Persistent Systems Launches Merchant Risk Management Solution Powered by Databricks AI

Persistent Systems Launches Merchant Risk Management Solution Powered by Databricks AI

Persistent Systems Launches Merchant Risk Management Solution Powered by Databricks AI​

Persistent Systems, a global Digital Engineering and Enterprise Modernization leader, has launched its Merchant Risk Management and Fraud Detection solution, which is powered by the Databricks Data Intelligence platform. The solution aims to assist financial institutions in reducing fraud losses, improving detection accuracy, and lowering manual review efforts through real-time, intelligence-driven decision-making.

As digital payments expand, financial institutions, payment service providers, digital platforms, and their end customers are facing escalating fraud, regulatory scrutiny, and reputational risk. The solution addresses the limitations of traditional approaches that rely on static rules and post-transaction analysis, enabling a shift to upstream merchant risk management for early detection and continuous monitoring.

Built on the Databricks Data Intelligence platform, the system utilizes Agentic AI to vet merchants during onboarding. It analyzes various data points including business profiles, compliance history, transaction patterns, and external indicators to assess risk before any transactions occur. Once a merchant is live, the solution continuously monitors transactions, chargebacks, and third-party signals in real time to identify emerging fraud or compliance risks.

When risk signals are detected, the system can trigger configurable actions such as enhanced monitoring, placing a merchant on a watch list, or imposing transaction restrictions, all with full auditability and governance. The design serves as a Databricks accelerator, unifying both batch and streaming data streams with merchant profiles and external risk signals, creating a governed, real-time intelligence layer.

The solution is available now and can be deployed as a Databricks-based accelerator for banks, acquirers, and payment service providers globally.

Key expected business impacts highlighted for the solution include:

MetricProjected Improvement/Reduction
Chargeback and fraud losses20 - 40% reduction through earlier risk detection
Fraud detection accuracy30 - 60% improvement using multi-signal intelligence
Manual review effort50 - 70% reduction, freeing teams for higher-value investigations
Risk management costs10 - 20% reduction through automation and streamlined workflows

Barath Narayanan, Global BFSI and Europe Geo Head at Persistent, noted that effective risk management now requires transforming data into intelligence and responding in real time, a capability enabled by combining scalable data processing with AI.

Josh Meyer, Global Head of Partner Solutions and Industry GTM at Databricks, stated that this intelligence-driven challenge in merchant risk management is best addressed by unifying data at scale to gain real-time visibility across the merchant lifecycle, leading to earlier risk detection and stronger compliance.

Persistent Systems is a Databricks Global Systems Integrator partner, maintaining over 900 Databricks certified professionals and more than eight accelerators on the Databricks platform.

PERSISTENT Stock Price Movement​

Shares of Persistent Systems Limited are edging higher to ₹5407 as of 12:34 PM, posting a gain of 0.62% in live trading. The stock sees robust activity today, with 310,656 shares changing hands in the ongoing market session.

Source:​

 

Disclaimer: Due care and diligence have been taken in compiling and presenting news and market-related content. However, errors or omissions may arise despite such efforts.

The information provided is for general informational purposes only and does not constitute investment advice, a recommendation, or an offer to buy or sell any securities. Readers are advised to rely on their own assessment and judgment and consult appropriate financial advisers, if required, before taking any investment-related decisions.

Any views, opinions, or statements expressed, where applicable, are those of the respective analysts or experts and do not reflect the views of this website. The website has no association with such viewpoints and does not assume any responsibility for them.

Back
Top