This MSc Business Analytics project investigates the impact of rainfall on paddy harvest and its subsequent effects on agricultural loans in Sri Lanka. The research aims to predict agricultural loan losses by analyzing historical data related to rainfall, paddy cultivation, and loan performance. The project explores the significance of agriculture and agricultural loans in Sri Lanka, highlighting the need for risk mitigation strategies due to environmental factors. The methodology includes a literature review, research design (descriptive and inductive approach), data collection and analysis using multivariate regression. The project also covers requirement analysis, design of the solution, implementation with visualization and descriptive statistics, and testing and evaluation using techniques like ACF, PACF, MAPE, RMSE and change point analysis. The project concludes with recommendations and future work, offering insights for banks and borrowers to manage risks associated with agricultural loans effectively. The research provides practical implications for developing innovative loan products and risk mitigants, contributing to a better understanding of the relationship between environmental factors and financial outcomes.
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