstorms. These issues have only been made worse by climate change, which has increased the frequency and severity of extreme situations. Producers who are receiving close are significantly impacted. Farmers can turn to produce plan for financial security against crop losses as a safety net. However, traditional say negotiation processes have often been plagued by major challenges. These include risk evaluation during the screening process, false claims ranging from basic exaggerations to difficult schemes involving cooperation, delays, inaccuracies, and a lack of clarity in the claims process.

Now, technology offers a tempting alternative to these problems. By leveraging improvements in data analytics, artificial intelligence, and remote perceiving, insurers may improve the performance, reliability, and clarity of the claims process.

The Role of Technology in Agri-insurance

According to a study conducted during the crisis of 2020, the agri-insurance sector has the most popular technologies for insurance and reduction assessment:

The agri-insurance industry is now more dependent than ever on developing and implementing new systems and distant sensing equipment. These developments can simplify processes, lower costs, and improve the overall performance of comprehensive control.

Key Technologies and Their Rewards:

Advanced AI/ML designs for data analytics analyze foliage indices in combination with other datasets to forecast produce growth, assess possible risks, identify and evaluate potential risks, detect early signs of grain damage, and many other things.
Remote Monitoring and Verification: Satellite imagery, drones, and IoT sensors enable real-time monitoring of crop health, soil conditions, and other agricultural parameters, facilitating damage assessment and claim verification.

By leveraging AI-powered algorithms to analyze satellite imagery, drone footage, and sensor data, insurers can automatically assess the extent of crop damage, validate claims, and estimate potential losses. This significantly shortens the time required for manual inspections and settlement of claims. As an example, let’s deep dive into how technology is leveraged in flood assessment.

Leveraging Technology for Flood Assessment in Agri-insurance

The United States Geological Survey ( USGS 2021 ) categorizes flood as the “rising or overflowing of a body of water, particularly onto normally dry land ) into two basic categories:

River flooding ( incessant rains in Kerala during the monsoon season of 2024 )

Additionally, secondary effects of natural disasters like storm surge- cyclones/hurricanes ( Cyclone Nivar ) and tsunamis (tsunami in Japan in 2011 ) also cause flooding.

Risk Management

Insurance’s assessment of risk takes into account floods and other natural disasters. It is in direct proportion to what

Exposure of the asset- farms, buildings
Compared to one in 100 years, the probability of hazard-flood occurrence every one of 10 years is lower.
Vulnerability of assets to damage

In the image, Farm A is farther from the river, has lower elevation and natural protection ( e. g., trees ), and therefore lower vulnerability to flooding. Meanwhile, Farm B, closer to the river, has a higher elevation, lacks natural protection, and hence has a higher vulnerability to flooding. Farmers who are more vulnerable and exposed are typically more vulnerable, and their crop insurance premiums are typically higher to make up for it. Based on the evaluation of crop type, location, cultivation practices, historical data, and more, underwriters determine the level of risk associated with the insured crop and set appropriate premium rates. Underwriting is essential to ensure that insurance premiums accurately reflect the actual risk involved and that the policyholder is able to adequately cover potential losses. In the event of unanticipated damages, farmers can pay a comparatively low premium to receive substantial compensation.

Flood Mapping with Satellites

Satellite imagery, even during cloud cover, is vital in flood assessment. With a spatial resolution of 10 m operating in the C band of the microwave region of the electromagnetic spectrum, microwave data from satellites like Sentinel-1 can travel through clouds to give an accurate picture.

Case Study: 2024 Assam Floods

In a recent study tool ( July 2024 ), free data was used to map the Assam floods. It leveraged pre- and post-flood images to detect changes in surface water. The impact of the floods on the population was assessed using the Global Human Settlement Layer and the MODIS Land Cover to assess the effects on agriculture and urban areas.

Impact Assessment: Remote sensing tools allow insurers to rapidly assess damage and estimate its extent, fast-tracking preliminary assessments of insured assets. Combined with on-ground verification, it helps quantify flood risk and guide resource allocation for insurers and government agencies.

In July 2024, flood damage was estimated for all Assam districts in the area of the river Brahmaputra. As shown in the visualizations:

Estimated flood extent area- 0.83 million hectares
Impacted area -0.26 million hectares of cropland
Impacted population- 2.19 million people

Figure 1: Potentially flooded area

Figure 2: Affected cropland

Disclaimer: This analysis is for technology demonstration purposes only ( data as of July 26, 2024 ). Further investigation is necessary because the Assam flood situation is still ongoing.

