# Analyzing the Corporate Business Intelligence Impact: A Case Study in the Financial Sector
## 1 Introduction
In their study, a backtracking method was introduced in business intelligence and decision-making environments to increase plan failure and risk-taking ability. [PERSON] et al. (2022) proposed an IoT-based Efficient Data Visualization Framework (IoT-EDVF) to enhance the risk of leakage, analyze multiple data sources, and strengthen data quality management for business intelligence in the field of corporate financial [26]. [PERSON] et al. (2023) introduced a conceptual framework that outlines the key factors affecting the adoption of business intelligence systems within Libya's SME sector [27]. Artificial intelligence has established itself as a crucial element in the decision-making framework of business intelligence. The integration of AI into BI systems has transformed how organizations gather, analyze, and understand data to make well-informed choices. Utilizing machine learning, natural language processing, and sophisticated analytics, the collaboration between AI and BI has enhanced decision-making, boosted efficiency, and strengthened competitive positioning [28; 29]. [PERSON] and [PERSON] (2022) provided a comparison between traditional business intelligence (BI) and its augmented variant within the business analytics process [29]. Their findings indicated that augmented analytics improves analytical capabilities, shortens time frames, and facilitates data preparation, visualization, modeling, and insight generation. [PERSON] et.al. (2024) presented three models based on various feature set combinations and machine learning algorithms for predicting credit card customer churn in their study [30]. The results highlight the promise of machine learning in predicting customer attrition, allowing for the implementation of proactive retention strategies in the banking sector. According to research conducted by Fortune Business Insights (2023) in the United States, the areas where business intelligence is most widely applied are banking, financial services, and insurance (BFSI), healthcare, information technology and telecommunications, retail consumer groups, and manufacturing. According to research, BFSI is expected to have the highest market growth during the forecast period [31]. Again, in the research conducted by Fortune Business Insights (2024), it was stated that the size of the global business intelligence market is expected to increase from USD 31.98 billion in 2024 to USD 63.76 billion in 2032 and has a compound annual growth rate of 9.0% during the forecast period (2024-2032) [31]. This study aims to examine how data-driven strategies and decision-making processes are shaped in the corporate world by focusing on the increasing importance of business intelligence today. Another focus of the study is to reveal concrete applications of the impact of business intelligence on corporate performance and how business processes are optimized. In this way, the contribution of business intelligence to corporate success will be understood more comprehensively and will enable businesses to understand how to best benefit from this technology. To the best of our knowledge, no detailed study has been found in the literature. Therefore, this study will contribute to eliminating this deficiency in the literature. This study consists of five sections. After the introduction, the proposed research framework, methodology, and case study are examined. The results and discussion are presented in the Section 3, and the conclusions are given in Section 4. Finally, in Section 5, recommendations for future research are presented.