UNITED STATES OF AMERICA —Prism Data has successfully closed a 20 million USD Series A funding round to accelerate the expansion of its artificial intelligence-driven cash flow underwriting infrastructure. The investment round was spearheaded by Story Ventures, with additional participation from FINTOP, Core VC, Obvious Ventures, and Mana Ventures. This latest injection brings the company’s total capital raised to over 25 million USD, following an initial seed round completed previously.
Prism Data is a financial technology enterprise focused on modernizing credit risk assessment through real-time banking data analysis. The organization develops predictive modeling tools that evaluate the financial behavior of consumers and small businesses, offering an alternative to conventional credit scoring methodologies that often fail to capture comprehensive financial health.
This capital infusion is strategically timed to support the broader integration of advanced transaction categorization within the lending sector. Traditional credit reporting mechanisms frequently overlook nuanced financial behaviors, resulting in significant annual losses from defaults and the systematic exclusion of viable borrowers from mainstream financial services. By analyzing actual cash flow patterns, financial institutions can construct a more accurate risk profile, thereby mitigating default exposure while broadening credit accessibility for historically underserved market segments.
The financial services and banking industries across North America are the primary stakeholders affected by this technological shift. As regulatory environments increasingly emphasize fair lending practices and robust risk management, the adoption of alternative data sources becomes a critical operational imperative. Lenders, fintech platforms, and credit bureaus stand to gain competitive advantages by integrating these sophisticated underwriting tools into their existing decision-making frameworks.
From a strategic market perspective, the deployment of Prism Data’s newly introduced REFRACT engine represents a significant evolution in financial intelligence. This artificial intelligence model, trained on a proprietary dataset exceeding 30 billion bank transactions, enhances the precision of transaction categorization. By accurately distinguishing between income, borrowed funds, and routine transfers, the technology enables lenders to generate highly predictive cash flow scores. Investors and financial executives should monitor this trend as a key indicator of the ongoing transition toward data-centric, AI-enhanced credit underwriting models that promise to redefine risk assessment standards.
