Over the past few years, the presence of AgTechs has increased. As per data from Startup India, the country has nearly 3,116 registered food and agriculture start-ups. This number has increased 25% to 30% annually. Most of these start-ups emerged over the past five years and at least 500 have crossed the Proof of Concept[1] (PoC) stage.
Globally, India ranks second, based on the number of AgTechs, behind only the US. A 2018 PwC report estimated the overall target market for AgTechs in India to be more than USD 350 billion yet the combined revenue of all food and agri start-ups in India is less than 100 million USD, indicating a huge opportunity for AgTechs to disrupt the market.
Investors are also increasingly interested in AgTechs in India. The sector currently has more than 90 active institutional investors and 250 angel investors. This interest has translated into higher investment sizes—the sector has seen investments worth about USD 500 million since 2014, with more than 50% of this amount invested in 2019. AgTech in India received a major boost early last year with Tiger Global investing USD 89.5 million in NinjaCart. Furthermore, the sector has received renewed attention as a result of COVID-19 as AgTechs supply essential products and services. The pandemic has presented an opportunity for growth for many AgTechs and has demonstrated their resilience and relevance.
Our analysis further suggests that seed and early-stage funding comprises nearly 70% of AgTech investment deals whereas the remaining 30% represent investments in series A stock and beyond. With an agrarian economy and the world’s second-most populous country, funding has facilitated AgTech innovations and improved the productivity of farms and farmers.
AgTechs offer diverse solutions across the agri value chain
Innovative AgTechs in India offer solutions to problems permeating the entire agri value chain, both upstream (close to farmers) and downstream (close to consumers). For the purpose of MSC’s study, AgTechs in India were classified into six broad categories, as discussed below, based on the solutions offered. Farmers require financial services for various purposes across each of these six categories:
AgTechs in farm management and data analytics facilitate data collection and decision-making using drones, sensors, Internet of Things (IoT) technology, and data analytics. These AgTechs use this data to build models around price forecasting and the management and monitoring of crops, among other areas.
Agri-input marketplaces provide farmers and merchants a platform where they can purchase agriculture inputs and facilitate last-mile delivery.
Agri–output marketplaces are business models that aggregate demand in the supply chain. They typically source produce from farmers or farmer producer organizations (FPOs) and sell to Kirana stores, supermarkets, and hypermarkets, among others.
Agri financing companies offer applications and platforms that connect farmers digitally. They offer digital payment solutions, lending services, and insurance services. Most FinTechs in India have built interesting models around farmer onboarding and credit scoring using alternate data, such as farmer behavior. Agri-FinTechs have huge potential to meet the unmet credit needs for farmers with their innovative models.
Livestock managementAgTechs digitize supply chains for allied activities such as cattle, poultry, and fisheries to introduce efficiency and reduce costs.
Mechanization or novel farming systems are a category of AgTechs that include 1) companies offering farming-as-a-service, in other words, they rent services and machinery to reduce capital expenditures thereby increasing efficiency and affordability, and 2) companies that offer alternate farming techniques such as aeroponics[2], hydroponics, and aquaponics.
Three key factors limit the growth of AgTechs in India
Despite their immense potential, AgTechs in India are limited by challenges around funding, strategic partnerships, and data. The following graphic looks at these challenges in detail:
AgTechs continue to innovate with the goal of improving farmers’ lives. Yet, the complexity of the agriculture sector makes it difficult for AgTechs to remedy these challenges independently. The answer, in part, lies in collaboration. Some AgTechs have realized this and are actively scouting for ways to collaborate with financial institutions and government bodies. In the third and final blog of this series, we highlight ways AgTechs can successfully work with financial institutions and overcome collaboration challenges, as well as discuss ideas behind the development of innovative solutions to finance the farmers.
[1] Proof of Concepts are used for testing the feasibility of a design idea or concept for application to real-world challenges and problem statements.
[2] Aquaponics is an indoor gardening practice whereby plants are grown and nourished by suspending their roots in the air and spraying them regularly with nutrients and water solution. Hydroponics is the science of growing plants without using soil, while feeding them with mineral nutrients dissolved in water. Aeroponics is the field of agriculture that uses technology for data collection, analytics and automation in farming activities.
