MORN News & Events

Morningstar Credit Analytics announced a new AI integration designed to enable licensed users to access Morningstar Credit Analytics' commercial real estate and commercial mortgage-backed securities data directly within Anthropic's Claude. By integrating via Model Context Protocol, analysts can query live loan- and deal-level data using natural language questions within their AI workflows. As AI interfaces become a primary entry point for financial research, governed access to structured institutional data is becoming critical for professional market participants. Morningstar Credit Analytics' integration aims to bring institutional credit intelligence into AI-enabled research workflows while preserving the data governance and entitlement controls already in place.

Morningstar Credit Analytics launched Corporate Credit Analytics, a new set of tools designed to bring greater transparency and consistency to private credit analysis. The company said, "Corporate Credit Analytics is built to address a growing challenge in private credit analysis: fragmented, non-comparable data, a gap the Financial Stability Board identified in its 2026 private credit report. The platform brings three tools together designed to create consistent, comparable credit analysis: Data Explorer surfaces aggregates of real company financial statements and loan-level data sourced from private company disclosures, rather than public comparables. The data set includes approximately 80 metrics spanning financial statements, debt schedules, covenant thresholds, credit estimates, and key credit ratios including EBITDA to interest expense, debt to EBITDA, cash flow to debt, leverage, and liquidity. Data Overview provides configurable visualizations of trends, ratio distributions, and key performance metrics across private credit rating categories and industries, supporting portfolio insights and effective communication with investment committees and stakeholders. The Credit Estimate Tool generates ratings-aligned credit risk scores for private and limited-disclosure borrowers using methodologies consistent with Morningstar DBRS frameworks. Outputs are mapped to familiar rating categories and benchmarked against aggregated segment statistics by industry, region, and credit quality."

Morningstar and PitchBook announced a new integration with Perplexity that broadens access to Morningstar and PitchBook data, research, and intelligence through Perplexity's AI platform. Through these Model Context Protocol integrations, eligible users can incorporate Morningstar- and PitchBook-backed intelligence directly into their research workflows within Perplexity and Perplexity Computer, where they can move from questions to carrying out multi-step research tasks with trusted context. The experience pairs natural-language search with citation-based responses, drawing on the breadth of Morningstar and PitchBook's analyst-driven investment research across public and private markets. This supports more efficient research by helping investors and financial advisors swiftly find and use trusted information in AI-enabled workflows.

Reports Q1 revenue $644.8M, consensus $626.91M. "In the first quarter, we created significant value, growing operating and adjusted operating income by more than 30%, while reducing shares outstanding by roughly 4% for a total of more than 10% over the past 12 months. On the product front, we introduced new proprietary intellectual property, including PitchBook's daily valuation estimates for venture capital-backed companies and public-market-style research on leading private firms," said Kunal Kapoor, Morningstar's CEO.