Integrating Financial and Textual Indicators for Enhanced Financial Risk Prediction: A Deep Learning Approach
DOI:
https://doi.org/10.54536/ajfti.v2i1.2489Keywords:
Financial Indicators, Textual Indicators Management Discussion and Analysis, Deep Learning, Financial Risk PredictionAbstract
The study evaluates the effectiveness of financial indicators in financial risk prediction and develops a framework using financial and textual data. It emphasises the importance of both data types in risk assessment and prioritises liquidity and industry specific metrics. The analysis of the existing literature affirmed the significance of both data types in risk assessment. The findings of the study revealed a strong correlation between financial and textual indicators. The selection of deep learning was based on its adeptness in handling diverse unstructured data, justifying its application. This innovative methodology enhances financial risk prediction and supports strategic decision-making.
References
Al-Eitan, G. N., & Bani-Khalid, T. O. (2019). Credit risk and financial performance of the Jordanian commercial banks: A panel data analysis. Academy of Accounting and Financial Studies Journal, 23(5), 1-13.
Alduais, F. (2022). Textual analysis of the annual report and corporate performance: evidence from China. Journal of Financial Reporting and Accounting.
Arnold, M. N. G., Balakrishnan, M. R., Barkbu, M. B. B., Davoodi, M. H. R., Lagerborg, A., Lam, M. W. R., Medas, M. P. A., Otten, M. J., Rabier, L., & Roehler, C. (2022). Reforming the EU fiscal framework: Strengthening the fiscal rules and institutions. International Monetary Fund.
Bawa, S. S. (2023). Implementing Text Analytics with Enterprise Resource Planning. International Journal of Simulation--Systems, Science & Technology, 24(1).
Chen, Y., Kumara, E. K., & Sivakumar, V. (2021). Investigation of finance industry on risk awareness model and digital economic growth. Annals of Operations Research, 1-22.
Dianova, A., & Nahumury, J. (2019). Investigating the effect of liquidity, leverage, sales growth and good corporate governance on financial distress. Journal of Accounting and Strategic Finance, 2(2), 143-156.
Feyen, E., Natarajan, H., & Saal, M. (2023). Fintech and the Future of Finance: Market and Policy Implications. World Bank Publications.
Humphreys, A., & Wang, R. J.-H. (2018). Automated text analysis for consumer research. Journal of Consumer Research, 44(6), 1274-1306.
Iqbal, J., & Riaz, K. (2021). Predicting future financial performance of banks from management’s tone in the textual disclosures. Quality & Quantity, 1-31.
Karas, M., & Režňáková, M. (2020). Cash flows indicators in the prediction of financial distress. Engineering Economics, 31(5), 525-535.
Mai, F., Tian, S., Lee, C., & Ma, L. (2019). Deep learning models for bankruptcy prediction using textual disclosures. European journal of operational research, 274(2), 743-758.
Maisharoh, T., & Riyanto, S. (2020). Financial Statements Analysis in Measuring Financial Performance of the PT. Mayora Indah Tbk, Period 2014-2018. Journal of Contemporary Information Technology, Management, and Accounting, 1(2), 63-71.
Malekloo, A., Ozer, E., AlHamaydeh, M., & Girolami, M. (2022). Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights. Structural Health Monitoring, 21(4), 1906-1955.
Mashrur, A., Luo, W., Zaidi, N., & Robles-Kelly, A. (2020). Machine Learning for Financial Risk Management: A Survey. IEEE Access, 8, 203203-203223. https://doi.org/10.1109/ACCESS.2020.3036322
Metaxa, D., Park, J. S., Robertson, R. E., Karahalios, K., Wilson, C., Hancock, J., & Sandvig, C. (2021). Auditing algorithms: Understanding algorithmic systems from the outside in. Foundations and Trends® in Human–Computer Interaction, 14(4), 272-344.
Mohamed, M. I. (2022). Effects of Credit Risk Rating on the Firm Value of Listed Commercial Banks in Kenya KeMU].
Neale, B. (2021). The craft of qualitative longitudinal research: the craft of researching lives through time. Sage.
Nukala, V. B., & Prasada Rao, S. (2021). Role of debt-to-equity ratio in project investment valuation, assessing risk and return in capital markets. Future Business Journal, 7(1), 13.
Peng, X., & Huang, H. (2020). Fuzzy decision making method based on CoCoSo with critic for financial risk evaluation. Technological and Economic Development of Economy, 26(4), 695-724.
Phan, D., Joshi, M., & Mascitelli, B. (2018). What influences the willingness of Vietnamese accountants to adopt International Financial Reporting Standards (IFRS) by 2025? Asian Review of Accounting, 26(2), 225-247.
Platonova, E., Asutay, M., Dixon, R., & Mohammad, S. (2018). The impact of corporate social responsibility disclosure on financial performance: Evidence from the GCC Islamic banking sector. Journal of Business Ethics, 151, 451-471.
Stephany, F., Stoehr, N., Darius, P., Neuhäuser, L., Teutloff, O., & Braesemann, F. (2020). The CoRisk-Index: A data-mining approach to identify industry-specific risk assessments related to COVID-19 in real-time. arXiv preprint arXiv:2003.12432.
Swanepoel, M. (2018). The development of an integrated financial decision-making model using making model using lean accounting North-West University].
Urdes, L., Simion, V.-E., Talaghir, L.-G., & Mindrescu, V. (2022). An Integrative Approach to Healthy Social-Ecological System to Support Increased Resilience of Resource Management in Food-Producing Systems. Sustainability, 14(22), 14830.
Washburne, A. D., Morton, J. T., Sanders, J., McDonald, D., Zhu, Q., Oliverio, A. M., & Knight, R. (2018). Methods for phylogenetic analysis of microbiome data. Nature microbiology, 3(6), 652-661.
Weygandt, J. J., Kimmel, P. D., & Kieso, D. E. (2018). Financial accounting with international financial reporting standards. John Wiley & Sons.
Winsemius, H. C., Jongman, B., Veldkamp, T. I., Hallegatte, S., Bangalore, M., & Ward, P. J. (2018). Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts. Environment and Development Economics, 23(3), 328-348.
Xing, F. Z., Cambria, E., & Welsch, R. E. (2018). Natural language based financial forecasting: a survey. Artificial Intelligence Review, 50(1), 49-73.
Zhang, Z., Luo, M., Hu, Z., & Niu, H. (2022). Textual emotional tone and financial crisis identification in Chinese companies: a multi-source data analysis based on machine learning. Applied Sciences, 12(13), 6662.
Zio, E. (2018). The future of risk assessment. Reliability Engineering & System Safety, 177, 176-190.
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