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The novel Coronavirus has upended global industries and economies. Decision makers require access to comprehensive and timely information on emerging risks for the sectors they monitor. Coronavirus Pulse is a machine learning-enabled tool that prioritizes real-time news stories related to COVID-19 based on sentiment.
- Track and prioritize real time news from global news providers and sources allowing users to identify risk and emerging themes.
- Filter news articles by sector, entity, region, publication date and adversity level to assess sentiment on your credits.
- Enhance your surveillance workflows through an interface that was built to rapidly funnel required news data based on client requirements.
- Leverage Moody’s Analytics Credit Sentiment Score, a rating for negative credit sentiment of a news article embedded in the platform.
- Identify and surface top entities, sectors or themes in Coronavirus news.
- Gain a 360-degree view on emerging risks by benefiting from accurate, timely and transparent data.
- Identify news articles related to COVID-19, tag each company mentioned, and surface sector-specific themes and events using machine learning (ML) and natural language processing (NLP).
- Determine overall sentiment through the ML algorithms which read each article in its entirety and assign it to one of three categories: adverse, neutral, or positive.
- Benefit from Moody’s Analytics Credit Sentiment Score™ solution which uses state-of-the-art AI techniques such as natural language processing, text analytics, and machine learning to derive credit-relevant sentiment from news articles.
- Gain efficiencies in early warning and monitoring processes. Where existing quantitative measures are available, the Credit Sentiment Score solution works in tandem, helping to explain sharp increases in risk measures.
Credit analysts have always used news to help understand and monitor their borrowers. But news volume has exploded in recent years, leaving many organizations complaining of information overload. Today, stakeholders can use artificial intelligence (AI) methods to help identify which articles are worth reading and why. This option frees up time for deeper investigations and allows more names to be monitored.