How Moody's Gen AI Tool Cuts Financial Analysis Time by 30%

Credit ratings provider Moody's reports its artificial intelligence (AI) platform is driving efficiency gains across financial services firms, with users processing up to 60% more research while reducing task completion times by 30%.

The Research Assistant platform, which uses generative artificial intelligence (AI systems that can create new content based on training data), has logged more than 100,000 user interactions since its December 2023 launch, according to internal usage data from the company.

The platform's integration of AI capabilities has enabled investment bankers, portfolio managers and research teams to discover more relevant content for strategic decisions, Moody's says.

Rapid adoption across sectors

The system saw a 300% increase in recurring users during its second quarter in market, with financial institutions implementing the technology within months rather than the years typically required for enterprise software deployment.

Analysis shows 90% of interactions focus on three core areas: thematic research and strategic portfolio adjustments at 39%, detailed financial analysis at 32%, and initial screening for new opportunities at 20%.

The platform integrates Retrieval Augmented Generation (RAG), a technique that allows AI models to access and reference external data sources, to maintain accuracy in decision-making processes. 

This addresses regulatory requirements around personally identifiable information and decision auditability.

Cristina Pieretti, General Manager of Moody's View and GenAI Solutions, says the platform's impact spans multiple roles. 

“Users of the platform had a remarkable 60% peak in research readership, with a sustained increase of 35% more data and insights analysed to inform their decisions.”

Transforming financial workflows

The technology enables investment bankers to synthesise market trends and competitor analysis in minutes rather than hours, according to the company. 

Portfolio managers can process extensive datasets across multiple sectors, while rating advisors use the system to assess creditworthiness by analysing financial metrics alongside market conditions.

Corporate bankers are enhancing client relationship management through rapid access to company analysis and sector performance metrics, while credit analysts can now analyse multiple risk factors simultaneously, including financial statements, market conditions and industry trends.

The platform has shown particular benefits for junior professionals, who can now contribute to complex analyses earlier in their careers by spending less time on data gathering, Moody's says. 

This has led to standardised output quality across organisations by embedding institutional knowledge directly into analytical workflows.

Future developments

Moody's says it is developing AI agents - autonomous systems that can execute complex workflows with minimal human intervention. 

These agents will combine access to proprietary databases, analytical engines and curated newsfeeds to produce comprehensive company analyses.

The company plans to launch specialised AI assistants for specific use cases. 

The technology aims to reduce credit memo production time by more than half through automated data gathering and standardised report generation. 

For M&A activities, tools will screen companies based on financial metrics, market position and industry dynamics to identify potential deals.

Implementation requires careful navigation of regulatory requirements, particularly for applications handling sensitive data or influencing material decisions. 

Financial institutions must maintain transparency through documentation of model decisions and validation processes, according to Moody's.

“To realise the potential and achieve successful implementations and ROI, strong C-suite alignment and clear business goals are crucial,” says Dimitrios Papanastasiou, Head of GenAI Practice at Moody's.

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