Unique Presentation Identifier:

71

Program Type

Honors

Faculty Advisor

Mrs. Rebecca Cunningham

Document Type

Presentation

Location

Face-to-face

Start Date

9-4-2026 9:00 AM

End Date

9-4-2026 9:30 AM

Abstract

College students often lack accessible tools that combine real-time financial tracking, mobile accessibility, predictive analytics, and secure system design, leaving many without structured insight into their spending behavior. MoneyUP is a full-stack financial management platform developed to address these challenges through a secure, data-driven budgeting system deployed as both a web application and a cross-platform Flutter mobile application. The system integrates the Plaid API in its Sandbox environment to synchronize simulated banking data for secure testing without exposing live financial credentials. Transaction data is processed and stored using Supabase with a relational PostgreSQL database structured to enforce normalization, referential integrity, and policy-based access control through unified authentication and role management. Unlike traditional budgeting tools that primarily categorize historical transactions, MoneyUP incorporates a machine learning model that analyzes spending behavior to generate personalized budgeting recommendations and predictive financial insights, enabling proactive financial planning rather than reactive expense tracking. The platform follows a modular architecture separating authentication, transaction synchronization, machine learning logic, and presentation layers to improve scalability and maintainability across mobile and desktop environments. Key engineering challenges addressed include managing high-volume transaction datasets, optimizing real-time synchronization, ensuring cross-device responsiveness, and maintaining secure financial data handling practices. These architectural decisions establish a scalable foundation for predictive, student-centered financial planning systems

Download

Share

COinS
 
Apr 9th, 9:00 AM Apr 9th, 9:30 AM

MoneyUP: A Predictive Financial Management System for College Students

Face-to-face

College students often lack accessible tools that combine real-time financial tracking, mobile accessibility, predictive analytics, and secure system design, leaving many without structured insight into their spending behavior. MoneyUP is a full-stack financial management platform developed to address these challenges through a secure, data-driven budgeting system deployed as both a web application and a cross-platform Flutter mobile application. The system integrates the Plaid API in its Sandbox environment to synchronize simulated banking data for secure testing without exposing live financial credentials. Transaction data is processed and stored using Supabase with a relational PostgreSQL database structured to enforce normalization, referential integrity, and policy-based access control through unified authentication and role management. Unlike traditional budgeting tools that primarily categorize historical transactions, MoneyUP incorporates a machine learning model that analyzes spending behavior to generate personalized budgeting recommendations and predictive financial insights, enabling proactive financial planning rather than reactive expense tracking. The platform follows a modular architecture separating authentication, transaction synchronization, machine learning logic, and presentation layers to improve scalability and maintainability across mobile and desktop environments. Key engineering challenges addressed include managing high-volume transaction datasets, optimizing real-time synchronization, ensuring cross-device responsiveness, and maintaining secure financial data handling practices. These architectural decisions establish a scalable foundation for predictive, student-centered financial planning systems