AgTechs are the missing link that can facilitate financing for SMFs
Financial institutions in India have historically lacked the expertise or capacity to generate granular farm and farmer-related data needed to offer credit to farmers. However, the digital revolution in India has paved the way for banks and other financial institutions to use technology to target and service customers, reduce costs and reach previously untapped segments such as SMFs.
A typical financial institution’s credit cycle consists of four stages: loan origination, underwriting or credit assessment, servicing and monitoring, and collection. AgTechs have the ability to provide financial institutions with data and technology at various stages during the credit cycle as illustrated below.
Upon loan origination, financial institutions are primarily concerned with client details such as the borrower’s personal information, income details, and credit history—if available. AgTechs like FarmGuide, Jai Kisan, PayAgri, and Skymet support financial institutions in this process by undertaking data collection including historical data on crop type and quality, weather forecasting, and soil quality assessments.
For the underwriting or credit assessment process, financial institutions require details about the agriculture land holdings and crops, as well as information on the movable assets or properties held by the farmer. AgTechs like FarmGuide and Jai Kisan have a unique role to play in developing solutions to digitize land records and gathering farmer-specific data. Moreover, they can also tap into their existing physical networks such as their field staff or other local partners, who deal with farmers, to source further information.
For servicing and monitoring, financial institutions typically require details about sowing and harvesting along with information on historical cropping patterns to generate yield estimates. AgTechs like CropIn, SatSure, AgroStar, and Gramophone generate data on overall yield estimates, forecast demand, monitor crops to predict non-performing assets and use of farmer credit—all by analyzing satellite imagery and agri-input data based on farmers’ online purchase patterns.
Finally, to collect their loans, financial institutions need visibility on crop harvest and prices to estimate the repayment capacity of farmers. AgTechs like NinjaCart, Jumbotail, and Agricx play a significant role in this process by offering forward market linkages and grading and sorting produce for farmers thereby allowing them to sell their produce at the market price and generate a sufficient return. Banks can then use this information on pricing captured by AgTechs to estimate the repayment capacity of farmers.
Despite the potential, several challenges limit meaningful partnerships between AgTechs and financial institutions
Collaboration between AgTechs and financial institutions are at a nascent stage and will require time to scale primarily due to the following hurdles:
Lack of a full stack solution for banks: Most AgTechs offer independent solutions that solve a small part of a larger problem along the agri value chain. Banks, however, want to partner with AgTechs that offer a “full stack of solutions,” thus eliminating the need for them to partner with multiple AgTechs.
Challenges with the non-risk-sharing model of AgTechs: Banks want to work with AgTechs that share the associated risks and resulting liability of agri financing. Since financing farmers, particularly SMFs, entails the provision of data and the assumption of risk, banks hesitate to forge partnerships or conduct pilots with AgTechs that want to be indemnified from assuming liability.
Limited understanding of AgTech solutions: Most banks have a limited understanding of the solutions offered by AgTechs and believe that AgTechs are only confined to generating data points using satellite imagery. Banks are not aware of the value proposition and potential of AgTechs to inform their credit cycle and, hence, often disregard their solutions.
Limited trust of data captured by AgTechs: Traditional financial institutions are dependent on their staff and their local-level understanding for sourcing and verifying information related to farmers and their crops. Since AgTechs collect most data using technology such as satellite imagery, spectrometry, etc., banks are skeptical of the reliability of data that AgTechs generate. Moreover, banks require historical trends and data points over the past four to five years to gain a reliable picture of their borrower; however, nascent AgTechs are not yet capable of providing such historical data points.
Suggestions to improve the AgTech ecosystem
The recommendations below address the myriad challenges AgTechs in India face, as individual players in the agriculture ecosystem and in collaboration with other AgTech players. These recommendations should serve to enhance opportunities for AgTechs to finance the untapped SMF segment:
Build an AgriStack model: AgriStack is envisioned as a public, digital platform that offers access to all farmer-related information at three levels: farm, farmer, and crop(s). AgTechs, banks and other ecosystem players could use the AgriStack platform to generate precise farmer and farm-level data to design products, solutions, and policies/schemes targeted toward the welfare of farmers, particularly SMFs. An enhanced AgriStack, with the fourth element around the market, could also pave the way for AgTechs to develop a full stack of solutions based on the farm, farmer, crop-level data, and market access.
