Machine Learning Enabled Financial Statements in Assessing a Business's Performance
- Title
- Machine Learning Enabled Financial Statements in Assessing a Business's Performance
- Creator
- Priya P.S.; Shah J.A.; Aarawal A.; Kalra R.; Kadam S.; Sontakke K.A.
- Description
- Machine Learning Enabled Financial Statements (MLEFS) revolutionize corporate performance analysis. This study examines MLEFS's dramatic effects using data gathering, model creation, interpretability, deployment, and ethics. We found that MLEFS accurately predicts crucial financial measures, helping investors, lenders, and financial analysts make better judgments. The study emphasizes the importance of financial measures like Return on Assets (ROA) in supporting financial theories and models. The research also stresses interpretability and ethics, promoting responsible machine learning in finance. Future trends include enhanced interpretability, strong ethical frameworks, real-time analysis, big data integration, regulatory adaption, and industrial acceptance. This study opens the door to data-driven financial analysis and decision-making, improving strategic planning, risk reduction, and investor trust. 2024 IEEE.
- Source
- Proceedings of 9th International Conference on Science, Technology, Engineering and Mathematics: The Role of Emerging Technologies in Digital Transformation, ICONSTEM 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Business Performance; Ethical Considerations; Financial Analysis; Financial Ratios; Financial Statements; Interpretability; Investor Confidence; Machine Learning; Predictive Analytics; Return on Assets (ROA)
- Coverage
- Priya P.S., Sri Krishna College of Technology, Tamil Nadu, Coimbatore, India; Shah J.A., Amity Business School, Amity University, Maharashtra, Mumbai, India; Aarawal A., Management, Ndiit, Delhi, New Delhi, India; Kalra R., School of Business And Management, CHRIST(Deemed To Be University), Karnataka, Bangalore, India; Kadam S., Symbiosis Institute of Business Management, Pune, Symbiosis International, Deemed University, Maharashtra, Pune, India; Sontakke K.A., Sies College of Management Studies, Department of Finance, Maharashtra, Navi Mumbai, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835036509-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Priya P.S.; Shah J.A.; Aarawal A.; Kalra R.; Kadam S.; Sontakke K.A., “Machine Learning Enabled Financial Statements in Assessing a Business's Performance,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 28, 2025, https://archives.christuniversity.in/items/show/19367.