Responsibility Reports, Large Financial NER, Financial Items Classification, Sentiment Analysis, News Briefing and much more!
Finance NLP 1.9 comes with a lot of new capabilities added to the 135+ models and 25+ Language Models already available in previous versions of the library. Let’s take a look at each of them!
Responsibility Reports
Extract up to 20 quantifiable entities, including KPI, from Responsibility and ESG Reports of companies.
Check our latest article about how to automatically process Responsibility Reports with Finance and Visual NLP here.
Improved large Financial NER
Extract up to 40 entities from financial texts, now improved with different document types, including 10K, 10Q filings, Broker Reports and Earning Calls.
Understand Increased / Decreased amounts and percentages
With our new Assertion Model, you can analyze the context of amounts and percentages and understand if they are mentioned to have been increased or decreased.
Reuters and CNBC Financial News Briefing
Analyze financial news from Reuters, WSJ, CNBC, etc. and get a brief of them, using T5 Transformers.
Financial Sentiment Analysis on Trade Tweets
Analyze tweets about Trading activities of companies and infer sentiment (positive, negative, neutral actions).
Clovis Oncology downgraded to in line from outperform at Evercore ISI
Result:😟Autodesk stock price target raised to $162 from $149 at Wedbush
Result:😀
Improved Financial Deidentification
Financial Deidentification models and pipelines got their accuracy improved.
Check the new 2 notebooks available at Finance NLP Workshop.
Detect signers in Financial Reports
Detect signers section and extract PARTY, SIGNER_PERSON and SIGNER_TITLE from Financial texts.
Negation Detection Demo
We created a Streamlit app to showcase how you can use our Assertion Status models to Understand Negation in context.
Topic Classification
Identify the topic of a financial text from a series of predefined ones, including DIVIDENDS, COMPANY NEWS, PRODUCT NEWS, TREASURIES, DIVIDENDS, EARNINGS, STOCKS, IPO
and many others!
Item / Section Classification of 10K Reports
Identify sections in 10K reports, including Items 1, 2, 3, 7, 7A, 8, 9A, 9B, 10–15.
Revamped Databricks notebooks
If you are a user of Databricks, you will find a series of notebooks improved and revamped for your environment here.
Fancy trying?
We’ve got 30-days free licenses for you with technical support from our financial team of technical and SME. This trial includes complete access to more than 135 models, including Classification, NER, Relation Extraction, Similarity Search, Summarization, Sentiment Analysis, Question Answering, etc. and 25+ financial language models.
Just go to https://www.johnsnowlabs.com/install/ and follow the instructions!
Don’t foger to check our notebooks and demos.
How to run
Finance NLP is very easy to run on both clusters and driver-only environments using johnsnowlabs
library:
!pip install johnsnowlabs
nlp.install(force_browser=True)
nlp.start()