Moody’s and Microsoft’s New Partnership Brings “Moody’s CoPilot” and “Microsoft Fabric”
Moody’s and Microsoft made a big strategic partnership announcement in June 2023. The partnership will create enhanced insights into corporate intelligence and risk assessments utilizing Microsoft AI and Moody’s data, analytics, and research. Built on Azure OpenAI Service, Moody’s CoPilot, is being deployed to Moody’s 14,000 global employees, and “will combine Moody’s proprietary data, analytics and research with the latest large language models (LLMs) and Microsoft’s generative AI technology.” In addition, Microsoft and Moody’s will collaborate to deliver data to their shared customers through Microsoft Fabric, a new analytics platform for end-to-end data management.
Scoutbee Announces Generative AI Feature Updates to the Scoutbee Intelligence Platform
In June, supplier intelligence and discovery platform provider, Scoutbee, announced generative AI feature updates to the Scoutbee Intelligence Platform (SIP). “The new features enable companies to analyze and get deep insights into their existing supply base. Using the Scoutbee conversational AI, users can ask smart and strategic questions, such as ‘Where do I have single-source suppliers for a product?’ or ‘Is there an alternative supplier for this product?’ to uncover and address vulnerabilities in their base.” CEO Gregor Stuhler states their chat features are built on top of Scoutbee’s data foundation, which centralizes and organizes companies’ supplier information in a meaningful way.”
Google Cloud’s AML AI
Also in June, Google Cloud launched Anti Money Laundering AI (AML AI), which will help global financial institutions in detecting money laundering. As an alternative to rules-based transaction alerting, AML AI provides a consolidated customer risk score that is generated by machine learning. “The risk score is based on the bank’s data including transactional patterns, network behavior, and Know Your Customer (KYC) data to identify instances and groups of high-risk retail and commercial customers.” The release states money launderers can learn and work around rules-based systems to avoid detection and cites “95% of system-generated alerts turn out to be “false positives” in the first phase of review, with approximately 98% never culminating in a suspicious activity.”