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Researches for Natural Language Processing for Financial Domain

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awesome-financial-nlp

Researches for Natural Language Processing for Financial Domain.

Financial Applications of NLP

Text data is one of the important resources for the financial domain. For example, we read the news when buying stock and we evaluate the plan when providing finance. In the past, the volume and velocity of textual data were manageable enough to be manually analyzed by teams of human experts but recent growth is intractable. Recent progress of NLP techniques helps this situation and it will reveal how the experts determine various judgements.

Application

  • Market Analysis: Apply classification/clustering method to analyze market.
    • Micro: Stock price prediction etc
    • Macro: Unravel market movement
  • Risk Management: Apply classification method etc to detect fraud or money laundering.
  • Compliance: Apply various NLP methods to verify compatibility to internal investment/loan rule.
  • Asset Management: Apply various NLP methods to organize unstructured documents etc.
    • Internal: Utilize internal documents.
    • External: Utilize internal documents like SNS etc.
  • Customer Engagement: Apply Question Answering, Dialog etc to communicate with customer.

Classification

Sentiment Analysis

Clustering (Unsupervised Classification)

Question Answering/Dialog

Knowledge Extraction

Event extraction

Relation Extraction

Workshops

  • ECONLP: Economics and Natural Language
  • FNLP: Financial Narrative Processing
  • FinNLP & FinSDB:
  • KDF: Knowledge Discovery from Unstructured Data in Financial Services
  • Robust AI in FS
  • ADF: Anomaly Detection in Finance

Dataset

Reference