In the era of digital recruitment resume screening is the crucial step if it is not done properly will lead to Fake extracted resumes and HR managers uses the key word based application tracking system and rule based filtering tools to overcome the challenges and speedup and reducing the cost effective the recruitment process and accurately and detecting important information by using natural language processing that fits for job description and identifying the fraud information in the resume by providing the credibility scoring this project uses the uses the combination of the machine learning and natural language processing framework for Resume Authenticity Assessment and Credibility Scoring our system integrate the BERT transformer architecture and word embedding techniques and AI-generation detection and email automation.and scores in ascending order Federated training for privacy and secure resume and to avoid the human error to train models using resumes data set this can be processed through ensemble classifier SHAP Explainability and this output gives the credibility score and a gives the specific skill mismatch under 10 to 15 seconds fastly scalable integration into ATS for cost-effective, equitable hiring.