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What is FinBERT
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification.
- Financial Domain TrainingFurther trained on a large financial corpus to understand the unique language and terminology of finance.
- Three-Class SentimentClassifies text into Positive, Negative, or Neutral sentiment with softmax probability outputs.
- Easy IntegrationAvailable via our secure, high-performance API for seamless integration into your applications.
Trusted by the Financial Community
Join thousands using FinBERT for sentiment analysis.
API Requests Processed
10M+
Monthly API calls
Active Subscribers
5k+
Satisfied professionals
Accuracy
89%
On Financial PhraseBank
Choose Your Perfect Plan
Start analyzing financial sentiment today.
Free
Perfect for trying out financial sentiment analysis
Includes
- 3 Analyses per day
- Up to 5,000 characters per request
- High accuracy model
- Basic support
Starter
Best for individualsFor researchers analyzing news, press releases, and partial earnings calls
Includes
- 300 Analyses per day
- Up to 20,000 characters per request
- Analyze news and press releases
- Partial earnings call analysis
- Priority processing
- Email support
Pro
For full transcript workflows, API access, and high-volume teams
Includes
- 2,000 Analyses per day
- Up to 50,000 characters per request
- Supports full earnings call transcripts
- Full transcript comparison
- API access included
- Priority support
What Professionals Say About FinBERT
Hear from financial analysts and developers leveraging FinBERT.
Sarah Chen
Quantitative Analyst
FinBERT has transformed our news analysis workflow. The financial domain understanding is exceptional compared to generic sentiment models.
Michael Park
Fintech Developer
Integration was seamless through the API. We added financial sentiment analysis to our platform in hours.
Emily Rodriguez
Investment Manager
We use FinBERT to process thousands of earnings reports. The sentiment scores help us make better investment decisions.
David Kim
Data Scientist
The softmax outputs give us granular sentiment insights. We've built powerful trading signals on top of FinBERT.
Jessica Williams
Financial Reporter
I use FinBERT to analyze market sentiment from news articles. It's become an essential tool in my research.
Robert Taylor
Portfolio Manager
FinBERT helps us track market sentiment shifts in real-time. It's invaluable for our risk management strategy.
Frequently Asked Questions
Got questions about FinBERT? We have answers.
What is FinBERT?
FinBERT is a pre-trained NLP model specialized for financial sentiment analysis. It is built by further training the BERT language model on a large financial corpus and fine-tuning it for sentiment classification using Financial PhraseBank.
How accurate is FinBERT?
FinBERT achieves high accuracy on financial sentiment tasks, particularly when evaluated on the Financial PhraseBank dataset. Its domain-specific training makes it significantly more accurate than generic sentiment models for financial text.
What type of text can FinBERT analyze?
FinBERT is designed for financial text including news articles, earnings reports, financial statements, analyst reports, and social media posts about financial markets.
How do I integrate FinBERT?
FinBERT is available via our cloud API. You can easily integrate it with just a few lines of code. Check our documentation for detailed examples.
How much does FinBERT cost?
We offer flexible subscription plans tailored to your needs, including a free trial to get you started. Check our pricing page for details.
What sentiment classes does FinBERT predict?
FinBERT classifies text into three sentiment categories: Positive, Negative, and Neutral. It provides softmax probability outputs for all three classes along with an overall sentiment score.
Start Analyzing Financial Sentiment
Join the community of financial professionals and developers leveraging FinBERT for smarter sentiment analysis.
