The FinNum Task series aims at better understanding of numeral information in financial narratives. The goal of FinNum-3; on the English data part; is to have a fine-grained manager’s claim detection in the Earning Conference Calls (ECCs) with the help of Natural Language Processing (NLP). To succeed in the best performance for predicting in-claim and out-of-claim numerals, we propose the BERT (Bidirectional Encoder Representations from Transformers) base model , which is pre-trained on a large corpus of English data. The results of our model are 86.48% of macro-F1 score in the validation split and 87.12% of macro-F1 score in the test data.