The frustration I observed with existing mobile personal finance apps was clear: the effort required to input daily expenses felt disproportionately high compared to the limited reward of truly understanding and managing one's money dynamically. These apps often lacked a 'responsive' intelligence, failing to adapt to the natural ebb and flow of a user's spending habits. Budgets felt rigid and backward-looking – a constant calculation of 'how much is left to survive' rather than a proactive guide based on actual needs and goals.

This insight fueled my passion to create a different kind of personal finance experience. My project aimed to empower users to spend according to their needs, guided by a logic-based budget. This approach moves beyond static assumptions, offering a more reasonable and intuitive way to manage daily finances. Instead of just tracking what's gone, the focus was on enabling users to achieve their meaningful life goals.

Visualisation became a powerful tool in this endeavor. I designed interfaces that transformed raw expenditure data into actionable insights, helping users understand their spending patterns and progress towards their objectives. Crucially, I integrated a prediction algorithm to minimize the burden of manual input. This algorithm aimed to intelligently predict a user's daily budget and even anticipate potential expenses – a proactive list of likely or unlikely expenditures. This drastically reduced the effort required from the user, making expense tracking less of a chore and more of a seamless part of their day.

This project culminated in the development of a novel mobile-based finance application. The journey involved a thorough analysis of existing personal finance apps and shopping websites to pinpoint their shortcomings. From there, I explored various innovative approaches to address these issues.

I experimented extensively with different methods for inputting expenses, striving for maximum ease and efficiency. To rigorously test the effectiveness of the prediction algorithm and its impact on user behavior, I employed a modified "Wizard of Oz" technique over a 30-day period. This allowed me to simulate the algorithm's predictions and gather valuable user feedback on its accuracy and helpfulness in anticipating their budget and potential expenses.

The interface I designed for recording expenses and displaying the algorithm's output was iteratively refined based on user feedback, ensuring it was both intuitive and informative. The entire flow of how the prediction mechanism was tested with users was carefully documented to understand the user journey and identify areas for improvement. Ultimately, the positive user responses to this testing validated the core principles of the project: that by minimizing input effort and providing responsive, goal-oriented insights, we could create a personal finance tool that truly empowers users to manage their money effectively and achieve their aspirations.