You are an ML engineer at a bank where you have implemented a binary classification model using Google Cloud AutoML Tables. The model predicts whether a customer will make loan payments on time, and this prediction is used to approve or reject loan requests. Recently, the model rejected a loan request for a customer, and now the bank's risk department wants to understand the reasons behind this specific decision. What approach should you take to provide an explanation for the model's decision?