Saurabh Joshi, EVP and President, CSG Forte – Interview Series

Saurabh Joshi is President of CSG Forte, where he is responsible for setting the strategic vision of the organization and for driving product innovation, revenue growth, business development and operational improvements. Mr. Joshi previously served as the Senior Vice President and General Manager for North America at Western Union. Before that, he was Vice President and General Manager for the Home Purchase Business of Better Mortgages, following his role as Global Head of Revenue Planning and Operations at PayPal Inc. Earlier in his career, Mr. Joshi has worked and lived in North America, South America and Asia, where he held a variety of leadership roles at SecondMarket, Rocket Internet and Goldman Sachs.

CSG Forte is part of CSG, a global technology company that provides SaaS platforms for customer engagement, billing, and payments used by enterprises across industries such as telecommunications, financial services, healthcare, and government. Its solutions help organizations manage complex transactions, streamline digital payments, and improve customer experiences across multiple channels.

The company recently launched Payments Protection.ai, an AI-powered fraud detection and financial risk management solution designed to help organizations identify suspicious payment activity, reduce fraud losses, and better manage risk across today’s fast-moving digital payments ecosystem.

You’ve led payments, fintech, and platform businesses at PayPal, Western Union, and now CSG Forte. How did those experiences shape your perspective on where fraud prevention needs to evolve, and what gaps you wanted PaymentsProtection.ai to address?

One pattern has remained constant across all the roles I’ve held: fraud evolves faster than static systems. As digital payments scale, the speed, volume, and complexity of transactions increase, and so does the sophistication of bad actors.

What has become clear is that many fraud tools remain reactive and rely heavily on fixed rules, manual tuning, and siloed data. That creates two risks: either you miss emerging fraud patterns, or you introduce unnecessary friction that impacts legitimate customers.

With PaymentsProtection.ai, we wanted to address the adaptability gap. Fraud detection needs to learn continuously, operate in real time, and adjust thresholds dynamically as behavior changes. In today’s digital payments environment, fraud prevention has to function as an intelligent control system.

Payments fraud has traditionally been treated as a risk or compliance problem. Why do you see it increasingly becoming a revenue and customer-experience issue?

Fraud decisions now define the customer experience as much as pricing or product quality.

In a digital economy, the fraud engine is sitting directly in the checkout path. Declining a legitimate payment doesn’t feel like security to the customer; it feels like failure.

That’s why fraud prevention is no longer just a compliance control, but also a growth lever. The real challenge is protecting against risk while preserving approval rates for legitimate customers and minimizing friction.

What motivated CSG to introduce an AI-native fraud platform now, and how has the payments threat landscape changed over the past few years?

Two structural shifts in the payments landscape make this an important moment.

First, transaction speed has increased. Instant payments, embedded finance, and digital-first commerce are shrinking the window for risk review. We no longer have hours or days for decisions; it must happen in seconds.

Second, as technology continues to evolve, attack methods are becoming more automated and scalable. That increases the need for systems that can adapt continuously rather than rely solely on static rule updates.

At the same time, we saw a clear gap in the market where customers were being forced to stitch together multiple tools to manage payments and fraud, often with limited visibility across systems. Drawing on our deep experience across payments infrastructure, we wanted to become a more comprehensive partner and give customers a simpler, more integrated way to protect transactions while supporting growth. Introducing an AI-native platform reflects the need for faster pattern recognition and dynamic risk calibration, while also helping customers manage payment fraud. We are focused on responding to changes in transaction speed and fraud sophistication.

PaymentsProtection.ai monitors transactions across ACH, cards, and other channels in near real time. Why is cross-channel visibility becoming critical for effective fraud detection?

Fraud thrives in fragmentation.

An individual or entity may exploit ACH return timing, test stolen card credentials, and attempt to take over accounts through digital entry points. If monitoring is isolated by channel, those behaviors can appear unrelated.

