In the world of financial risk assessment, New York based Moody’s is a global powerhouse with a vast wealth of information. Now, thanks to a partnership with Microsoft announced today, Moody’s is bringing the power of generative AI to its enterprise.
Moody’s is using the Microsoft Azure OpenAI service as the engine that helps to unlock research information and risk assessment capabilities. Among the first services to be deployed is Moody’s CoPilot, which is an internal tool that will help the company’s 14,000 global employees more easily query and access data and research with the power of large language models (LLMs).
Looking beyond just AI, Moody’s is also embracing the Microsoft Fabric data management platform — which was announced last month — in a bid to help better manage data for AI and analytics.
“The new generative AI tools will further enhance data and risk management capabilities for our employees and customers,” Nick Reed, CPO at Moody’s, told VentureBeat. “Users will leverage the technology to access tailored risk data and insights drawn from across Moody’s vast body of risk data, analytics and research.”
Generative AI has sparked the interest of many firms across multiple industries including financial services. Just last month, JPMorgan revealed that it has plans for a ChatGPT-like investment service.
Reed commented that Moody’s has long incorporated traditional AI technologies into its solutions to enable the scale and speed to help customers make informed decisions on risk. He noted that Moody’s began evaluating generative AI when it became evident that rapid advances in the technology would help further harness the power of Moody’s proprietary data, analytics and research to help customers and deliver value in new ways and through new channels.
“We believe that generative AI represents a huge opportunity for our customers and our employees to make smarter and more informed decisions,” Reed said.
Reed explained that the Moody’s Copilot combines the company’s corpus of knowledge and opinion with the latest LLMs and Microsoft’s generative AI technology. He added that Moody’s Copilot is currently in its alpha phase, but with the company’s 14,000 employees acting as innovators, his hope is to very rapidly move to beta and beyond — with all answers and use cases grounded by Moody’s proprietary data assets.
“Our vision is that users will seamlessly combine insights on formerly disparate risk areas like credit risk, ESG exposure, and supply chain management,” said Reed. “Risks that Moody’s has a wealth of preexisting data and insights into, but that may have existed in separate silos for our users.”
All of this proprietary information will be combined with the significantly lower barrier to accessing it that comes with generative AI. Reed said that Moody’s customers and employees will be able to query data using the best of language models.
Bill Borden, corporate VP of worldwide financial services at Microsoft, told VentureBeat that Moody’s has had a long standing relationship with Microsoft.
Borden said that Moody’s was looking to benefit from generative AI in a way that integrates with existing processes and could meet the strict security and compliance needs of the company. It’s an approach that is built on a solid foundation at Microsoft.
The move to help support financial service firms with generative AI is an extension of the work that Microsoft has been doing in the sector for a long time, according to Borden. He noted that Microsoft has been working to help financial services firms in their digital transformation journey move to the cloud with a very structured approach. It’s an approach that understands how regulations work in different jurisdictions around the world and has the right controls and governance models in place.
With generative AI, Borden said that Microsoft has a firm foundation with responsible AI, which is part of the platform. He also noted that Copilot services that firms like Moody’s are building for their own enterprise data are built on the same infrastructure that Microsoft uses to build its own suite of Copilot services.
Moody’s isn’t just using Microsoft Azure OpenAI service to build out its generative AI capabilities — it’s also using the recently announced Microsoft Fabric data technology.
Reed said that Microsoft Fabric allows Moody’s users to simplify how they are able to view and analyze data by bringing it all together.
“Moody’s has a vast set of proprietary risk data across areas including credit, ESG, commercial real estate, supply chain and much more,” Reed said. “We are evaluating the full set of possible use cases with Fabric to determine our full course of action.”
The idea of having a data lake is nothing new for a company like Moody’s. Borden said that data lakes are prevalent across banking, capital markets and insurance companies. With Fabric, Borden said the idea is to have an environment that can source data together from multiple sources and provide governance, data catalog and insights.
“Fabric is the integration of our horizontal data platform capabilities,” said Borden. “We’re combining those things together to make it much more consumable for our customers to actually help them with their data strategies.”
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In the world of financial risk assessment, New York based Moody’s is a global powerhouse with a vast wealth of information. Now, thanks to a partnership with Microsoft announced today, Moody’s is bringing the power of generative AI to its enterprise.
