Personal Budgeting: Analysis of Software Solutions and Optimization Opportunities

Abstract

In the current context of rapid digital technology development and widespread adoption of internet banking, the popularity of cashless transactions and electronic banking services is growing significantly. This trend, in turn, stimulates interest in personal budgeting and financial planning tools, which enable users to better control expenses, build savings, achieve long-term goals, and make informed financial decisions on a daily basis. This article presents an analysis of five popular mobile applications for personal budgeting, evaluating their functionality, advantages, and limitations. The study examines the presence of built-in mechanisms for budget planning, goal setting, income and expense monitoring, and tools for automated fund allocation. Particular attention is given to the issue of budget optimization using modern mathematical methods. The article explores the potential integration of the simplex method of linear programming into mobile applications for personal financial planning, aiming to create budgets under resource constraints and meet specific financial objectives. A practical example of solving an optimal expense allocation problem using the Python programming language and the scipy.optimize library is provided. The implementation of this model into an Android application via the Chaquopy plugin is also demonstrated. The study considers modern literature on financial literacy, behavioral finance, and psychological aspects of money management, including Thaler’s theory of mental accounting. Additionally, it reviews relevant sources on software tools and mathematical methods. The results may serve as a basis for developing more effective mobile applications with adaptive budgeting functionality.