Create digital GPS-tagged land boundaries: Currently, only a few states have digitized their land records. The government, both central and state, should take the lead in creating GPS-tagged boundaries and digital records to help identify the rightful land owner thereby guaranteeing land title. Open APIs[I]could be shared with AgTechs to harvest this government-owned data to create lending solutions for financial institutions and promote access to finance for SMFs. This would also ensure that banks trust the authenticity of the data and solutions provided by AgTechs as the Government of India (GoI) would be the original source of the data.
Create a single-window approach to address AgTech concerns: State governments could set-up a “single window” approach for AgTechs to raise their concerns, receive responses to their questions, and resolve grievances around delayed payments for government projects undertaken by AgTechs. This approach will streamline the communication between AgTechs and government bodies thereby encouraging effective partnerships.
Creation of a separate fund for financing SMFs: Development financial institutions should come together to offer capital to financial institutions lending to SMFs or explore the creation of a separate fund similar to the Rural Infrastructure Development Fund (RIDF)[I]. This would enable financial institutions lending to SMFs to borrow capital at a low cost, which they could ultimately on-lend to SMFs at a lower cost.
India could become a global hub for Agri-FinTech innovations
With the recent spate of investment deals, the AgTech sector has come into the spotlight. It is an opportune time for ecosystem players to capitalize on this renewed attention. With increasing traction, AgTechs will continue to provide viable solutions to farmers by making use of innovative technology. However, creating new collaborative platforms, such as AgriStack, is of utmost importance so there can be seamless sharing of data among multiple stakeholders including governments and financial institutions, as well as a culture of transparency and accountability across the agri value chain. Effective partnerships between financial institutions, the central and state governments, and AgTechs present an opportunity to conduct pilots and Proof of Concepts (PoCs) while addressing the dearth of financing available to SMFs. Such collaborations could also reinforce India’s emergence as a global hub for digital financial service solutions for farmers.
[1] Open APIs are publicly available software that allows developers to communicate with each other and share data freely. They allow universal access to data, thus promoting the creation of innovative solutions.
[2] RIDF was set up by the Government of India to provide loans to state governments and state-owned corporations to finance rural infrastructure projects. The fund is maintained by National Bank for Agriculture and Rural Development (NABARD).
Despite an increase in penetration of agricultural credit, most SMFs continue to remain excluded
While agriculture remains a key economic activity in India, employing close to 55% of the population, most farmers find it challenging to access finance. Farmers rely on both formal, as well as informal, sources[1] to fulfill their needs for activities such as purchasing inputs, machinery, and improving the quality of their land. During the course of MSC’s study, farmers in India were divided into three categories based on the size of their landholdings. These categories included small and marginal farmers owning less than 2 hectares of land, medium farmers owning between 2 and 10 hectares of land, and large farmers owning more than 10 hectares of land.
A significant finding from this study was the disparity in access to formal and informal finance that was prevalent in the three farmer categories. Our analysis indicates that, despite the Government of India’s policy to encourage agricultural lending, only approximately 29% of farmers enjoy access to credit from formal sources. Of the SMFs, who comprise 86.2% of the total farmer population, approximately half were unable to borrow from either formal or informal sources. Of those SMFs that do borrow, 59% or 36 million accessed formal credit while 41% relied on informal credit.
Banks are reluctant to offer credit to SMFs
Agricultural credit disbursed by banks increased by 27% from 2016-17 to 2018-19 as a result of mandated priority sector lending (PSL) policies of the Reserve Bank of India (RBI). In 2018-19, banks disbursed agriculture credit worth USD 168 billion, three-fourths of which came from commercial banks with the remainder disbursed in equal proportion by cooperative banks and regional rural banks. All these banks disbursed nearly 50% of their credit to large farmers and were unable to meet their mandated PSL criteria of disbursing 8% of their credit to SMFs.
In India, the RBI mandates banks that are unable to attain their PSL target to either purchase priority sector loans from other banks or contribute to the Rural Infrastructure Development Fund (RIDF)[2]. As more and more banks struggle to meet their PSL targets, the sale of priority sector lending certificates (PSLCs) has gained traction. PSLCs help banks fulfill their shortfall by trading the certificates from the seller to the buyer bank for a fee. Private and foreign banks, which often lack a presence in rural areas and find it costly to lend to PSL target segments, have emerged as the predominant buyers; while public sector banks, rural regional banks, and small finance banks have emerged as the major sellers of PSLCs. As per RBI data, the trading volume of PSLCs increased by 78% to USD 44 billion in FY 2019, up from USD 26.5 billion the previous year. The sale of PSLCs for SMFs grew 62% to USD 15 billion in FY 2019 as compared to FY 2018.
