Miracle Pay enables crypto payments at point-of-sale

The move into point-of-sale represents a critical step for crypto adoption, targeting a market where 39% of U.S. merchants now accept digital assets. For merchants already accepting crypto, these sales account for over a quarter of their total sales, with 72% reporting growth in these transactions over the past year. This adoption is most potent among large enterprises with over $500 million in revenue, 50% of which already accept crypto payments. For SaaS platforms, this signals a broader trend: the monetization of payments through embedded finance. By integrating financial services directly, platforms can increase revenue per user, enhance customer retention, and create a stickier product ecosystem. This strategy shifts payments from a cost center to a significant revenue driver, with PayFac-as-a-Service (PFaaS) models allowing platforms to launch branded payment experiences in weeks without the regulatory overhead of becoming a full payment facilitator. The underlying technology is also rapidly advancing, with a clear enterprise shift toward real-time payments and settlement. Over 70 countries now have instant payment systems, and this is becoming an expectation for cross-border transactions, which are projected to reach $290 trillion by 2030. Blockchain and stablecoins are key to this, enabling near-instant settlements and reducing the complexities of traditional international transfers. To manage this complexity, payment orchestration has become essential infrastructure for scaling platforms. Orchestration layers intelligently route transactions across multiple processors to optimize approval rates, which can increase by 5-10%, and reduce processing costs. This is critical for platforms expanding globally, as it simplifies the integration of local payment methods and manages the intricacies of cross-border commerce. AI is further accelerating this evolution by transforming payment routing and fraud detection. AI-driven systems analyze vast datasets in real-time to select the most efficient and secure path for each transaction, a process that was previously manual and far less effective. In fraud prevention, machine learning models detect anomalies and sophisticated threats that rules-based systems miss, which is crucial as 77% of customers now expect AI-driven fraud prevention. For enterprise sales leaders, the conversation is shifting from price to total enterprise value. Instead of focusing solely on discounts, sophisticated negotiations now involve a range of commercial levers, including multi-year terms, payment timing, and implementation scope. Adopting a value-based approach, where the solution's ROI is clearly quantified, allows for collaborative negotiations that build long-term partnerships rather than transactional relationships.