SQL In Financial Modeling And UX Streamlining Data Integration For Better User Experiences

Abstract

This study explores the transformative role of SQL in financial modeling and user experience (UX) streamlining, focusing on its ability to enhance data integration, computational efficiency, and user satisfaction. By leveraging SQL's robust querying capabilities, financial institutions can improve the accuracy and scalability of forecasting, risk analysis, and portfolio optimization models. Empirical results demonstrate that SQL-based financial models achieve high accuracy rates, with forecasting models reaching 92.5% accuracy, while significantly reducing computational times. Furthermore, SQL-driven data integration enhances UX, as evidenced by a System Usability Scale (SUS) score of 85.6 and a Net Promoter Score (NPS) of 72, indicating strong user satisfaction. Statistical analyses, including ANOVA, t-tests, and regression models, validate the reliability and efficiency of SQL in handling large datasets and complex queries. The study also highlights SQL's ability to streamline risk analysis, with metrics such as historical volatility (18.5%) and Value at Risk (VaR) (5.8%) providing critical insights for decision-making. Qualitative feedback from users underscores the importance of real-time data access and intuitive interfaces, with 78% of users praising the ease of use of SQL-driven applications. These findings have significant implications for financial institutions seeking to adopt data-driven strategies, as SQL enables both technical robustness and user-centric design. The study concludes by identifying limitations, such as the reliance on a single dataset, and proposing future research directions, including the integration of SQL with emerging technologies like artificial intelligence and blockchain. Overall, this research underscores SQL's pivotal role in driving innovation and efficiency in the financial sector.