FiNCAT: Financial Numeral Claim Analysis Tool
This tool addresses a specific need for investors by automating numeral claim analysis in financial texts, but it is incremental as it applies existing methods to a new domain.
The paper tackles the problem of automatically differentiating between in-claim and out-of-claim numerals in financial documents to aid investment decisions, achieving a Macro F1 score of 0.8223 on a validation set using the FinNum-3 dataset.
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