Revolutionizing Agri-Insurance Through a Data-Driven Approach

Synopsis: 

The agri-insurance industry, while promising, faces numerous challenges ranging from unpredictable weather patterns, pests and diseases to the complexities of claim validation. Insurers need innovative solutions to address these. This blog delves into the critical challenges portfolio managers, underwriters, and claims adjusters encounter. It explores how technology, particularly Cropin's solutions, can address these challenges by providing accurate risk assessments, real-time monitoring, and efficient claim processing. By leveraging data-driven insights and advanced analytics, Cropin empowers insurers to make informed decisions, mitigate risks, and improve overall performance.

According to Allied Market Research, the global agri-insurance market valued at $38.5 billion in 2022 is poised for significant growth of 5.8% CAGR to touch $67.4 billion by 2032. Although this sounds very promising, as an agri-insurance professional, you're well-versed in the unique challenges of this sector. From creating and managing portfolios amidst shocks from unpredictable weather patterns to the constant threat of fraudulent claims, the industry demands innovative solutions to ensure profitability and sustainability. Cropin's technology offers an innovative solution to address these challenges. By leveraging remote sensing, cutting-edge data analytics, artificial intelligence (AI), and more, Cropin empowers insurers to make informed decisions, reduce risks, streamline operations, and fast-track settlements.

Navigating the Agri-Insurance Landscape

The agricultural sector is inherently risky, with farmers facing unpredictable weather, pests, and diseases that can significantly impact their harvests. This, coupled with the intermittent nature of agricultural income, necessitates operating lines of credit throughout the year. Agri-insurance is a popular risk management option for farmers worldwide, as it offers financial protection against crop losses and is vital for farmers to secure and access essential credit.

The insurance market is a dynamic landscape, constantly shifting between periods of high and low premiums. Understanding this cyclical pattern is essential for portfolio managers to make informed decisions and mitigate risks.

Successfully navigating the insurance cycle requires a deep understanding of market trends and risk exposures. By anticipating fluctuations, portfolio managers can make strategic decisions about asset allocation, risk mitigation, and pricing policies.  Failure to adapt to the changing market can lead to suboptimal portfolio performance and increased financial risk. Poorly designed insurance programs can erode trust among farmers and the public. Building a strong foundation of confidence among all stakeholders is crucial for long-term success.

Traditional insurance practices often fall short of meeting the demands of modern agri-insurance. That's why, globally, agri-insurance leaders are leveraging technology as their ally, transforming all industry verticals from portfolio management to claim validation.

Below is a quick look at the top challenges leaders in portfolio management and claim validation functions like you face

Biggest Challenges in Agri-Insurance

Premium Estimation and Portfolio Management:

• Uncertainty in Climate Projections: Rising temperatures, changing rainfall patterns, and frequent extreme weather events disrupt agricultural productivity. Climate change is impacting crop yields, disease patterns, pests and weed distributions, land suitability, and yield quality, making accurate risk forecasting difficult and impacting premium pricing, risk assessment, and claims validation.
• Data Limitations: The sheer volume of agricultural data can be overwhelming. A study by the World Bank Group estimates that about 4.1 million data points per farm per day will be produced by 2050. However, insurers often struggle to access and utilize both historical and real-time data and the insights it can unlock, compromising accurate portfolio management and premium estimation. 

Assessing Future Regional Risks:

• Uncertainty in Regional Crop Viability: Climate change impacts established food production zones, leading to uncertainties in crop suitability and yield prediction, which impact underwriting and long-term risk planning.
• Risk Forecasting: Insurance companies often lack comprehensive data on how climate change and unprecedented weather events will affect different regions. This hinders underwriting, accurate risk forecasting, and the development of effective risk management strategies.

Risk Mitigation and Disease Early Warnings:

• Late detection of diseases: One of the most significant challenges facing agri-insurance providers is the timely detection and mitigation of crop diseases. Late identification of diseases increases risk exposure for both farmers and insurers.
• High cost of mitigation: Without timely data, the cost of mitigating crop diseases can skyrocket. Farmers most often encounter production losses, resulting in higher insurance payouts, straining the financial resources of both farmers and insurers.

In-Season Performance Monitoring and Claim Validation:

• Climate Change: Climate change is a significant challenge facing the agri-insurance industry. With the increasing unpredictability of weather patterns impacting yield, insurance claims are on the rise. Validation of these claims requires real-time monitoring of every insured plot in-season.
• Data Inconsistencies & Delays: Relying solely on manual reports, especially from remote areas, can lead to delays, inaccuracies, and increased susceptibility to fraudulent claims. It impacts in-season performance monitoring, slows validation, increases claim processing time, and delays settlements.
• Self-Reported Data Discrepancies: Farmers may provide inaccurate or exaggerated self-reported data. This must be verified, which is time-consuming and prone to fraud when done manually. Cross-verification without technology-backed tools like satellite imagery is almost impossible.