Cross-channel visibility helps identify behavioral patterns. That broader context improves detection consistency and reduces blind spots. As payment ecosystems become more multi-rail and multi-channel, unified monitoring becomes increasingly important.

Many fraud systems still rely heavily on static rules. How does an adaptive, learning-based approach change the way fraud teams operate day to day?

Traditional fraud systems often rely on static rules and thresholds that require ongoing manual updates, which creates an operational burden and slow response to new fraud patterns.

PaymentsProtection.ai uses AI-powered decisioning models to monitor transactions and promptly support fraud alerting and intervention. The objective is to reduce false positives while improving detection accuracy, helping businesses maintain both protection and customer experience without slowing processes down.

The platform can be deployed in cloud, on-prem, or hybrid environments. What typically drives those deployment decisions for enterprises handling sensitive payment data?

The platform is a cloud-based architecture powered by AWS and built to support scalability, high availability, and enterprise-grade security, including PCI SSF compliance.

Its cloud-based infrastructure enables the system to analyze high volumes of transactions while maintaining performance and uptime. This supports organizations handling growing digital payment volumes across channels. For sensitive clients, the solution can also be deployed and configured on their on-premise servers or in a hybrid setup, ensuring we meet different customer needs.

With AI increasingly being used by fraudsters as well as defenders, how do you expect the role of AI in payments security to evolve over the next few years?

We’re entering what I would describe as an AI-versus-AI environment.

Fraud is becoming automated, synthetic identities can be generated at scale, and stolen data can be stitched together with generative tools to create convincing profiles. That means traditional, manually tuned rule systems will struggle to keep pace.

Over the next few years, AI in payments security will need to become more adaptive and more contextual. It won’t be enough to only flag anomalies. Rather, systems will need to evaluate patterns across identity, behavior, and transaction velocity, and then respond before losses can occur.

At the same time, there’s the governance piece. As we collect richer behavioral or biometric signals, the responsibility to protect that data increases. The industry will have to balance intelligence with privacy and customer trust.

Different industries face very different fraud patterns. How does PaymentsProtection.ai adapt to vertical-specific risks in sectors like healthcare, telecom, or property management?

The platform is positioned as an industry-tailored solution across verticals, including healthcare, telecom, and property management.

This vertical focus enables configurable thresholds, monitoring indicators, and reporting structures aligned with specific use cases and risk profiles. Fraud patterns and operational workflows differ across industries, and configurability is designed to reflect those nuances.

CSG processes hundreds of millions of transactions annually. How does operating at that scale influence how fraud models are trained, tested, and improved?

CSG processes large volumes of digital payment transactions across industries. Operating at scale provides broad exposure to transaction patterns across ACH, card, and multi-channel environments.

This scale supports continuous monitoring and reporting, helping refine detection strategies and strengthening overall risk management.

The platform’s architecture is built to analyze high transaction volumes per second while maintaining responsiveness and reliability.

Looking ahead, do you see fraud prevention becoming a standalone function or increasingly embedded directly into payment and commerce infrastructure?

The lines between payments, risk, and fraud teams are increasingly converging as payment volumes accelerate and settlement windows shrink. In many organizations, these teams still operate independently, but they’re being asked to make faster, more coordinated decisions than ever before. As a result, we’re seeing fraud prevention increasingly integrated directly into payment workflows.

PaymentsProtection.ai is designed to monitor transactions and enable faster intervention before settlement cut-off times. Additionally, the solution makes it easier for teams to interpret data, tune thresholds, and respond to emerging threats without adding complexity or friction. That positioning reflects the broader shift in payments: protection must seamlessly operate within the transaction lifecycle rather than as a separate, after-the-fact review process.

As digital payments accelerate, fraud detection will increasingly move toward the core infrastructure that processes transactions.

Thank you for the great interview, readers who wish to learn more should visit CSG Forte or their new product Payments Protection.ai.