Motivation – The “Why”
As per Agriculture Census, 2015-16 India has 126 million small and marginal farmers and requires Rs 37-40 Lakh Crore (400-500 US$ Billion) of working capital annually. RBI estimates that approx. 59.1 % of small and marginal farmers and 30 % of agricultural households avail credit from non-institutional sources probably since they cannot offer collateral to avail institutional credit. As per NAFIS Survey 2016-17, only 10.5 % of agricultural households have a valid Kisan Credit Card since several households have multiple cards and, in several states, (e.g., Tamil Nadu, Andhra Pradesh, Kerala, Karnataka), 71% of the crop loans are disbursed outside of KCC.
As per RBI (2019) – aggressive efforts are needed to improve institutional credit through technology-driven solutions:
- Credit is largely dependent on the operated area due to constraints on data available on other credit determinants, such as district-wise input cost for a crop, type of crops being grown, crop-wise sown area, etc.
- Banks to explore collaborations with Agri Start-ups to provide access to credit efficiently to farmers.
- IBA to come out with a tech-driven portal to ease farmer credit.
Scope – The “What”
The Agri Collaboratory is helping build common digital infrastructure (“Digital Rail”) as a digital public good, in open source for the ecosystem and the government. Project AgCx aims to simplify Farm Credit Assessment for Small & Marginal farmers by triangulating consented, multi-year, disparate, public, and private data sets. TAC is an “Agri ecosystem builder” and the primary point of contact for stakeholders and the general administrators of the project.
Project AgCx Objective: Create an affordable assessment of 1) The Farmer, 2) Her Farm, 3) Target Crop + Credit Usage.
“In 50 | At 50 | For 50”: Realtime – in less than 50 min, at a base cost of Rs 50 (for the farmer), at national scale – for 50+ Million farmers, (directly or with FPOs), and monitor credit usage to improve recovery.
Roadmap – The “How”
The Agri Collaboratory (TAC) partners with Samunnati, Govt of Telangana, RICH, Cropin, Satsure, The Indian Institute of Science (IUDX), Digital Green, and others to build open-source digital assets and enable data flows. The insights from these diverse datasets, combined with local level information from the Govt, along with policy and regulatory changes, can provide accurate, real-time credit assessment for millions of small and marginal farmers.
The Project AgCx will focus on a 3-5 year, 4-phase implementation plan:
Phase 1: Concept Development & Buy-in:
- Create a detailed conceptual design to get buy-in from stakeholders (domain, technology, government, funders).
- Conduct experiments in a sandbox environment at Mulkanoor, Telangana for ~3000 farmers to test out various elements of Project AgCx, across multiple stakeholders.
Mulkanoor and Jammikunta, Telangana experiments:
Approach:
Collate issues related to agri credit (and more broadly, rural finance) across perspectives; a) Incomplete definition of a farmer, b) Insufficient cashflow for farmer, c) Limited flow of credit to small and marginal farmers e) Glacial credit request processing and f) Lack of personal financing offerings. Establish key linkages between various parts of the crop cycle, impacting rural finance. This project is organized into 3 workstreams.
- As-is process mapping: Conduct a survey to capture farmer demographics, feedback on lending products and schemes (when and what stage they need loan, awareness of various government schemes, access to institutional credit) and feedback on credit process and hurdles (how much time it took them to avail loan, challenges / issues in getting the loan, reasons for loan delays / rejections and the advantages of being a member of a farmer collective)
- Credit assessment report: Create a credit assessment report with inputs from various lending institutions (public and private sector banks, NBFCs & Co-operative societies. This report then can be used by the lending institutions using a configurable business rule engine depending on the type of loan, tenure, secured vs unsecured. Streamlining the credit assessment report will enable wider adoption and minimize loan rejections.
- Data integration: Accurate and quality data is key for timely decision making, creating scale and interoperability. To validate this hypothesis, check the veracity of consented farmer data with Government Telangana data base, integrate this data with public and private data sets (e.g. Satellite data for crop history / yield, soil data, irrigation data, local demand, credit history and loan usage)
Phase 2: Proof of Concept (POC): Conduct several controlled (iterative) experiments (POC), in 3 districts, 6 talukas with about 30,000 farmers to develop and validate the following key steps for Project AgCx:
- Agri Lender Ecosystem Buy-in: Concur with RBI, Banks, NBFCs, NABARD, etc. on an approach of using Data-based Farm Credit Assessment and fine-tune the alternate credit assessment report format.
- Cash Flow Lending: Build an industry approach toward cash-flow lending for rural finance
- Enable potential data sources: Test data availability with Govt., Private, and the public sector, validate data accuracy with ground sources, and match Farm ID to the Farmer through unique identifiers.
- Aggregate Data: Collate data from multiple sources through a semi-automated process to validate the suitability to create the credit assessment report based on ground reality.
- Automate: Test an automated Agri Data Exchange and Farm Credit Application with the selected Data streams.
Phase 3: Pilot: Conduct detailed pilots based on the learning from the POCs, in 3-4 states, 10 districts for 100,000 farmers:
- Test suitability and interoperability of data at scale: Across several agronomic zones, and farmer types including tenanted. Test ability of AgCx with automated Agri Data Exchange to process transactions in minutes and at low cost (~ Rs 50 to 100 / farmer).
- Build version 2 of the AgCx platform: Focusing on cashflow lending and integrations with MoF, MoA, NIC, and other agencies.
- Test wider applicability: – include broader datasets by onboarding 15+ Data Providers and 10+ Agri lenders.
Phase 4: Field Trial Roll-Out: Rollout AgCx in 2-4 states as a production trial. Establish commercial business models for AgCx to be self-sustainable. Onboard 25+ Data Providers and 25+ Farm Credit lenders.
Aspirational Cash-Flow Lending: The Vision for 2025
A cash-flow based lending system (which currently does not exist in agriculture) will allow for a gradual credit rating to be built over time and bring in the unserved and underserved rural population into the institutional credit framework. While collateral based lending favors farmland owners, the cash flow lending model focuses on the “farmer” rather than the “owner” and works for both – landholder farmer and tenanted farmers.
Desired state: Selvam, a rice farmer with a two-acre farm near Madurai, requires a loan amount ahead of the agricultural season. He approaches a digitally trained entrepreneur in his village with his details (crop, land, income, identity, etc). Much like a LIC agent / independent financial advisor, this digitally trained village level entrepreneur (VLE) enters the Selvam’s details including crop, livestock, background etc. with his consent into the system and accesses pre-approved templates from different banks: Axis, IndusInd, HDFC, Samunnati, etc. He helps Selvam understand their products, and choose a few options, based on best fit with requirements from all options. Upon selecting the correct product, the VLE submits the application on a digital platform. Within half an hour, Selvam closes the loan, and links insurance. Everything is coordinated by the VLE who not only aggregates information but also ensures technical advice is provided and is paid by Selvam for his efforts. Multiple sellers compete for his business in a digitally enabled process.
The Agri Collaboratory 