AI-Driven Financial Forecasting and Decision Support Systems

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@article{1713728,
      author = {Chidere Amaka Maureen},
      title = {AI-Driven Financial Forecasting and Decision Support Systems},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {7},
      pages = {1642-1648},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1713728.pdf},
      abstract = {This paper explored the paradigm shift of adopting Artificial Intelligence (AI), high-speed cloud systems, and Big Data analytics in financial decision support systems (DSS). The conventional statistical models were no longer effective in real-time prediction as the financial sector experienced growing data complexity and volatility in the markets. The study examined how dynamic, predictive, and prescriptive analytics replaced the traditional, historical data processing. In particular, the paper has looked at the effectiveness of Deep Learning architectures, such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, in processing time-series financial data. Moreover, the study also measured the importance of data warehousing and cloud migration strategies in facilitating real-time scalable stream processing. Findings revealed that although AI-based models were very effective in improving the accuracy of the forecast, especially in the fields of credit risk analysis and algorithmic trading, they also brought considerable difficulties in terms of algorithmic bias, model interpretability (Black Box problems), and data privacy. Hence, this paper proposed a detailed model of aligning AI functions with effective data management to maximize strategic decision-making within the current financial organizations.},
      keywords = {Artificial Intelligence; Financial Forecasting; Machine Learning; Decision Support Systems; Deep Learning; Predictive Analytics; Financial Technology.},
      month = {January},
      doi = {https://doi.org/10.64388/IREV9I7-1713728}
  }