Persistent Systems has launched a Merchant Risk Management and Fraud Detection solution powered by the Databricks Data Intelligence platform to help financial institutions reduce fraud losses and lower manual review effort through real-time intelligence. The solution targets banks, acquirers, payment service providers and digital platforms as digital payments scale. Persistent said the approach shifts merchant risk management upstream to enable early detection, continuous monitoring and AI driven action. Built on Databricks, the solution uses agentic AI for multi-signal vetting during onboarding by analysing business profiles, compliance history, transaction patterns and external indicators to assess risk before transactions begin. Once live it continuously monitors transactions, chargebacks and third party signals in real time to detect emerging fraud or compliance risks and triggers configurable actions such as enhanced monitoring, watch listing or transaction restrictions with auditability and governance. Designed as a Databricks accelerator, it unifies batch and streaming data, merchant profiles and external risk signals into a governed real-time intelligence layer to speed time to value. The company expects 20 to 40 per cent reduction in chargeback and fraud losses, 30 to 60 per cent improvement in detection accuracy, 50 to 70 per cent reduction in manual review effort and 10 to 20 per cent lower risk management costs through automation. Persistent is a Databricks Global Systems Integrator partner with 900 plus Databricks certified professionals and more than eight accelerators on the platform. The solution is available now and can be deployed for banks, acquirers and payment service providers globally. Persistent's Global BFSI and Europe Geo head said merchant risk has become more complex and that working with Databricks combines scalable data processing with AI to identify emerging risk earlier, while the Databricks lead said the collaboration helps unify data at scale for real time visibility and resilient compliance.