Our project focuses on enhancing the mortgage loan approval process at banks by integrating an AI-based objective decision-making layer. We began by collecting and structuring over 50,000 datapoints relevant to mortgage applications. This comprehensive dataset underwent extensive data exploration and analysis to uncover patterns and insights critical to the lending decision process. 

Using these insights, we developed an AI model designed to augment current decision-making frameworks with precision and fairness. To make the AI's decisions transparent and explainable, we created a detailed dashboard that visualizes the decision-making process. This dashboard highlights the weights assigned to each parameter, ensuring that users can see how various factors influence the AI's recommendations. 

Furthermore, to maximize the utility of our data, we incorporated a Large Language Model (LLM). This easier to extract meaningful insights and make informed decisions. The integration of LLM ensures that the wealth of data can be accessed and utilized efficiently, facilitating a deeper understanding and better-informed decision-making process. 

Overall, our project not only streamlines and enhances the mortgage approval process but also ensures transparency, fairness, and ease of use, paving the way for more reliable and equitable lending practices.