AI at the Heart of Safer Payments: An Interview on Risk Management Innovation
In the global payments space, risk management is evolving rapidly thanks to machine learning, AI, and advanced analytics. We sat down with our Consumer Risk Data Science team to discuss how these technologies are shaping the future, recent innovations, and what responsible AI means for the business.
How do machine learning, AI, and advanced analytics shape the future of risk management in the global payments space?
Machine learning, AI, and advanced analytics are transforming risk management by making it smarter, safer, and more customer-centric. These technologies allow us to analyze vast amounts of transaction data in real time, identifying subtle patterns that traditional methods might miss. This means fewer false positives and more accurate risk assessments. Improved detection accuracy reduces friction for legitimate transactions, helping us onboard and serve more customers globally without compromising security. Advanced models also adapt to evolving fraud tactics, ensuring proactive detection and prevention. Ultimately, AI-driven risk management balances security with convenience, creating a safer and more inclusive payments experience worldwide.
Can you share an example of a recent innovation or breakthrough your team delivered that had a measurable impact on fraud reduction or risk prediction?
We launched a dedicated Anti-Money Laundering (AML) risk scoring model for registered eCash customers in the EEA and UK. This innovation removes fraud bias from AML ratings, isolates true AML and Countering the Financing of Terrorism (CFT) indicators, and aligns with global regulatory expectations for defensible and transparent risk classification. It also delivers high explainability, making it easy to demonstrate key drivers and decisions to regulators. The benefits include dynamic, risk-based limit increases for low-risk segments, better protection for high-value genuine customers, reduced need for Full Due Diligence for low-risk users, and safer expansion into new markets where AML risk was previously a blocker.
Consumer risk touches nearly every part of the business, how do your teams collaborate with product, engineering, risk operations, compliance, and other units?
Consumer risk is truly a cross-functional effort. Our models feed into operational workflows, and we rely on feedback to continuously improve detection strategies. We partner with product and engineering to embed risk controls into design, ensuring security doesn’t come at the expense of user experience. For example, outcomes of risk models in AWS integrate into risk engines like Feedzai or KYC limit services so they work seamlessly. Compliance ensures our models meet transparency and auditability standards. This collaboration creates better models, improved customer experience, and stronger regulatory confidence.
What does responsible AI mean at Paysafe, particularly in the context of fraud prevention and consumer decisioning?
Responsible AI at Paysafe means building models that are accurate, transparent, and ethical. In fraud prevention and consumer decisioning, this starts with data integrity: we use high-quality, relevant data and avoid signals that could introduce bias. Explainability is critical: we ensure every decision can be clearly justified for regulators and customers. We also embed model governance oversight, validating models and monitoring them continuously. Finally, responsible AI is about balance: stopping fraud without creating unnecessary friction for genuine customers. Every model we deploy is tested to protect users while enabling growth.
What is your overarching vision for Consumer Risk Data Sciences at Paysafe over the next few years?
Our vision is to evolve toward proactive, intelligent risk orchestration at a global scale. Over the next few years, we’ll embed consumer risk models across all portfolios and segments, leverage next-generation AI to uncover complex fraud patterns, advance explainable AI for AML models, and enable global scalability as Paysafe enters new markets. Ultimately, our goal is simple yet powerful: make risk management invisible for genuine customers and impenetrable for bad actors, powered by ethical, adaptive, and business-enabling data science.
Join Us in Shaping the Future of Payments
At Paysafe, we’re building the next generation of risk management powered by AI and data science. If you’re passionate about innovation, security, and creating frictionless experiences, explore our career opportunities and be part of the journey.