Cropin's Innovative Data-Driven Solution for Agri-Insurance

Let’s now deep-dive and understand how technological innovations like Cropin solutions can be leveraged to address the most debilitating problem—the information gaps—and address all your crop-related challenges.

Cropin Cloud platform, the most advanced AI platform for agriculture, empowers agri-insurance providers by addressing the critical challenge of data limitations. Our platform provides access to a vast dataset, including weather forecasts, agronomy data, earth observation, soil health information, market trends, our proprietary crop knowledge graph, and other related metrics. Our AI-powered models leverage these comprehensive datasets to accurately predict crop yields, identify risks and offer data-driven insights.

By leveraging Cropin's solutions, you can make informed decisions about risk assessment, portfolio management, and pricing strategies.  We, the Harvest Guardians, empower you to harness data at both granular (down to a five-kilometer-by-five-kilometer grid level) and regional levels! Our integrated, non-invasive Cropin Cloud platform provides cost-effective access to real-time data, advanced analytics, and actionable insights to support informed decision-making.

Key Benefits of Cropin's Solutions for Agri-insurance

Crop Suitability & Crop Acreage Estimation:

At Cropin, we pinpoint ideal regions suitable for specific crop varieties by leveraging our proprietary crop knowledge graph (10,000+ varieties!) built over 14 years.  Cropin's Regional Intelligence leverages a vast dataset, including weather patterns, soil analysis with open-source maps, satellite imagery, dynamic Land Use Land Cover (LULC), and historical crop yields, to arrive at a Cultivation Potential Index (CPI). CPI goes beyond land suitability - it reveals spatial productivity, considering factors like sunshine, soil, water, and even farmer demographics. We also map water sources, soil types (using open-source maps), and potential risks. Crop Acreage Estimation provides insights into crops grown in a region in historical and ongoing season. Assessing risk exposure based on crop suitability and revenue potential is crucial. We empower you with intelligence vital for underwriting functions to minimize risk and drive long-term planning.

Crop Identification:

Cropin's crop identification model leverages cutting-edge technology to identify crop varieties accurately. Our advanced algorithms are trained and tested on extensive datasets, ensuring optimal performance. We employ automated pipelines for data processing, quality assurance, and delivery of result, streamlining the entire process. The cornerstone of our crop identification model is our proprietary crop knowledge graph. This comprehensive database provides invaluable insights for accurate and efficient crop identification, essential for underwriting and claim validation.

Enhanced Data Access:

Digitize farm data on the Cropin Cloud platform and gain access to location-specific information on a centralized platform. Adopting a globally scalable Cropin Cloud platform starts with geotagging agricultural plots and digitizing farm and farmer data. Plot area audit detects and maps the plot insured and maintains a digital record of the same. It plugs data loss, a prevalent threat in manual data collection, and reduces the time lag in access to data. We empower you to access a geospatial-ready data multiverse to feed into your risk assessment models.

Real-Time Monitoring:

Are you tired of relying on outdated and sporadic field visits for information? Today’s challenges, like climate change, unpredictable weather patterns, and evolving pest pressures, mandate near-real-time data insights. Cropin Cloud leverages multiple remote sensing satellite data and weather data sources to monitor your insured fields constantly. This real-time data feeds into our trained and tested AI/ML models to offer crucial insights like yield estimation, crop health tracking, and growth stage progression, amongst others, for informed decision-making. The near real-time data enables risk mitigation and swift claims validation for processing.

Accurate Crop Health Assessment:

Cropin Cloud remotely monitors crop health using three important parameters derived from vegetation indices, namely: Canopy Greenness – derived from Normalized Difference Vegetation Index (NDVI); Canopy Nitrogen Uptake - derived from Normalized Difference RedEdge Index (NDRE) and Canopy Water Stress - derived from Land Surface Water Index (LSWI). The raw indices data is fed into our conceptualized AI/ML models and categorized into buckets varying from above normal to high deviation or poor. The insights offered by our deep learning algorithms enable climate-smart agriculture and risk mitigation among growers, and you can adjust insurance premiums accordingly.

Crop Growth Progression & Harvest Window Estimation:

Cropin's Crop Stage Model offers valuable insights into crop development. By leveraging satellite data, weather information, and agricultural expertise, the model accurately predicts the current stage of your crop, its progress from sowing, and the optimal harvest window. The model estimates the deviation in days from the typical harvest window based on the historical normal. This information is crucial for insurers to understand the impact of climate change on crop growth, assess risks, and predict harvest-window.

Water Stress Identification

Canopy Water Stress is derived from Cropin’s AI/ML models using data from the vegetation index. Using advanced analytics, it identifies water stress issues—crucial information for risk management and claim validation. Our models pinpoint regions particularly susceptible to water stress, which you can use to tailor insurance policies. Water stress data can be utilized to validate claims during droughts and floods and assess the extent of crop damage. It also offers farmers guidance on water management practices.

