Forensic Accounting in Private Equity: Enhancing Due Diligence and Fraud Detection

This study applies deep learning to forensic accounting in private equity, enhancing due diligence and fraud detection. We developed a neural network combining LSTM and convolutional layers, trained on multi-year financial records and fraud cases. The model incorporates transfer learning and attention mechanisms for interpretability. Synthetic data generation and advanced sampling techniques address class imbalance. Validated on real-world cases, our system shows significant improvement in fraud detection rates and a reduction in false positives compared to traditional methods.