Language AI Technologies
Turn unstructured text data into meaningful insights
Natural Language Processing (NLP) is revolutionizing financial risk intelligence and investment research. By analyzing vast amounts of unstructured data from news articles, social media, and financial reports, NLP provides timely and valuable insights for optimizing investments and minimizing risks in today's data-driven financial landscape.
Sentiment Analysis
Our sentiment analysis AI model is tailored for assessing the impact of news on investing. By automatically scanning hundreds of thousands of articles per day, it can quickly identify relevant market trends, sentiment shifts, and emerging risks that could impact investment portfolio. Our model accuracy is industry leading on FPB dataset.
Topic Classification
Our topic classification AI model leverages the pretrained large language model, but is fine-tuned to categorise articles accurately into topic labels and scores according to our proprietary taxonomy with systematic and comprehensive coverage related to all external and internal aspects of a company. The taxonomy is also customisable based on client's needs.
Entity Recognition
Our entity recognition AI model automatically identifies and extracts financial entities such as companies, currencies, and securities from unstructured news and financial documents and applies advanced machine learning techniques and domain-specific knowledge to overcome the challenges caused by complexity, variability, and ambiguity of financial texts. This task is critical for accurate financial analysis and risk assessment.
Document Summary
Financial document summary uses machine learning algorithms to automatically read, extract key information, and convert unstructured financial statements and research reports of different formats and from different sources into a unified and structured summary. It can help analysts and investors save time and resources, allowing them to focus on analysis and decision making.