Key insights
- The author discusses the potential impact of a move to semi-annual reporting on financial data companies like Moody's, FactSet, and S&P. While historical data aggregation revenue may decline, increased reliance on predictive risk models could offset this. The author suggests that the recent valuation compression in these companies presents a long-term buying opportunity, given their potential to adapt to the regulatory change.
The SEC Chair telegraphed this in Sept 2025 but it looks to be taken more seriously today. Question is, how to profit off of the move.
My first thought was that the big financial data companies (Moodys, FactSet and S&P) would be crushed by this due to the cyclical nature they take advantage of. I ran through all three corp's SEC filings and no one mentions this as a headwind in the future.
If you flip the script, moving to less public reporting makes their corporate customers relied on them more. It creates an info vacuum that's owned by the biggest players (including Bloomberg but that's private). The positives are that Moodys and S&P would still need to supply risk analysis and customers would rely on their predictive risk models more than ever.
The downside is that a portion (SEC filings say roughly between 8-15%) of their service is aggregating the historical data to provide to their customer base. This would be slashed in half given this regulatory change. However since all three have predictive and alt models this can be transitioned to focusing on those products.
Given valuations have been compressed (-20% their combined forward P/E avg) from the AI fears in February, it's worth considering this as a long term entrance in financial data analysis.
Data:
- Current Bundled Forward P/E: 24.6 * 5-Year Average Bundled Forward P/E: 30.1 * -.9% below their bundled 5-year Average ROIC