Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/3528
Title: | WONGA: The Future of Personal Finance Management – A Machine Learning-Driven Approach for Predictive Analysis and Efficient Expense Tracking |
Authors: | Uyanahewa, M.I.R Jayawardana, G.V.H.D Bandara, M.B.D.N Hapugala, H.A.V.V Attanayaka, B |
Keywords: | Personal finance SMS tracking expense classification expense prediction budget planner image processing machine learning regex NLP ANN CNN |
Issue Date: | 10-Jul-2023 |
Publisher: | IEEE |
Citation: | U. M.I.R, J. G.V.H.D, B. M.B.D.N, H. H.A.V.V, B. Attanayaka and D. Nawinna, "WONGA: The Future of Personal Finance Management – A Machine Learning-Driven Approach for Predictive Analysis and Efficient Expense Tracking," 2023 4th International Conference for Emerging Technology (INCET), Belgaum, India, 2023, pp. 1-6, doi: 10.1109/INCET57972.2023.10170209. |
Series/Report no.: | 2023 4th International Conference for Emerging Technology (INCET); |
Abstract: | The financial literacy of Sri Lankans is relatively low, leading to difficulties in managing personal finances. This research presents a smart solution to simplify the complexities associated with money management and assist individuals in managing their finances more efficiently to achieve better financial health without requiring a comprehensive knowledge of money management from the user. The proposed system automates personal finance management with minimal user effort, reducing manual data entry by tracking cash flow by utilizing SMS messages and expense bills to extract bank transaction data and cash expenditures. Each extracted expense will automatically be categorized into the correct expense category. The system also generates a custom budget plan for each user based on spending patterns to help them stay on the budget throughout the month and avoid irrational overspending. Furthermore, the system provides a mechanism to predict future expenses associated with upcoming events based on calendar events, allowing users to devise the most efficient budget plan and avoid facing financially unprepared events in the upcoming month. All these smart solutions are bundled up in the "Wonga" mobile application to help users make better financial decisions to achieve personal financial success. |
URI: | https://rda.sliit.lk/handle/123456789/3528 |
ISSN: | 979-8-3503-3575-0 |
Appears in Collections: | Department of Computer Science and Software Engineering |
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WONGA_The_Future_of_Personal_Finance_Management__A_Machine_Learning-Driven_Approach_for_Predictive_Analysis_and_Efficient_Expense_Tracking.pdf Until 2050-12-31 | 1.22 MB | Adobe PDF | View/Open Request a copy |
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