Rainforest Adds PayPal to Checkout

Vertical SaaS platforms are increasingly embedding financial services to boost revenue per customer by 2-5x. This strategy, known as embedded finance, is projected to exceed $7 trillion in U.S. transaction volume by 2026, creating a significant revenue pool beyond core software subscriptions. The playbook was written by platforms like Shopify and Toast. Shopify's "merchant solutions," including Shopify Payments, now constitute the majority of its revenue, generating $7.06 billion in 2023. Similarly, Toast, a restaurant-focused platform, achieved its first full year of profitability in 2024 and saw its annualized recurring revenue cross $2 billion in 2025, driven heavily by its fintech solutions. To monetize payments, platforms can become full Payment Facilitators (PayFacs) or adopt a "PayFac-as-a-Service" model. Becoming a full PayFac offers more control but involves significant cost and compliance overhead, whereas hybrid models provide a share of the revenue while a partner manages risk, liability, and operations. Rainforest's model allows platforms to add payments without the burdens of registering as a formal PayFac. As platforms scale, they face increasing complexity in cross-border payments, which are hindered by fragmented regulations, high intermediary bank fees, and slow settlement times. Modern payment platforms are addressing this by consolidating compliance checks and using localized payment rails to simplify the process and improve transparency. The demand for 24/7 availability is driving the adoption of real-time payment (RTP) networks like FedNow and The Clearing House's RTP. These systems offer instant, irrevocable settlement, improving liquidity for merchants. However, they also present challenges, as infrastructure must be capable of handling thousands of transactions per second outside of traditional banking hours. To manage this complexity, AI is being deployed for intelligent payment routing and fraud detection. AI algorithms analyze transactions in real-time to select the optimal payment gateway based on cost and success rates, while machine learning models can spot anomalous patterns to prevent fraud before it happens, often within a 10-50 millisecond window.