Data-Driven Decision-Making in Corporate Finance: A Review of Predictive Analytics in Profitability and Risk Management

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@article{1705773,
      author = {Olufunmilayo Ogunwole, Ekene Cynthia Onukwulu, Micah Oghale Joel, Ejuma Martha Adaga, Augustine Ifeanyi Ibeh},
      title = {Data-Driven Decision-Making in Corporate Finance: A Review of Predictive Analytics in Profitability and Risk Management},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {7},
      number = {11},
      pages = {772-782},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705773.pdf},
      abstract = {This review paper explores the transformative role of predictive analytics in corporate finance, focusing on its contributions to profitability enhancement and risk management. By leveraging historical data and advanced algorithms, predictive analytics empowers organizations to make informed decisions that drive financial performance. The paper discusses how predictive models facilitate market trend forecasting, identifying profitable customer segments, and optimizing resource allocation. Furthermore, it highlights the application of predictive analytics in risk management, emphasizing its capacity to identify, assess, and mitigate various financial risks, including credit, market, operational, and fraud risks. However, challenges such as data quality, biases, technical complexities, and ethical considerations must be addressed to fully realize the benefits of predictive analytics. The paper concludes with recommendations for organizations to integrate data-driven strategies into their corporate finance practices, fostering a culture of data literacy and continuous improvement. Overall, this review underscores the critical importance of predictive analytics in navigating the complexities of the modern financial landscape.},
      keywords = {Predictive Analytics, Corporate Finance, Profitability, Risk Management, Data Quality, Financial Decision-Making.},
      month = {May},
  }