With the changing environment, the role of banks is diversifying, and they are increasingly involved in agri-based lending activities. Besides financing traditional activities, banks are engaged in sourcing credit flow to the agriculture sector, exporting and marketing agricultural produce, and channeling loans at subsidized interest rates to farmers.
Key challenges distressing the banking industry
High Cost of Servicing
Low Ticket Size & Higher Risk Involved
Difficult to Find and Verify Information
Estimating the Farmer's Yield / Income
How does PInCER help?
Cropalytics solution makes the process cost-effective & helps the banking sector monitor risk in near real-time. Our solution enables banks to streamline their lending strategies, develop loan products, deploy manpower, and manage crop risk based on data.
Agribusiness lenders and banks can mitigate risks by utilizing region-specific offerings such as weather-based advisory, acreage insights, and yield & harvest predictions. Cropalytics’ pest and disease module provide 15-day warnings about disease and pest infestations.
PInCER Modules Enabling the Banking Industry
Helps lender classify villages based on crop acreage, health, yield forecast, and scores of other parameters
Using the farmer’s geo-location remote images and land records to verify the farming history, ownership and acreage
Farmer Decision Support System
Mobile app that supports farmer enrollment, geolocation, tracking and advisory for crop risk mitigation
Field Decision Support System
A portal for allocation of territories and farmers to extension teams, tracking actual visits and supporting navigation to enrolled farms. A useful tool to manage FPOs
Using remote sensing to track areas and crops of interest, monitoring crop health, making yield estimates and harvest updates
Assess crop risk progressively; using stochastic models at the pre-sowing stage and deterministic models using remote-sensing for standing crops. Estimate share of the portfolio at NPA risk and likely insurance recovery
Key benefits of using PINCER
Satellite and weather data-based advisory
Prioritize your target area
Demand forecasting and effective go to market
Drive farmer engagement
Track crop-specific acreage and yield estimation
Limit field visits for your last-mile team
Mapping maize crop acreage for an agrochemical and agricultural biotechnology corporation
The client wanted to conduct a study to estimate and map the crop acreage of maize across 5 countries in Asia (China, India, Pakistan, Philippines, Thailand & Vietnam). The aim was to have a scalable approach to understand maize growing regions in these countries and estimate crop acreage, which will eventually help the company in planning for its maize-oriented products.
RMSI adopted an integrated approach to use satellite imagery, ground survey, and secondary information to develop an understanding of Maize crop acreage. We conducted a detailed analysis to understand the Maize crop’s sowing window, crop duration, and spatial distribution/spread across the five Asian countries during 2018-19’s multiple cropping seasons.
Gram Panchayat level crop yield estimation using technology for a government entity
The client wanted to conduct a pilot project to compare the potential scope, applicability, and viability of various advanced technology-based yield estimations for three crops – Paddy, Cotton, and Red Gram – grown in different agro-climatological zones of India.
RMSI proposed an approach where robust machine algorithms were clubbed with efficient remote sensing technologies and physical surveys. It captured ground control points (GCPs) critical for capturing location, crop signature, and CCE data, and RMSI generated crop spread maps for specific crops using high spatial resolution satellite imageries.
Assessing crop growth using remote techniques for a non-profit international research institute
The client wanted to conduct a study for crop health monitoring, pre-harvest crop acreage, and yield estimation to find out the potential scope, applicability, and viability of scientific and modern techniques in agricultural assessments. The areas of study were four soybean-growing districts of Maharashtra (i.e., Kolhapur, Latur, Osmanabad, and Washim).
RMSI conducted an experimental study to compare the potential scope, applicability, and viability of four advanced technology-based agricultural assessment techniques for soybean as a test crop in four soybean-growing districts of Maharashtra with different agro-climatological set-ups in Kharif 2016.
Crop yield estimation & supply chain management for an Apex-Export Trade Promotion Active government entity
The client wanted to assess the Basmati crop acreage in northern India to estimate yield and thereby assist in effectively managing the Basmati supply chain in India, mainly for exports.
RMSI adopted an integrated approach to use satellite remote sensing, ground survey, and secondary information to develop an understanding of basmati acreage. It was followed by satellite image processing to estimate the spatial distribution and distinction of different rice varieties from basmati, depending on the various crop growth stages at the time of imagery acquisition.
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