High cost of service: Banks find it costly to serve SMFs with low ticket-size transactions, and difficult to reach out to them as the farms and farmers are located in remote areas. Banks also perceive an inherent risk of default associated with lending to SMFs.
Limited mechanisms to assess SMFs creditworthiness: Banks have limited access to farmers’ financial information such as cash flows and credit history. Most farmers have either had no or negligible experience banking with formal financial institutions. Further, banks are unable to verify whether the information provided by SMFs, such as income from other sources, is reliable for financing decisions.
Uncertainty in the policy environment: Banks hesitate to serve SMFs due to the farm loan waivers offered by state governments. Since the government assumes the liability of the farmer and repays the bank in the case of default, banks feel that such loan waivers reduce the credit discipline of farmers and create a moral hazard. Loan waivers coupled with banks’ perceptions of high non-performing assets in agricultural lending make financial institutions reluctant to serve SMFs.
Banks would be remiss to disregard the potential opportunity to offer credit to 90 million SMFs, which represent a relatively untapped segment in India. Although the challenges cited above are, in part, driven by costs and the policy environment, many hurdles could be overcome with access to reliable farm-level data. This creates an opportunity for technological interventions in the agriculture sector that could improve banks’ abilities to obtain and verify farmer data resulting in greater access to finance for SMFs. In our next blog, we unpack the AgTech landscape in India and focus on technological innovations across the Agri value chain.
The second blog covers the AgTech landscape in India and highlights three key challenges limiting their growth. The third blog focuses on partnerships between AgTechs and financial institutions and offers recommendations on improving the AgTech ecosystem in India.
About the study
MSC (MicroSave Consulting) and ThinkAg studied the AgTech landscape in India focusing on innovations in financing small and marginal farmers (SMF). The study, conducted in June 2019, looked at technology-led solutions in the AgTech space and examined how financial institutions could adopt such solutions to finance SMFs. We consulted over 50 stakeholders for the study representing AgTechs, financial institutions, investors, donors, input suppliers, agri-corporates, industry experts, and incubator managers. In May 2020, the results of the study were disseminated via a webinar organized by the World Bank.
[1] Farmers rely on both formal, as well as informal sources to fulfill needs and requirements for activities such as purchasing inputs, machinery, and improving the quality of their land, among others.
[2] RIDF was set up by the Government of India to provide loans to state governments and state-owned corporations to finance rural infrastructure projects. The fund is maintained by National Bank for Agriculture and Rural Development (NABARD).
The number of farmers in Africa who have subscribed to agricultural digital services has grown by between 40% and 45% per year in the past three years. According to the African Development Bank (AfDB), an estimated 33 million people in Africa have already registered for digital agricultural services, such as weather updates and market linkages. These farmers constitute nearly 13% of all the smallholders and pastoralists in Sub-Saharan Africa. Today, they find value from a range of digital agricultural services available to them.
Through digital services and platforms, the transformation of the agricultural sector and its economics is increasingly becoming feasible. This is due to innovations in affordable technologies and mobile-based solutions, which continue to expand. However, most digital agricultural platforms provide only a few services that are core to the business models of the providers. Most platforms have a “walled-garden” approach and do not provide complementing services from other synergistic platforms. This offers a huge untapped opportunity to create unified and interoperable platforms that can provide a wider range of services needed by smallholders.
Digital agricultural services can be valuable in multiple ways to the cultivating smallholders and a range of other stakeholders in the agriculture sector. For smallholders, digital agricultural services can:
Provide easy, timely, relatively accurate, and low-cost access to information or advisory services. This access helps smallholders enhance the efficiency of their livelihood activities and mitigate risks from weather uncertainties and climate change.
Open up possibilities for smallholders to procure agri and farm inputs, such as seeds, chemicals, fertilizer, and farm equipment. Moreover, the inputs procured through established digital means, can be of better quality, sourced conveniently, timely, and potentially at lower prices compared to traditional channels of agro-dealers and retailers.
