Optimized Machine Learning Models for Predictive Analysis: AI-Driven Analytical Tools for Enhanced Credit Risk Assessment

@article{1702303,
      author = {Ifeanyi Moses Uzowuru, Olayinka Odutola, Adeyanju Adetoro, Odunuga Atinuoluwadide Moromoke, Prinka Kumari},
      title = {Optimized Machine Learning Models for Predictive Analysis: AI-Driven Analytical Tools for Enhanced Credit Risk Assessment},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {11},
      pages = {321-326},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702303.pdf},
      abstract = {This research explored the optimization of advanced machine learning models for predictive finance, focusing on developing and implementing AI-driven analytical tools to enhance credit risk assessment in the banking sector. By leveraging advanced machine learning optimization techniques, the study aimed to improve the accuracy and efficiency of credit risk models, reduce financial losses, and promote more informed decision-making in banking operations. The research examined various machine learning model optimization strategies, their impact on predictive performance, and the integration of AI-driven tools in real-world banking scenarios.},
      month = {May},
  }