Reports and statements are crucial for communicating usage data to users, often including sensitive personal information (PII). These documents, distributed electronically or physically, utilize various formats like tables and charts. Data inaccuracies and breaches in these reports lead to significant penalties for organizations. Many organizations outsource report generation, increasing the risk of errors and misdelivery. The problem stems from the handling of PII within these reports. A solution involves using machine learning and visual language models. This technology can detect and correct inaccuracies within the data. The goal is to prevent PII breaches through automated detection and correction. This approach aims to improve data accuracy and security in report generation and distribution. Ultimately, the solution reduces financial and reputational risks associated with data errors.