Provide support through better visibility to market prices and demand, and realize better prices by marketing the produce more widely and efficiently.
Open up new opportunities and frontiers, such as digital payments, credit and insurance, and derivative trading of produce.
Provide market-driven new income-generating opportunities, such as value addition, primary processing, and so on.
Digital agricultural platforms are useful for the providers of agri services and products in the following ways:
Through demand aggregation, the platforms can collect and communicate the needs and preferences of farmers easily to plan sourcing and supply of agri inputs. Input suppliers can understand the nuances of demand, which can help providers to develop robust supply chain management plans. They can understand the needs, constraints, and preferences of farmers better to provide them with personalized services.
As the models and platforms evolve, they can integrate supply chains to enable better information sharing between providers, processors, distributors, retailers, consumers, and supporting sectors.
Providers across value chains can use the platforms to gain a more accurate understanding of the needs of the farmers. They can utilize Artificial Intelligence (AI) and Machine Learning (ML) tools to align their offerings and services according to the expectations and aspirations of farmers.
Financial service providers can utilize data and analytics to provide relevant financial products and services. They can then use the data generated through digital agriculture services to improve their decision-making. Through the platforms, financial service providers can access more data points to develop robust credit-scoring models. This, in turn, can improve the efficiency of financial transactions and introduce greater transparency in pricing.
Kenya and India have been leading in the digitization of agricultural ecosystems among the developing countries in Africa and Asia. A broad range of digital agricultural services has either been evolving or is now available. These services depend on the levels of phone penetration and access, as well as high-speed internet availability and access. The graphic below examines this in detail.
The most basic of services provided through digital platforms are weather forecasts and advisories. The accuracy of these forecasts is critical for the recipients. Even minor discrepancies can lead to disastrous consequences. For example, in rain fed-areas or places with water scarcity, farmers irrigate crops based on expected rainfall. If the rainfall forecast is off-the-mark, they can end up flooding the fields or irrigating too little. These errors can destroy harvest-ready crops and risk their entire earnings in a season.
Therefore, many innovators, such as Skymetweather and ileaf are increasingly relying on local weather stations or Internet of Things (IoT) sensors located on the field to predict critical weather parameters as precisely as technology allows them to do. This is critical to building trust in and utility of the information and advisory services provided to the service recipients. In turn, it would enable such platforms to sustain membership and use of its services.
Precision agriculture tools are being used effectively to collect and analyze productivity levels alongside environmental and soil quality variables. This analysis enables service providers to recommend targeted actions to farmers. It can help them take precise actions to realize higher productivity levels or to prevent disease and pest infestation. For example, they can apply appropriate doses of nutrients, select an appropriate mix of fertilizers or chemicals, and maintain the required water levels and temperature of their crops.
Several Agritech firms offer precision agricultural tools based on Artificial Intelligence (AI) and Deep Learning (DL) solutions. They collect data through drones, IoT sensors, or satellite images or a combination of all three sources. These firms provide strategic solutions to improve productivity, efficient use of resources, enhanced risk forecasting, management capabilities, and so on. The ability to access precise data can increase profits and inform the process of making credit decisions.
Most extant platforms focus on providing only a handful of use-cases, such as advisory services, the supply of inputs, digital credit, or selective captive buying. This is a major downside of their approach. Moreover, the platforms often offer each of these services piecemeal and not as a basket of multiple services to farmers.
This offers an important opportunity for providers to integrate multiple services on a unified platform to make them more powerful. These services can include financial services, input demand aggregation and delivery, output (production) estimation and market linkages with multiple buyers, and digital payments, among others. Such integration would be immensely useful to farmers and providers. An integrated agri-platform approach can enable providers to add multiple new and relevant services, leveraging demographic and transaction data, and creating synergies with other providers on the platform.
Digital agricultural platforms can transform the agricultural sector but it will be essential to pay attention to the digital divide. Platforms must be designed to be inclusive for female farmers and for segments that enjoy limited or no access to digital tools or are unable to use them.
