AI APPROACHES TO RECRUITMENT FRAUDIDENTIFICATION
Keywords:
Deep Learning, Online Recruitment Fraud, Fraud Detection, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs)Abstract
Online recruiting fraud has grown to be a serious problem in the contemporary digital age since it affects organizations financially in addition to jeopardizing job searchers' privacy. Many times, the most up-to-date fraud tactics go undetected by traditional fraud detection systems. Because of their superior accuracy in sorting through massive datasets, deep learning algorithms hold great promise as a tool in the battle against false job ads. Several deep learning models, including CNNs, RNNs, and transformers, are being examined in this study with the aim of uncovering unethical labor practices. These techniques enhance the safety of online recruiting platforms and identify dishonest users by using feature extraction and natural language processing (NLP).
