The AI Advantage in Credit Risk and Investment Analysis

In today’s volatile global landscape, shifting geopolitical and macroeconomic conditions necessitate a rigorous and adaptable approach for risk assessment and investment management. Leveraging AI is no longer optional; it is essential to rapidly extract early warning signals, synthesize advanced data analytics, and identify emerging threats to generate actionable intelligence with unparalleled speed.

This session explores best practices for financial professionals integrating AI and proprietary data models to enhance risk and investment workflows across portfolios, sectors, and markets.

Key topics covered:

• How to use RAG models effectively: Delve into the best prompting practices to maximize the value of retrieval-augmented generation (RAG) models for credit risk analysis.

• How to differentiate the value of specialized AI for credit analysis: Explore the value of specialized AI for credit investment decisions compared to open-source models.

• How to extract signals from unstructured text: Learn how AI can surface sentiment, event-driven risks, and thematic indicators across large volumes of unstructured documents to inform faster, more proactive investment decisions.

Speakers

Michelle Cheong

Head of Thought Leadership, Credit Solutions
S&P Global Market Intelligence

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Kathryn Doud

Credit Product Specialist
S&P Global Market Intelligence

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Chirag Patel

Director, Data & Research, Buy-Side
S&P Global Market Intelligence

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