CreditRiskMonitor Announces Third Quarter Results

VALLEY COTTAGE, NY / ACCESSWIRE / November 14, 2024 / CreditRiskMonitor.com, Inc. (OTCQX:CRMZ) reported operating revenues of $5.0 million, an increase of approximately $217 thousand or 5%, for the third quarter of fiscal 2024 compared to the same period of fiscal 2023. The Company reported pre-tax income of approximately $716 thousand, an increase of approximately $222 thousand, for the third quarter of fiscal 2024 compared to the same period of fiscal 2023. The increase in pre-tax profitability was primarily driven by decreased salary and related expenses, lower customer acquisition costs, and an increase in interest income.

Mike Flum, CEO, said, "We continue our optimization initiatives to achieve higher efficiency for our teams. While our operating results have improved quarter over quarter, we still expect lower profitability in the short-to-medium term as we increase spending for data, technology, and employee upskilling. We expect these investments will support higher revenue growth and higher profitability in the long term.

Our Confidential Financial Statements Solution continues to receive positive feedback from prospects and customers as it gains momentum. We are making minor tweaks to the process based on user input as we refine product market fit. The add-on helps to address the private company coverage problem without resorting to the firmographic/technographic models used in thin file situations, which we feel provide a false sense of security.

We also continue to gain new clients for our SupplyChainMonitor platform and were excited to be rated as a top provider of financial risk analytics for supply chain risk management and third-party risk management by Spend Matters in their Fall 2024 SolutionMap rankings. There is a clear need for financial risk analysis in supply chain management and the movement from one-time onboarding checks to more robust continuous monitoring supports our value proposition.

Finally, we are working to improve our news systems with new natural language techniques to support better content tagging, fewer duplicated stories, and clear materiality to our subscribers. These steps will further support extracting more useful signals from news, improving our reports and counterparty relationship identification. Ultimately, this data will aid our long-term ambitions to offer lower-cost digital twin models leveraging our analytics to surface financial risk contagions within n-tier supply chains.