LSEG MarketPsych NLP Engine

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LSEG MarketPsych NLP Engine

An NLP-as-a-service platform for financial text analytics

The LSEG MarketPsych’s NLP Engine is an NLP-as-a-service platform for financial analytics. The NLP Engine was developed to rapidly process large volumes of unstructured text from financial sources, including news, social media, filings, transcripts, and brokerage research. Clients use the NLP Engine to generate standardized insights from their unstructured text.

The NLP Engine identifies and tags millions of entities, thousands of topics and events, and categorizes financial, ESG, and commodities sentiment. The NLP Engine can be deployed on premises or in the cloud.

Applications

Real-Time Nowcasting

Feed real-time text data into our system to receive instant insights, enabling you to make informed decisions quickly.

Research Capabilities

Efficiently navigate through extensive libraries of documents to identify key relationships between entities, market trends, and thematic developments.

Risk Identification

Automate detecting and monitoring risks within textual data. Perform KYC and monitor negative news with over 300 risk-related topics and events flagged for millions of entities.

ESG Insights

With coverage of over 200 ESG topics and a sentiment analysis model fine-tuned for ESG discourse, gain nuanced insights from ESG reports.

Customer Insight and Engagement

Understand client preferences and concerns regarding your financial products and services.

Market Sentiment Analysis

Input real-time news, analyst reports, and social media feeds to gauge market sentiment.

Regulatory Monitoring

Analyze regulatory changes with automated monitoring of regulatory texts.

Fraud Detection and Prevention

Enhance your fraud detection capabilities by analyzing transaction narratives, communication patterns, and reports.

Key Features

Entity Recognition

The NLP Engine’s AI-driven Named Entity Recognition (NER) system tags over 20 entity types, including companies, products, currencies, bonds, ETFs, commodities, and places. It additionally links over 130,000 of those entities to LSEG’s PermID for seamless data integration.

Apple Org (PermID: 4295905573) announces new

iPhone Product in California Region

Topic and Event Insights

The NLP Engine covers an extensive profile of 1,000+ topics and 4,000+ events across categories such as finance, environmental issues, politics, law, and technology. Topics are organized in a hierarchical taxonomy for easy navigation.

BYD’s new electric model Topic: EV will be unveiled

Event: EV-Launch in August

Sentiment and Emotion Analysis

Leveraging three fine-tuned classifiers, the NLP Engine quantifies the sentiment and emotional undertones in text, offering insights into market sentiment, ESG considerations, and commodity market dynamics, along with a spectrum of 10 emotional tones.

Sony’s earnings beat analyst expectations.

Financial sentiment: +98%

Analysts are dissatisfied with the company’s progress toward climate targets.

Disappointment: +26%, ESG sentiment: -98%

Figure: Aggregated product sentiment using NLP Engine output

Output and Accessibility

The NLP Engine outputs its analytics in JSON format, ensuring compatibility and ease of integration with existing systems. The output provides detailed, sentence-by-sentence insights.

Figure: Depiction of NLP Engine’s JSON output

Figure: Installation Workflow

NLP Engine is available for deployment in multiple environments: on-premises, cloud-based, and via API. MarketPsych’s tech team provides hosting advice, retrieval, and visualization guidance for the detailed analytics.

Getting Started

For those interested in integrating NLP Engine into their workflow, MarketPsych offers detailed support and a complimentary trial for institutions seeking to leverage NLP Engine’s analytical power.

For further information or to arrange a demonstration, please contact[email protected]