International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 11 | Nov 2025
p-ISSN: 2395-0072
www.irjet.net
Agri Finance Mate: Smart Agricultural Loan Calculator & Advisory Tool Aparna Shendkar, Vikas Nandeshwar, Soham Manjaratkar, Harsh Sonar, Gauri Solanke, Soham Vyavahare, Saksham Sonawane, Bhushan Sopal F.Y.B. Tech Students’ Applied Science & Engineering Project1 (ASEP2) Paper, SEM 2 A.Y. 2024-25 Vishwakarma Institute of Technology, Pune, INDIA. F.Y.B. Tech Students’ Applied Science & Engineering Project1 (ASEP2) Paper, SEM 2 A.Y. 2024-25 Vishwakarma Institute of Technology, Pune, INDIA. Department of Engineering, Sciences and Humanities (DESH) Vishwakarma Institute of Technology, Pune, Maharashtra, India ---------------------------------------------------------------------------***----------------------------------------------------------------------
Abstract- Many farmers struggle to understand how
simplify complex financial concepts such as cost estimation, loan repayment plans, profit forecasting, and investments by providing a user-friendly interface suitable for agricultural contexts.
agricultural loans work and how much they need to repay. This paper presents, Agra Finance Mate, is an easy-to-use tool that helps farmers calculate important loan details like the amount they can borrow, the interest they will pay, and their monthly installments (EMIs). By entering basic details like the type of crop, land size, and income, farmers can quickly get useful financial information. This tool is designed to make the loan process clearer and easier, especially for farmers who may not have access to financial experts. It also supports better planning and helps build trust between farmers and banks. In this paper, we explain how we created Agri Finance Mate and how it can help improve the way farmers manage their finances.
This research paper mainly explores the development and impact of the agricultural finance calculator. The paper mainly highlights its role in improving financial literacy, enhancing access to credit and loans, and assisting suitable agricultural practices. By leveraging this tool, stakeholders in the agricultural sector can generate better financial revenue and ultimately contribute to food security and rural development. Altogether empowering the nation's growth.
Keywords— Agri Finance Mate, Agriculture, Crop dvisory, EMI, Financial Literacy, Firebase, Government Schemes, Loan, Mobile App, Offline Mode, Subsidy, User Experience (UX), Web Application
Further, the paper is elaborated in different parts/sections, where I Section has the Introduction part, II Section has Literature Review, Section III comprised Methodology, Section IV contains research and discussion, Section V has Results, and Section VI contains conclusion.
I. INTRODUCTION
II. LITERATURE REVIEW
Agriculture is the backbone of many countries, especially developing countries. A significant population in many countries relies on agriculture as a source of livelihood. Though agriculture has much significance, this sector often faces numerous challenges, including inadequate access to credit, poor financial planning, and a shortage of tools required for effective budgeting and investment analysis. These issues obstruct the growth and sustainability of the farms, particularly for small landholders who operate on limited resources. To address these challenges, the use of technology in agricultural finance can be a suitable solution. The agricultural finance calculator is such a kind of innovation. It is a digital tool designed to assist farmers, agricultural businesses, and policymakers in making proper financial decisions. This calculator aims to
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Prior studies have concentrated on digital services, insurance, and microloans to help farmers. Personalized risk assessments and adaptable financial solutions are still lacking, though, which emphasizes the necessity of a comprehensive, data driven fetch platform designed specifically for smallholder farmers.[1] By enhancing irrigation infrastructure, which uses roughly 70% of water, water-saving agriculture helps to alleviate the agricultural water issue. To build these infrastructures and encourage sustainable farming, public funding is crucial.[2] In an effort to increase access to financial services, research focuses on streamlining farmer loan applications by utilizing machine learning models like logistic regression and random forest to predict loan
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