Effective personal finance management involves tracking expenses, which enables people to monitor their spending and potentially meet their financial goals. Using intelligent tools to automate financial tracking, categorization, and analysis is essentially the only way to effectively manage spending in today's fast-paced environment. By separating and tracking each financial transaction, the Expenses Tracking Application with OCR and ML improves the efficiency of personal finance management. After taking textual data from receipts, bills, or invoices through a machine learning model for classification into user-defined categories, the program employs optical character recognition (OCR) to digitize the data. Small purchases benefit from the ability to manually enter transactions without paper receipts or invoices as it is possible to perform entry and classification. Users can do entry and categorization with few input errors. This tool is streamlined for the manual process that led to errors, simplified tracking, saved valuable hours, and provided prompt feedback regarding common trends: information on the time and manner in which user spending occurs. Users can also receive customizable spending notifications in the event of overspending, regular subscriptions, or common bills, among other expenses.
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Mohan et al. (Thu,) studied this question.
www.synapsesocial.com/papers/68d9052541e1c178a14f54fb — DOI: https://doi.org/10.62643/ijerst.2025.v21.n3(1).pp1795-1802
J. Mohan
Daya Santosh Tonape
D. Venkata Bhargav
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