In some countries, the digital databases of governments capture vital farmer demographic and transactional information that covers a wide range of important parameters. These databases have been evolving to become mature and robust. One of the largest examples is the Prime Minister Fasal Bima Yojana (PM Agri insurance) and the integrated Mobile Fertilizer Management System (mFMS) in India. Individually, these databases serve varying purposes. However, unifying these databases to draw insights from across them could be immensely valuable. MSC and the Indian government’s policy think-tank NITI-Aayog are in discussions to explore the architecture and roadmap to achieve this.
Access to credit remains the biggest barrier to the sustainability of smallholder farmers. Digital agricultural platforms can have a critical role to enable access to credit. It can address several of the barriers that currently limit the availability of credit. Banks are risk-averse to work with farmers due to the limited availability of financial information around them. Digitized data can provide digital footprints in the form of sales records and purchases to determine the capacity to repay loans. Individual farmer profiles, social data, agronomic data, economic, and transaction data can be utilized to make credit-scoring algorithms more robust.
Agribusinesses already collect much of the information that banks require for credit assessments. A growing number of farmers are using mobile phones for financial transactions. These methods can enable financial institutions to undertake appraisals, conduct credit scoring, and take better lending decisions.
Kenya Commercial Bank (KCB) introduced a mobile-based platform for smallholder farmers called MobiGrow. It receives support from the MasterCard Foundation. The platform is accessible to over two million farmers in Kenya and Rwanda, who avail loans, savings, insurance, and agribusiness training opportunities. In its first year of operations, it registered over 400,000 farmers and saw transactions worth USD 22.4 million being conducted.
Bundled financial services can contribute to the scaling of the platforms. Providers can enable a wider range of financial services for the users, utilizing digital data trails, and combining access to agricultural information with financial services. The ease and the amount of data that can be collected for farmers will increase as the cost of digital tools continues to decline.
FarmDrive runs a credit-scoring system by using agronomic data, satellite data, and social data to link-local financial institutions to lend to eligible farmers. Impact Terra is a digital agricultural platform in Myanmar that bundles services as well. Its Golden Paddy platform reaches 2.8 million unique users and offers relevant information on best practices, weather, pricing information, and access to buyers, suppliers, and financial institutions.
A unified digital agricultural platform requires collaboration between multiple actors with complementary expertise. An open and shared data platform approach can be even more compelling, as this approach would offer significant upsides. These include: reduced and shared costs; ability to spread risks and bring innovations to market collaboratively and more quickly; mutually beneficial solutions, such as unified loyalty programs on the platform; ability to achieve scale and volumes rapidly; and to engage and provide support to governments. However, this also requires a much greater willingness on the part of providers to collaborate and share data and resources.
Innovative forward-looking providers, that realize the power and the value of unified services, can take a lead and the first steps to unify digital agricultural service. Philanthropic funding can provide a much needed initial support for proofs-of-concept and early demonstration of unified services, to catalyze crowding-in of additional investments for scale-up efforts.
An abridged version of the blog was first published on Soko Directory on 20th of May, 2020
Togo has ambitious plans to embrace digitization as a lever to modernize the economy and society. To this effect, the West African nation has created innovation centers to support the startup industry and provide an environment that enables innovation, research, and development. The World Bank’s Doing Business 2020 Report rated Togo as Africa’s best reformer in 2019. The ecosystem comprises 17 FinTechs, and more than 10 enablers and funding partners.
The government’s efforts to drive financial literacy and to include FinTechs into its digitization strategies alongside offering second-generation services are key success factors for FinTechs to stimulate financial inclusion.
Financial inclusion can increase if FinTechs join the playing field. Enablers include partnerships with incumbents, streamlining banks’ processes to lower costs, designing for client needs, use of alternative data, and enacting effective regulation.
With a vibrant startup ecosystem and growing access to investors, Dakar ranks ninth in Africa in terms of Fintech activity, according to the Global FinTech Index City Rankings 2020. The Government of Senegal is supportive and wants to enhance the growth of digital industries and strengthen the entrepreneurial ecosystem, yet FinTechs need access to funding and qualified staff.
The key success factor for FinTechs to stimulate financial inclusion in Senegal is the strong existing financial services sector. The ecosystem comprises 24 FinTechs and 47 enablers and funding partners. FinTechs can increase financial inclusion through partnerships with incumbent operators by streamlining banks’ processes to reduce their costs and by providing them with Open APIs. Yet this would require effective regulation.
