Analysis and Development of Data Validation Tools in Financial Systems: Case Study on Data Quality in Investment Funds

by Xhoana MYRTA

Abstract
Investment funds are pooled investment vehicles that collect capital from multiple investors to invest in diversified portfolios of financial assets such as equities, bonds, real estate, or other securities. They play a crucial role in financial markets by providing liquidity, enhancing market efficiency, facilitating capital formation, and offering diversification benefits for investors. However, the reliability of decisions taken by these funds is heavily dependent on the quality of the data they utilize. Inaccurate or incomplete data threatens market integrity, investor trust, and compliance with regulatory standards. This article examines the impact of data validation processes in financial systems, with a particular focus on investment funds. The study develops and tests a software-based data validation tool, enabling users to define validation rules for each dataset column and automatically detect inconsistencies. A mixed-method approach was used, combining literature review, SWOT analysis, case study research, and software testing. Results demonstrate that robust data validation processes significantly reduce inaccuracies, improve compliance, and strengthen investor confidence. The implications extend to enhancing decision-making, operational efficiency, and regulatory alignment in financial markets. This research contributes to the understanding of data validation as a strategic mechanism for ensuring data integrity in investment funds and offers pathways for the development of advanced validation tools in the financial sector.

Keywords: financial data validation, financial systems, investment funds, validation software, compliance, data integrity