FiNCAT: Financial Numeral Claim Analysis Tool

EasyChair Preprint 7387, version 2

Abstract

While making investment decisions by reading financial documents, investors need to differentiate between in-claim and out-of-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

Keyphrases: Natural Language Processing, financial text processing, numeral claim detection

@booklet{EasyChair:7387,
  author    = {Sohom Ghosh and Sudip Kumar Naskar},
  title     = {FiNCAT: Financial Numeral Claim Analysis Tool},
  howpublished = {EasyChair Preprint 7387},
  year      = {EasyChair, 2022}}