Globally, teams in risk, procurement, and compliance are under pressure to manage geopolitical risks and business risks. Third-party risks are impacted by the complexity of domestic and international businesses, as well as complex and diverse regulations. It is crucial that companies proactively manage third-party relationships. This cutting-edge platform, powered by D&B Data Cloud's 520M+ Global Business Records with 2B+ annual updates for third-party risks, is an AI-powered solution that mitigates and monitors counterparty risk on a continual basis. D&B Risk Analytics uses best-in class risk data, including alerts for high-risk purchases and match points of more than a billion. This helps to drive informed decisions. Intelligent workflows allow for quick and thorough screening. Receive alerts on key business indicators.
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Dun & Bradstreet’s ChatD&B offers a powerful, AI-driven chat interface that simplifies how organizations research and assess companies. Instead of traditional complex filtering, users interact naturally by asking questions in their own words to receive tailored insights such as company financials, risk scores, and market data. The platform taps into the vast Dun & Bradstreet Data Cloud to deliver real-time, reliable information that supports smarter, faster business decisions. Enhanced features include visibility into the data sources behind results, chat history for audit trails, and quick answers to product-related queries. ChatD&B is designed to optimize workflows across sales, finance, and risk management by providing instant access to trusted company data. It helps teams discover new opportunities, evaluate customers, and make confident decisions all through easy chat conversations. The platform also enables better compliance and verification by allowing users to track and reference past interactions. With ChatD&B, organizations can accelerate growth and reduce operational friction.
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Aiera
Empowering investment professionals with instant access to live audio, real-time transcription, advanced search capabilities, and comprehensive summarization, this solution stands out as the most precise tool for transforming streaming events and real-time data into valuable insights. It enhances productivity by providing insights from earnings calls, regulatory filings, conference presentations, macroeconomic events, and various imported documents. Users can engage with a live transcription that boasts a remarkable accuracy of 97% and a delay of under 0.5 seconds. During live events, features such as pause, rewind, and adjustable playback speed allow for greater control over the viewing experience. Additionally, the ability to stream multiple events at once and search across them eliminates the need to choose between options. It also enables users to conduct searches within transcripts, save specific search terms to monitor trends over time, and receive alerts for new matches. Furthermore, the system automatically identifies relevant insights across events, including topic extraction, sentiment analysis, and price tracking, ensuring that investment professionals remain informed and ahead of the curve. This holistic approach to data processing and insight generation truly revolutionizes how investment professionals engage with live events and data streams.
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Azure Text Analytics
Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.
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