Madhavi Nirati

Papers

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About

Madhavi Nirati is a researcher at the forefront of applied machine learning, with a primary focus on predictive analytics in financial technology. Her most-cited work, "Predicting Possible Loan Default Using Machine Learning" (2022), published in The International Journal of Computer Science Engineering and Its Research Trends (IJCERT), has garnered 2 citations and lays a critical foundation for risk assessment models. In this study, Nirati explores algorithmic approaches to forecasting borrower default, addressing a key challenge in lending by leveraging classification techniques to improve accuracy and reduce financial risk. Her contribution is notable for bridging theoretical machine learning methods with real-world financial decision-making, offering a scalable framework that could enhance credit evaluation systems. While early in her career, Nirati’s work signals a commitment to developing data-driven solutions for economic stability. Her research holds promise for students and practitioners interested in the intersection of computer science and finance, particularly in building robust predictive models that mitigate default risk. As her citation count grows, Nirati is poised to become a significant voice in the application of AI to financial services.