Payments Solving Downstream Finance Pain
The value of embedded payments is shifting to post-transaction workflows. Platforms are now expected to solve downstream accounting pain, with tools like Uncat automating transaction categorization for QuickBooks and Paddle offering audit-ready revenue recognition for SaaS.
Platforms are increasingly expected to become payment facilitators (PayFacs) to monetize transactions, moving beyond simple referral partnerships. This shift allows vertical SaaS companies to increase revenue per user by up to 5x and tap into the 80% of the embedded finance market that remains unrealized. For example, Toast, a restaurant-focused platform, generates the majority of its revenue from financial technology solutions, including transaction-based fees. Shopify's "merchant solutions" segment, primarily payment processing fees, accounted for 73.54% of its total $6.53 billion revenue in 2024. In the first quarter of 2025, Shopify Payments penetration reached 64%, processing $47.5 billion in volume. This strategy of embedding payments is crucial for vertical SaaS companies who risk constrained growth by focusing only on a narrow market. The demand for faster payments is pushing platforms to adopt real-time settlement systems. Unlike traditional batch processing, real-time payments operate 24/7, allowing for immediate fund availability and improved cash flow. Networks like The Clearing House's RTPĀ® can process transactions up to $10 million instantly, with over 1,130 participants as of December 2025. This reduces the friction of delayed bank transfers and paper checks, which can strain a business's cash flow. Cross-border payments introduce complexities like currency conversion, varying regulations, and higher transaction costs. The global cross-border payments market is projected to grow from $212.55 billion in 2024 to $320.73 billion by 2030. Inefficiencies in these transactions are significant, with the rate of straight-through processing for B2B foreign exchange payments at only 26%. AI is being deployed to manage these complexities, with payment systems having roughly 100 milliseconds to score fraud risk and route transactions. AI models analyze large datasets to differentiate between legitimate and suspicious activities, identifying trends a human might miss. This allows for real-time risk scoring, which can identify emerging threats in as little as 30-50 milliseconds. For SaaS CFOs, this evolution in payments brings challenges in revenue recognition under standards like ASC 606. The shift to subscription models with variable fees and contract modifications requires robust financial systems to manage deferred revenue and avoid leakage. CFOs are increasingly adopting automation to handle these complexities and improve forecasting accuracy.