Payments fraud management has evolved from a reactive cost center into a strategic growth engine. In a recent webinar hosted by American Banker, Galileo Financial Technologies Senior Director of Global Payments Risk Management, Maxim Spivakovsky, and Director of Fraud Solutions at PwC, Ramiel Mansour, revealed how financial institutions can transform fraud defense into a revenue driver while combating AI-powered threats.

The conversation highlighted a fundamental shift: fraud platforms that reduce friction, enable faster time-to-market, and use adaptive AI don't just stop bad actors—they unlock new revenue streams, improve customer lifetime value, and create competitive differentiation. 

Key Takeaways

• Revenue Impact Over Cost Reduction – Modern fraud strategies deliver ROI by increasing approval rates and reducing fraud cases simultaneously, proving fraud defense directly enables revenue growth.

• AI-Powered Adaptive Architecture – A three-pillar approach (cloud-native infrastructure, real-time data ingestion, continuous learning models) lets institutions detect and prevent AI-driven threats that evolve faster than traditional rule-based systems.

• Friction Costs More Than Fraud – Merchants lose significant revenue from false declines, and many customers will abandon providers after experiencing friction from fraud controls.

• Hybrid Teams Are the Future – The fraud center of excellence will combine lean, strategic in-house teams with managed service partners, while analysts evolve into AI supervisors and threat hunters rather than manual alert reviewers.

How to Turn Fraud Prevention from a Cost Center to Growth Engine

The traditional view of fraud management as purely defensive creates organizational silos and blinds executives to significant upside potential, the panelists noted. Forward-thinking institutions now measure fraud strategy success through growth metrics, not just loss prevention.

Building Intelligent Fraud Controls for the Customer Era

Beyond Traditional KPIs

While standard metrics like approval rates and fraud reduction remain important, antifraud KPIs should expand to include:

• Customer onboarding time – How quickly can legitimate customers start using products?

• Churn due to fraudulent activity – What's the impact across all customer touchpoints?

• Time-to-market for new products – Can fraud safeguards keep pace with innovation?

• Customer lifetime value impact – How do fraud controls affect long-term revenue?

The True Cost of Friction

Every false decline doesn't just block a transaction—it permanently damages customer relationships and erodes shareholder value. The friction extends beyond the initial touchpoint, driving increased call center volumes, lower Net Promoter Scores, and reduced engagement across all channels.

Balancing Fraud Prevention and Customer Experience

For an accurate cost/benefit analysis of anti-fraud operations, payment providers must adopt frameworks that quantify:

• Lost revenue plus wasted customer acquisition costs

• Investigation costs (labor, systems, call centers)

• Customer lifecycle erosion and accelerated churn

• Negative brand sentiment and reputational damage

Defending Against AI-Weaponized Fraud

Fraudsters are early adopters of emerging technologies. They're already weaponizing generative AI to create hyper-realistic phishing content, fabricate synthetic identities with convincing digital footprints, and deploy deepfakes at scale—all using generally available tools that require minimal technical expertise.

3 Steps for Optimizing Financial Fraud Detection Tools

Traditional fraud prevention systems relying on static, human-written rules can't keep pace. These legacy approaches are brittle, slow to update, and easily circumvented by AI-powered attacks.

The Three Pillars of Adaptive Architecture

Modern fraud defense requires a fundamentally different approach built on three core pillars:

1. Cloud-Native, Scalable Infrastructure

This isn't just about hosting location. Cloud-native foundations leverage inherent elasticity to process massive data volumes in real time—the only way to match the speed of AI-driven threats. Galileo's cloud-native platform provides the scalability and flexibility needed to handle any volume while maintaining performance.

2. Real-Time Data Ingestion and Feature Engineering

Adaptive systems need high-volume data pipelines that pull information from every financial channel: mobile apps, websites, APIs, and call centers. This holistic approach provides the context needed for accurate decisioning.

3. Continuously Learning, Dynamic Models

Through automated feedback loops, systems learn from new transactions, emerging patterns, and analyst decisions. This creates AI that adapts as fast as threats evolve.

