  While making investment decisions by reading financial documents, investors
need to differentiate between in-claim and outof-claim numerals. In this paper,
we present a tool which does it automatically. It extracts context embeddings
of the numerals using one of the transformer based pre-trained language model
called BERT. After this, it uses a Logistic Regression based model to detect
whether the numerals is in-claim or out-of-claim. We use FinNum-3 (English)
dataset to train our model. After conducting rigorous experiments we achieve a
Macro F1 score of 0.8223 on the validation set. We have open-sourced this tool
and it can be accessed from
https://github.com/sohomghosh/FiNCAT_Financial_Numeral_Claim_Analysis_Tool
