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- W4309048571 abstract "A good amount of people seeking loans in India has enlarged to a greater extent and the reasons for it could be many. The Employees working in banking sectors are deprived of knowledge to judge or foresee whether a customer (good or poor) will be able to pay the debt of the loan at the stipulated interest rate. Throughout the financial system, banking institution offer a variety of services, but lines of credit remains their primary and the biggest source of income. As a consequence, banking businesses will prosper from the revenue produced on the mortgages they make. Lending, or whether consumers return the money or default on one’s loans, actually impact a banking institutions’ financial statement. The banking institutions non-performing investments will be diminished by estimating mortgage. Consequently, more exploration into this event happening is needed. Because detailed estimations are crucial and essential for sufficient service, various methodologies must be assessed and analyzed. Our study and work research seeks to provide a comprehensive review of lending estimation systems and structures that employ prediction methods and techniques flourished and developed after recent years. In this study and paper, researchers studied the learning techniques as well as the raw datasets utilized for training and test sets. The system model’s precision is also discussed. Our work also provides a quick overview of a few datasets that can be used to anticipate loan/mortgage analysis. Recent and future trends are also spotlighted." @default.
- W4309048571 created "2022-11-21" @default.
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- W4309048571 date "2022-11-14" @default.
- W4309048571 modified "2023-10-16" @default.
- W4309048571 title "An Exploratory Study-Based Analysis on Loan Prediction" @default.
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- W4309048571 doi "https://doi.org/10.1007/978-981-19-4960-9_33" @default.
- W4309048571 hasPublicationYear "2022" @default.
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