Moody’s is using the Microsoft Azure OpenAI service as the engine that helps to unlock research information and risk assessment capabilities. Among the first services to be deployed is Moody’s CoPilot, which is an internal tool that will help the company’s 14,000 global employees more easily query and access data and research with the power of large language models (LLMs).
Looking beyond just AI, Moody’s is also embracing the Microsoft Fabric data management platform — which was announced last month — in a bid to help better manage data for AI and analytics.
“The new generative AI tools will further enhance data and risk management capabilities for our employees and customers,” Nick Reed, CPO at Moody’s, told VentureBeat. “Users will leverage the technology to access tailored risk data and insights drawn from across Moody’s vast body of risk data, analytics and research.”
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Why Moody’s is embracing generative AI now
Generative AI has sparked the interest of many firms across multiple industries including financial services. Just last month, JPMorgan revealed that it has plans for a ChatGPT-like investment service.
Reed commented that Moody’s has long incorporated traditional AI technologies into its solutions to enable the scale and speed to help customers make informed decisions on risk. He noted that Moody’s began evaluating generative AI when it became evident that rapid advances in the technology would help further harness the power of Moody’s proprietary data, analytics and research to help customers and deliver value in new ways and through new channels.
“We believe that generative AI represents a huge opportunity for our customers and our employees to make smarter and more informed decisions,” Reed said.
Combining knowledge and opinion with generative AI
Reed explained that the Moody’s Copilot combines the company’s corpus of knowledge and opinion with the latest LLMs and Microsoft’s generative AI technology. He added that Moody’s Copilot is currently in its alpha phase, but with the company’s 14,000 employees acting as innovators, his hope is to very rapidly move to beta and beyond — with all answers and use cases grounded by Moody’s proprietary data assets.
“Our vision is that users will seamlessly combine insights on formerly disparate risk areas like credit risk, ESG exposure, and supply chain management,” said Reed. “Risks that Moody’s has a wealth of preexisting data and insights into, but that may have existed in separate silos for our users.”
All of this proprietary information will be combined with the significantly lower barrier to accessing it that comes with generative AI. Reed said that Moody’s customers and employees will be able to query data using the best of language models.
Compliance, security and the need for enterprise AI
Bill Borden, corporate VP of worldwide financial services at Microsoft, told VentureBeat that Moody’s has had a long standing relationship with Microsoft.
Borden said that Moody’s was looking to benefit from generative AI in a way that integrates with existing processes and could meet the strict security and compliance needs of the company. It’s an approach that is built on a solid foundation at Microsoft.
The move to help support financial service firms with generative AI is an extension of the work that Microsoft has been doing in the sector for a long time, according to Borden. He noted that Microsoft has been working to help financial services firms in their digital transformation journey move to the cloud with a very structured approach. It’s an approach that understands how regulations work in different jurisdictions around the world and has the right controls and governance models in place.
With generative AI, Borden said that Microsoft has a firm foundation with responsible AI, which is part of the platform. He also noted that Copilot services that firms like Moody’s are building for their own enterprise data are built on the same infrastructure that Microsoft uses to build its own suite of Copilot services.
Why Moody’s is using Microsoft Fabric
Moody’s isn’t just using Microsoft Azure OpenAI service to build out its generative AI capabilities — it’s also using the recently announced Microsoft Fabric data technology.
Reed said that Microsoft Fabric allows Moody’s users to simplify how they are able to view and analyze data by bringing it all together.
“Moody’s has a vast set of proprietary risk data across areas including credit, ESG, commercial real estate, supply chain and much more,” Reed said. “We are evaluating the full set of possible use cases with Fabric to determine our full course of action.”
The idea of having a data lake is nothing new for a company like Moody’s. Borden said that data lakes are prevalent across banking, capital markets and insurance companies. With Fabric, Borden said the idea is to have an environment that can source data together from multiple sources and provide governance, data catalog and insights.
“Fabric is the integration of our horizontal data platform capabilities,” said Borden. “We’re combining those things together to make it much more consumable for our customers to actually help them with their data strategies.”
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Author: Sean Michael Kerner
Source: Venturebeat