Transforming Agri-insurance with Cropin

Cropin’s technology streamlines the agri-insurance process from start to finish. Deep learning AI/ML models, proprietary crop knowledge graphs, and satellite imagery data are combined to create the robust framework. These models provide actionable crop insights because they are trained on vast labeled datasets to improve accuracy.

First, satellite images are captured for the region of interest, and cloud masking and interpolation are applied. This data, comprising multiple vegetation indices like NDVI, NDRE, SAVI, EVI, LSWI, etc., is overlaid with other relevant datasets, such as weather data and proprietary crop knowledge graphs, and analyzed by our contextualized AI/ML models for a comprehensive understanding. After post-processing and auditing, the extracted agri-data is visualized on the intuitive platform as map-based dashboards.

Yield Estimation Model: Overlays weather data, crop-agnostic information, and phenology derivatives from Sentinel-2 and Landsat 8/9, with zone sampling data for improved accuracy of yield predictions.
Crop Acreage: Our dynamic LULC models generate accurate crop acreage using granular insights at a 10×10 meter resolution.
Rigorous Validation: Ensures validated data is provided for the area under cultivation, crop varieties sown, growth progression, health, and potential risks.

Regional intelligence from Cropin can quickly determine the extent of damage, validate claims, and estimate potential losses once a claim is filed, significantly reducing the amount of time needed for manual inspections and claim settlement. With this knowledge, insurers can control fake claims, such as filing claims for non-existent crops, submitting false records, exaggerating crop losses, and staging fake weather disasters.

With Cropin Sage, Unlock Smarter Underwriting

Cropin Sage, powered by Google Gemini, is a cutting-edge platform that offers comprehensive agri-food information and predictive insights. Cropin Sage can respond to your questions about agriculture quickly and accurately using both analytical and generative AI. Simply put, use natural language to ask your questions. Utilizing its potent AI capabilities, Cropin Sage will access the vast array of declared datasets, create dynamic visualizations of the results, and use them to translate them into SQL ( Structured Query Language ) queries. This user-friendly interface allows you to quickly obtain information on historical and real-time weather, potential pest scenarios, and future yield estimations. By harnessing the power of Cropin Sage, insurers can make informed decisions regarding fixing premiums and underwriting risks, benefiting from the platform’s accuracy, efficiency, and comprehensive data coverage.

Enhance Agri-insurance with Cropin Solutions:

Acreage Estimation and Crop Variety Identification: Accurately identifies sown areas using dynamic land use land cover ( LULC ) analysis. uses proprietary crop information to identify crops at the varietal level for over 10,000 different crop varieties.
Crop Health and Growth Progression Monitoring: Our deep-learning models track crop health and growth progression using vegetation indices like NDVI, NDRE, EVI, LSWI, and more.
Yield Estimation: Cropin’s zone sampling and advanced yield estimation models increase the accuracy of crop yield estimates, aiding risk assessment and premium calculation.
Rapid Impact Assessment: Fast-tracks identification of flooded areas and impacted farmers for streamlined claim processing.
Fraud Detection: By providing reliable information on crop types, growth stages, and health, Cropin helps insurers detect fraudulent claims and ensure accuracy. As a single source of truth, Cropin’s data validates claims and maintains integrity.
Near Real-time Monitoring: Insurers can monitor farmlands, assess crop growth and health, and identify and assess the impact of flood, pest, drought, etc, on yield.
Premium and Underwriting: Based on near-real-time data and risk assessments, the Cropin Cloud platform can assist insurers in improving their premium calculations and underwriting procedures.
Cost-Effectiveness: Remote monitoring and agri-intelligence can automate many aspects of the claims process. Insurance companies can lower operating costs and increase the affordability of premiums.

In conclusion, by leveraging the advanced Cropin solution, insurers are empowered to make informed decisions, control fraudulent claims, and improve the overall efficiency of agri-insurance processes. It empowers insurers to better assess risk, tailor policies, streamline claims, and provide superior service to farmers. Cropin’s solutions provide a comprehensive view of improving efficiency and accuracy in the agri-insurance industry, from identifying flood risk zones to evaluating crop health and yield predictions. With Cropin Sage, all you have to do is” Ask the right questions”.

From advanced calculations to settlements, agri-insurance challenges are simplified using technology.