Performance Evaluation
Use metrics such as precision, recall, F1-score, and AUC-ROC to assess the model’s effectiveness in predicting credit risk.
Validation and Deployment
Collaborate with financial institutions to validate the system’s outputs and deploy it in real-world scenarios for practical testing.
Expected Outcomes.
This research aims to demonstrate that fine-tuning GPT-4 can significantly enhance its ability to perform multi-dimensional credit risk assessments. The outcomes will contribute to a deeper understanding of how advanced AI models can be adapted for financial applications. Additionally, the study will highlight the societal impact of AI in improving financial inclusion, reducing default risks, and advancing the field of credit risk management.