Natural Language Processing for Financial Analysis
Purpose-built for financial analysis, our NLP tools and AI-ready data simplify the extraction of insights from complex, unstructured documents like transcripts and filings.
Transform Text Into Insight
Analyzing textual data from earnings call transcripts, research reports, and other financial documents can be time-consuming and costly. Our NLP-ready datasets eliminate the need for manual data preparation, allowing you to move straight into analysis, enhanced by rich metadata tagging and seamless integration with core datasets like Financials and Estimates.
And with ProntoNLP, our advanced natural language processing platform, you can go even further. Purpose-built for financial analysis and powered by proprietary large language models (LLMs), ProntoNLP transforms unstructured corporate disclosures into structured, actionable intelligence. It identifies and scores key performance indicators (KPIs), monitors both macro and micro risks, and surfaces forward-looking strategic signals in near real-time.
Finance-trained AI. Investment-ready intelligence.
ProntoNLP uses a fine-tuned LLM engine, purpose-built for finance and trained on S&P Global content to extract systematic signals from earnings calls, filings, and other textual documents.
Unlike general AI tools, ProntoNLP is specifically designed for market analysis and financial insights, delivering more accurate, relevant information tailored to investment workflows.
NLP Services
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S&P Global AI Data Portal
The S&P Global AI Data Portal enables you to bring trusted, differentiated data seamlessly into your AI workflows. We provide the data retrieval infrastructure and trusted sources that help bring accuracy wherever you work, with existing integrations across leading AI applications.
Deterministic Retrieval
Deterministic Retrieval provides targeted, API-based access to S&P Global data. The solution doesn’t include any AI-driven reasoning or generation, so customers retain full control over orchestration. Comprising over 35 specialized tools to enable precise retrieval, the solution is ideal for workflows like company research, financial analysis, transcript intelligence, and more.Adaptive Retrieval
Built for complex and open-ended workflows, Adaptive Retrieval builds on the capabilities of Deterministic Retrieval. Employing over 15 agents under the hood, the solution dynamically routes each prompt across the required data sources, generating queries and assembling results. Well-suited for deep research, multi-step analysis, and agent-driven tasks. -
ProntoNLP
ProntoNLP is an advanced natural language processing platform that transforms Filings and Transcripts into actionable intelligence. Leveraging a proprietary large language model, it extracts and scores key performance indicators (KPIs) from corporate disclosures—helping users identify strategic inflection points, validate financial statements, and monitor risks such as inflation or supply chain disruptions. The Transcript Analytics dataset surfaces insights from earnings calls, while the Filings Analytics dataset processes both SEC and non-SEC filings, offering hourly signal updates and low correlation to earnings data, providing fresh, forward-looking perspectives on corporate performance.
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Script Insight
Script Insight is a revolutionary AI-powered tool designed for issuers and their investor relations teams. The tool allows corporate issuers to analyze their earnings call transcripts before their earnings calls take place.
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Document Intelligence on S&P Capital IQ Pro
Document Intelligence brings together multiple GenAI innovations in a singular interface. Users benefit from smart search and the ability to interact with documents using GenAI tools and leverage smart summarization. The solution also provides key phrases that highlight relevant and significant topics within earnings call transcripts and natural language processing (NLP)-derived sentiment scores.
What is Natural Language Processing?
Natural Language Processing (NLP) is a branch of artificial intelligence that enables computers to understand, analyze, and generate human language. By transforming unstructured text such as earnings call transcripts, filings, research reports, and news into structured insights, NLP helps organizations extract information from large volumes of content.
In financial markets, NLP can be used to identify speaker sentiment, track emerging themes, classify events, and uncover signals within text that may support research and decision-making. As the volume of financial content continues to grow, NLP provides a scalable way to analyze language across companies, industries, and markets.
NLP serves as the foundation for many of today's generative AI and large language model applications. S&P Global has invested in NLP technologies for more than a decade, developing machine-readable datasets, analytics, and AI-powered solutions that help users discover insights from financial language at scale.
Insights from NLP algorithms
Webinars
Case Study
An Investment Firm Uses GenAI to Find Market-Moving Insights in Earnings Calls
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About
A buy-side firm sought to enhance its equity research with advanced AI tools to extract deeper insights from earnings calls and filings.
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Challenge
Traditional models and manual reviews were too slow and limited to keep pace with growing volumes of unstructured financial data. The firm needed a faster, more accurate way to detect signals and strategy shifts.
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Solution
The firm adopted ProntoNLP from S&P Global Market Intelligence, a GenAI-powered platform optimized for finance. It delivers structured sentiment, event detection, and thematic insights from transcripts and filings through user-friendly interfaces and data feeds.
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Outcome
With ProntoNLP, the analysts gained access to hourly updates across 110 key topics, streamlined workflows, and more precise signals. This strengthened their research process and gave them a competitive edge in equity investing.
Featured Content
Familiar Signal, New Context The Evolution of Earnings Call Sentiment Analysis from Lexicons to LLMs
Large language models (LLMs) have garnered widespread attention for their ability to understand natural language. Their application in equity investing, however, remains in its infancy due to novelty and cost. This study leverages LLMextracted features from earnings call transcripts and transforms them into actionable stock selection signals.
Hear from the experts in our webinar: Betting on LLM’s Intelligence: How Contextual Understanding Drives Outperformance
This webinar provides a detailed blueprint on how investors can systematically leverage LLM-based transcript features to identify future outperformers.
QRS Alpha Research
Watch our new video to find out how our Generative Al alpha research identifies key behaviors of executives during earings calls that correlate with company performance. By analyzing earings calls, we classified executives into four communication styles based on proactiveness and transparency Proactive & On Topic executives consistently outperform, generating an annualized average of 247 Bps of Alpha, while their Reactive & Off Topic peers underperform with -256 Bps of Alpha. With these insights, you can identity executive communication styles on earnings calls.
Expert Perspectives on NLP in Finance
Liam Hynes is interviewed at the Snowflake Summit on his research “Questioning the Answers: LLMs Enter the Boardroom”, where ProntoNLP and Snowflake Cortex were used to analyze 192,000 earnings calls with LLMs, revealing how executive communication patterns correlate with market performance.
Prof. Ronen Feldman explains how ProntoNLP takes unstructured textual data and finetunes it unto structured data & analytics.
Eghbal Rahimikia from Alliance Manchester Business School presents his academic research on year-specific LLMs for finance, trained on historical data—including S&P Global’s Key Developments—to avoid look-ahead bias and outperform larger models like LLaMA in trading scenarios.
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Textual Data for Natural Language Processing
Our NLP-ready datasets empower you to stay ahead of the market and make informed decisions with confidence.
With our textual data suite, you can access machine-readable transcripts, filings, broker research and proprietary S&P Global credit research in structured formats for NLP analysis, so you can skip the entire process of sourcing, cleansing, and maintaining the data, and jump straight into insightful analysis.