How Is Technology An Enabler Of Financial Inclusion?

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Financial inclusion means that individuals and businesses have access to useful and affordable financial products and services that meet their needs – transactions, payments, savings, credit and insurance – delivered in a responsible and sustainable way.

Source: The World Bank

Close to half of the world’s farmers remain unbanked and numerous agribusinesses are underserved by financial institutions due to the volatile nature of the agriculture sector. Being climate-sensitive, this sector’s outputs depend entirely on varying factors such as temperature and humidity, and also the arrival of monsoons at the right time. Climate change and the consequent weather extremities have severely impacted agricultural productivity over the last few decades, resulting in significantly low crop yields that are also poor in quality.

Lending institutions in many countries such as Jamaica and the United States have been cautious about funding agriculture, citing reasons that include the above-mentioned poor productivity, lack of collateral from farmers, and, in some cases, political situations such as the ongoing US-China trade war. In addition, it is crucial for banks to conduct intensive risk assessments before granting financial aid, which, being a labor- and time-intensive process, further discourages these lending institutions from extending their services to low-yield portfolios. In other words, what these institutions lack is farm-level intelligence that would enable smoother and more efficient operations.

How Is Technology An Enabler Of Financial Inclusivity?

The recent advancements in technology offer a myriad of opportunities for better and efficient financial inclusivity in both developed and developing nations around the globe. Efforts by numerous entities, particularly by agripreneurs, have paved the way for innovative agribusiness software and solutions that help lending institutions assess the creditworthiness of a farmer or an agribusiness and mitigate risks involved in the process.

Organizations such as Cropin are propelling agri-tech innovations to drive digitization in the agribusinesses the world over. Cropin leverages alternative agri-data, such as those derived from satellite monitoring, artificial intelligence, and big data analytics, to make business operations easier for financial institutions. Cropin’s SmartRisk is a unique agri-AI/ML solution that combines multiple sources of data including the platform’s global agri-ground intelligence, weather, and satellite imagery.

The platform establishes the performance of every pixel at a regional level (farm/postcode/state/country) — both historical and present — to deliver regional and plot-level insights at a fraction of the traditional cost and effort. The platform allows users to identify crops, detect crop health, forecast yield, and obtain farmer-level plot and crop performance reports, helping key stakeholders in the BFSI sector hedge risks and make informed business decisions.

 

Lending institutions can thus assess the performance of a farm plot based on historical, current, and predictive data with respect to the crops that were and are being cultivated, the health of the current crop, and the yield forecast for that season. Cropin’s platform also allows the digitization of ground-level intelligence by facilitating the registration of farm and farmer details, thereby reducing paperwork and hours of human labor. The digitized data, along with easy-to-integrate APIs, also ensures hassle-free analysis and reporting as and when required.

Cropin’s proprietary algorithms enable not only accurate crop detection but also crop growth and crop stage analysis, which aids financial institutions in identifying the time of harvest and thus enables timely recovery of the loan. Furthermore, the institutions can leverage this intelligence to identify regions under cultivation to expand their agri-lending services to new regions.

Potential Benefits of Using a Smart Agri-Tech Platform for the BFSI sector

  • Increase loan portfolios by up to 25%
  • Arrive at data-driven decisions that result in up to a 30% reduction in NPA
  • Improve yield by mitigating risks at the right time
  • Cut down significantly on manual labor costs such as field scouting and obtain accurate results in 50x less time

Technology, with the above benefits, improves financial inclusion by ensuring that more smallholder and marginalized farmers have access to financial aid, despite not being able to provide the institution with collaterals or other forms of assurance.

The service providers are also able to mitigate risks very early on, by analyzing the historical performance of the farm plot in the last three years and assessing the possibility of a good harvest at the end of the current season. The credit could also go a long way in improving the harvest for the farmer, by providing him with the resources to invest in better quality seeds or upgrade his farm machinery. This, in turn, brings home better returns for the farmer and ensures faster loan repayment. In the long term, this improves the farming community’s livelihood and, as an extension, the productivity of the agri-sector.

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Cropin Apps

Applications for
digitization

Cropin Apps is an integrated portfolio of highly customizable apps and solutions that capture and digitise agri-data from the farm to the warehouse to the fork. These applications are designed to scale digital transformation across agriculture and allied industries including forestry, commodity, banking and insurance.

DataHub

ML-ready data pipelines for enhanced analytics

Cropin Data Hub is designed to deliver the power of unified data by enabling interfacing with all agri-data sources from on-the-field farm management apps, IoT devices, mechanization data from farming resources, drones in agriculture, remote sensing satellite information, weather data, and many more.                                                      

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Access to field-tested machine learning models

Cropin Intelligence enables access to over 22 of Cropin’s contextual deep-learning AI models to help agri-businesses with insights and predictive intelligence. Built using the world's largest crop knowledge graph, these models have been field-tested and deployed worldwide while being fine-tuned to work with a range of specific crop varieties, conditions, and locations.