Advanced Detection Capabilities

The adaptive architecture must incorporate:

• Behavioral biometrics – Analyzing how users interact, not just what they do

• Graph and network analysis – Identifying entire networks of colluding bad actors invisible to traditional linear analysis

• Dynamic risk scoring – Moving beyond binary approve/decline to assign contextual scores to every interaction throughout the customer lifecycle

• Adaptive friction – Applying the right level of verification based on real-time risk signals

Galileo's Payment Risk Platform delivers these capabilities with AI-powered fraud detection that analyzes over 100 million unique spending patterns to stop threats before they happen. This approach transforms fraud architecture from roadblock to enabler, letting institutions innovate faster while maintaining security.

Building the Fraud Hub: Orchestration and Modularity

The concept of a "fraud hub" represents a unified system where multiple components interact to inform decisions dynamically. This breaks down the siloed, disconnected defenses that plague many institutions today.

A scalable, adaptable infrastructure should offer:

• Cross-channel visibility – Unified data views across all customer touchpoints

• Orchestration layers – Flexible adjustment of controls in real time

• Multiple detection models running in parallel – A/B testing to identify what works

• Risk-based friction strategies – Step-ups only when signals warrant them, with varying levels based on risk scores

• Diverse data integration – Combining device intelligence, behavioral biometrics, transactional context, third-party signals, and internal source data

When a fraudster bypasses one control using AI, cross-channel indicators provide additional context that traditional single-channel approaches miss. This reduces the lag between when new fraud tactics appear and when institutions can recognize them—critical in the generative AI era.

Galileo's fraud protection platform provides this comprehensive approach, combining managed services with advanced technology to deliver real-time fraud mitigation across all payment channels.

Making Fraud Defense a Strategic Mandate

The panelists stressed that the single most important factor to successfully navigating today’s fraud management landscape is thinking of fraud as a cross-functional component of sustainable growth, customer trust, and competitive differentiation.

An effective fraud strategy enables a payment provider to:

• Approve more good customers while blocking more bad actors

• Accelerate digital roadmaps without introducing unacceptable risk

• Protect brand reputation in an era of instant social media amplification

• Launch new products faster with embedded fraud safeguards

• Expand into new markets with confidence

This requires executive ownership and investment in adaptable, AI-powered platforms. It's no longer optional—it's a mandate for any modern digital business.

Watch the Full Webinar

Want to dive deeper into these fraud defense strategies? Watch the complete "Architecting Trust: Fraud Defense for Growth" webinar featuring Maxim Spivakovsky from Galileo Financial Technologies and Ramiel Mansour from PwC.

The full discussion includes additional insights on AI governance, regulatory compliance, data consortium strategies, and real-world case studies showing how leading institutions are transforming fraud management into a growth engine.

Access the complete webinar recording here to hear the experts' full conversation and get actionable strategies you can implement today.

For more information about how Galileo's adaptive fraud solutions can help your organization, visit our Payment Risk Platform page or contact our fraud experts.

Frequently Asked Questions

What makes modern fraud platforms different from traditional rule-based systems?

Traditional systems rely on static, human-written rules that are slow to update and easily circumvented. Modern adaptive platforms use cloud-native infrastructure, real-time data ingestion across all channels, and continuously learning AI models that evolve as fast as threats emerge. They provide contextual decisioning rather than binary approve/decline outcomes.

How can fraud prevention actually increase revenue?

By reducing false declines, friction, and customer churn while enabling faster time-to-market for new products. Studies show merchants lose revenue from declining legitimate transactions as well as from actual fraud. Modern platforms achieve ROI by simultaneously improving approval rates and reducing fraud losses.

What is adaptive friction and why does it matter?

Adaptive friction applies verification requirements dynamically based on real-time risk signals. Instead of blanket controls that frustrate all customers, institutions only add authentication steps when warranted—matching the friction level to the actual risk. This dramatically improves customer experience while maintaining security.

What's the biggest mistake executives make with fraud strategy?

Treating fraud as a back-office defensive function rather than a strategic growth enabler. This creates silos, focuses only on loss prevention, and blinds leadership to upside potential. Fraud strategy should have executive ownership and be integrated into core business strategy, with investment in platforms that accelerate innovation rather than blocking it.

Related Resources:

• Payment Risk Platform

• Fraud Operations Services

• Cyberbank Core Platform

• Digital Banking Platform