Yield Estimation:

Traditional yield estimation methods, such as Crop Cutting Experiments (CCE), often rely on random sampling and can be prone to inaccuracies. Cropin's innovative approach leverages advanced AI/ML models and non-invasive satellite data to pinpoint farm heterogeneity for zone sampling, providing unparalleled accuracy in capturing sample data. By combining data from zone sampling, weather forecasts, historical insights, proprietary crop knowledge, datasets from crop farming practices, crop science, and real-time field data, Cropin's AI/ML yield intelligence algorithms deliver highly accurate yield estimates. Our models can be hyper-tuned to your specific data on varieties and locations. This "hyper-tuning," along with historical data and the capability of our models to dynamically adapt to evolving growing conditions, provide you with improved yield predictions at different stages of the crop cycle, which is vital information for the insurance sector.

Figure 1: Yield Estimation at a plot-level 45 Days in Advance

Weather Updates and Disease Early Warning System (DEWS):

How many times have late detection of crop diseases increased your exposure to risks?  What if you had insights on the probability of a disease or pest attack days in advance, and you could alert farmers to implement proactive measures?  Cropin’s DEWS indicates the probability of the occurrence of the disease based on historical disease occurrence data, a comprehensive range of environmental factors like rainfall, humidity, temperature, wind speed, and even pollution levels, and Cropin’s Crop Knowledge Graph. By analyzing this extensive data set, DEWS can predict the potential outbreak of over 65 diseases across 20 different crops and their varieties 7-10 days in advance, empowering early detection and timely intervention. It reduces the need for costly mitigation measures and minimizes the financial impact of crop diseases on farmers and insurers.

Farmer Engagement:

With Cropin, you can directly engage with farmers in their local language and share timely alerts on possible pest threats, hyper-local weather conditions, critical agronomic practices, and predictive data-driven intelligence. The alerts and notifications can be disseminated across multiple communication channels—email, SMS, WhatsApp, and Mobile Apps. This is vital to safeguard yield and optimize payouts.

Cropin Sage: Time Travel to the Future:

Cropin Sage empowers you to "Time Travel to the Future" and understand a region's long-term potential.  It's a powerful tool that lets you leverage both analytical and Gen AI to analyze the impact of climate on crop yields. All you need to do is ask the right questions. With Cropin Sage, you can query historical and real-time weather, realistic pest scenarios, or even future yield estimations.

Figure 2: Cropin Sage answering a query on predicted yield

By combining historical and real-time data, Cropin enables more accurate risk assessments, effectively helping underwriters and actuaries price premiums. This ensures fair coverage and reduces the chances of mispricing policies, which is crucial for managing insurance portfolios. The ability to forecast risks based on reliable data empowers insurance companies to make smarter, data-driven decisions about their coverage strategies. Cropin’s geospatial tools and climate models assist insurance companies in assessing long-term risks in different regions. This allows underwriters and risk managers to consider regional factors during decision-making. By providing accurate projections of crop viability under changing environmental conditions, insurers can reduce future liabilities in their portfolios. Cropin Cloud helps connect with farmers, share advisories enabling climate-smart agriculture, and provide early warnings for diseases to mitigate risks. 

Benefits Agri-Insurance Professionals can get out of Cropin Cloud

• Enhanced Risk Assessment: Accurately assess crop suitability, estimate regional risks, and identify potential challenges using our advanced analytics.
• Efficient Claim Processing: Validate claims and reduce errors of manual inspections.
• Accurate Damage Assessment: Assess crop damage and estimate losses more precisely.
• Proactive Risk Management: Offer timely alerts about potential disease with DEWS and take proactive mitigation measures.
• Improved Decision Making: Make informed decisions based on accurate crop identification and real-time data.
• Enhanced Data Access: Gain access to data multiverse, including area audits, remote monitoring, weather patterns, soil analysis, satellite imagery, and historical crop yields to feed into your risk assessment models.
• Improved Accuracy of Yield Estimation: Accurately and non-invasively predict crop yields based on a comprehensive dataset and advanced modeling.
• Farmer Engagement: Communicate directly with farmers to share valuable insights and support.

Conclusion

In conclusion, Cropin's technology offers a transformative solution for agri-insurance providers, empowering them to navigate the complexities of the modern agri-insurance landscape. It empowers you to address challenges across portfolio management, performance monitoring, and claim validation functions of agri-insurance. By leveraging satellite imagery, AI, and Cropin’s proprietary crop knowledge graph, insurers can enhance risk assessment, streamline claim processes, and provide exceptional service to farmers. Cropin's innovative approach goes beyond traditional methods, offering a non-invasive and efficient solution. Unlike physical inspections, Cropin's technology minimizes disruptions to on-field operations while providing accurate and timely data.

Edited by Abishek Keerthi Narayan