Automated Anomaly Detection in Financial Statements Using AI

We are a burgeoning startup in the Accounting & Auditing industry focused on revolutionizing financial analysis and audit processes through AI-driven solutions. Our current challenge is the manual, time-consuming process of identifying errors and anomalies in financial statements, which often leads to oversight and inefficiencies. By implementing an AI-based system using technologies such as OpenAI API, TensorFlow, and PyTorch, we aim to automate and streamline these processes. The project involves developing a robust anomaly detection model that uses Large Language Models (LLMs) and Natural Language Processing (NLP) to analyze textual and numerical data, predict potential errors, and generate comprehensive reports. This tool will serve as a transformative solution for auditors, enabling them to focus more on strategic analysis rather than manual data checks. Potential freelancers should possess experience in predictive analytics and familiarity with frameworks like Hugging Face and Langchain for NLP tasks, as well as YOLO for any necessary computer vision components.