AI can automate the credit decision process, making it more efficient and accurate by predicting loan approval or denial based on historical data. Machine learning algorithms can identify patterns and trends in the data that would otherwise take a significant amount of time for human underwriters to notice. However, AI's accuracy relies on having a clean and diverse dataset. Deep learning is a subfield of machine learning that uses neural networks to replicate pattern recognition abilities of the human brain, building more accurate predictive models and improving machine learning algorithms' performance. A neural network consists of interconnected units called neurons, which process and transmit information, using weights to control the strength of connections between them. Classification is a supervised machine learning task where the goal is to predict class labels based on input data, with binary classification being used in this case to solve the task of predicting loan approval or denial.