Marri, Siva Prasad (2025) Automating financial statement generation using Artificial Intelligence and machine learning. World Journal of Advanced Research and Reviews, 26 (2). pp. 1395-1399. ISSN 2581-9615
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Abstract
Artificial Intelligence and Machine Learning technologies are fundamentally transforming financial statement generation, bringing unprecedented levels of automation, accuracy, and analytical insight to traditionally manual processes. These innovations address the growing challenges of complex global operations and increasing regulatory demands through intelligent data aggregation, automated anomaly detection, optimized processing capabilities, and advanced visualization techniques. By integrating with existing financial systems, AI solutions streamline the collection and processing of financial data while enabling multidimensional analysis previously impossible through conventional methods. The implementation of machine learning algorithms for pattern recognition significantly enhances error detection while reducing false positives. Query optimization techniques dramatically improve processing speeds and system performance, enabling near real-time financial analysis. The combination of intuitive visualization tools and predictive analytics capabilities transforms financial reporting from retrospective documentation to forward-looking strategic intelligence. Organizations adopting these technologies report substantial benefits including reduced operating costs, improved forecast accuracy, accelerated reporting cycles, and enhanced decision support capabilities, positioning them to better navigate an increasingly data-driven business environment.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjarr.2025.26.2.1748 |
Uncontrolled Keywords: | Financial Automation; Artificial Intelligence; Machine Learning; Anomaly Detection; Predictive Analytics |
Depositing User: | Editor WJARR |
Date Deposited: | 20 Aug 2025 10:55 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/2859 |