mlsanityData to 14 Oct 2026

FiNCAT: Financial Numeral Claim Analysis Tool

arXiv 2202.00631 ↗First posted 26 Jan 2022q-fin.GN cs.CLcited by 0

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Abstract (arXiv)

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

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 26 Jan 2022.

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References · 3

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166

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