Competitive Intelligence-Driven Financial Analytics: A Strategic Framework for Environmental Scanning and Sustainable Decision Support in Financial Software

Abstract

Purpose: To examine how Competitive Intelligence (CI) can be operationalized within financial software to support environmental scanning, strategic signal identification, and sustainable decision-making under volatile conditions. Methodology/Approach: A quantitative, design-oriented approach was applied to OpenFinData, comprising 1,500 records across 19 financial tasks mapped into 12 CI dimensions. The analysis combined data preprocessing, TF-IDF, dimensionality reduction, clustering, and exploratory indicators of information density, responsiveness, and strategic fit. Originality/Relevance: The study integrates Competitive Intelligence, Financial Analytics, and Dynamic Capabilities, positioning financial software as enabling infrastructure for organizational intelligence processes while distinguishing computational capability from organizational CI capability. Key Findings: The findings reveal different levels of coverage and alignment between analytical workloads and CI dimensions, with greater concentration in investment intelligence and risk and compliance intelligence. Workload structure shows potential to support organizational sensing and strategic decision support but should not be interpreted as a direct measure of organizational CI maturity. Theoretical/Methodological Contributions: The study extends the interface among CI, Environmental Scanning, Financial Analytics, and Dynamic Capabilities and proposes a reproducible procedure for mapping analytical demands into CI dimensions and assessing their strategic alignment.