Savemore: An AI-Based Artefact to Improve Financial Literacy and Savings in Ireland

Chhabra, Keshav (2025) Savemore: An AI-Based Artefact to Improve Financial Literacy and Savings in Ireland. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (794kB) | Preview
Preview	PDF (Configuration Manual) Download (454kB) | Preview

Abstract

This practicum research investigates Savemore, an AI-based solution to improve the saving habits and financial literacy amongst students, gig workers, freelancers, small business owners, and part-time earners in Ireland. Due to the uncertainty of income, these groups often face restrictions or very limited access to tailored financial tools, which leads to poor saving practices and elevates financial stress. With solutions like Savemore, intelligent tailored guidance related to automated budgeting, interactive financial literacy training, and moneysaving suggestions could be helpful solutions. Additionally, it aims to provide intelligent customer-focused individualized guidance, which can help in reducing financial stress by guiding users to make wise decisions for their spending habits.

This research report includes mixed-methods assessment and prototype development in accordance with the Design Science Research (DSR) approach. It includes the analysis of synthetic datasets of 1,000 simulated users for quantitative research from usage analytics and qualitative feedback from the survey conducted with a small group of people to integrate the feature and consider their concerns, which helped in the overall development of the design for the user-friendly interface.

Additionally, the findings of the research show that Savemore can help users gain awareness of spending trends, increase savings, and build confidence in managing personal finances. Also, its accessibility and simplistic interface can benefit those with limited time and access or financial expertise.

This report concludes how AI-driven solutions can have a transformative impact on the vulnerable earning groups for enhancing the understanding of budgeting and savings amongst them.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Del Rosal, Victor UNSPECIFIED
Subjects:	H Social Sciences > HG Finance Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HG Finance > Fintech T Technology > T Technology (General) > Information Technology > Fintech L Education > LC Special aspects / Types of education > Literacy
Divisions:	School of Computing > Master of Science in FinTech
Depositing User:	Ciara O'Brien
Date Deposited:	24 Jun 2026 10:28
Last Modified:	24 Jun 2026 10:28
URI:	https://norma.ncirl.ie/id/eprint/9391

Actions (login required)

View Item