As artificial intelligence (AI) continues to evolve, its role in the world of B2B payments is transforming. No longer is the conversation about whether AI can make transactions faster or smarter—it’s about whether AI can make these transactions trustworthy. This shift towards dynamic, data-driven trust in payments is essential as businesses and financial institutions navigate the complex world of fraud, security, and verification.
During a recent conversation at the B2B Payments 2025 event hosted by Karen Webster, Vijay Mehta, EVP/GM of Global Solutions and Analytics at Experian, explained that AI’s ability to validate and execute decisions on the front lines of payment processing is revolutionizing the industry. In doing so, AI is not just improving operational efficiency but also rethinking how trust in digital transactions is established, maintained, and secured.
From Static Identity to Adaptive Trust
In traditional consumer identity verification (IDV), identity was typically static—one that was linked to personal attributes such as social security numbers, addresses, or credit histories. However, as Mehta explained, the B2B landscape is far more complex. Here, businesses represent a dynamic network of roles, permissions, and, increasingly, AI agents that initiate or authorize transactions on behalf of an organization. These evolving roles make trust in digital interactions more complicated but also more necessary.
“Identity isn’t static anymore,” Mehta emphasized. “It’s a network of roles, permissions, and now digital proxies with agentic AI.” Experian’s approach, according to Mehta, involves adaptive trust—a concept where trust is continuously reassessed based on real-time data. The more interactions, decisions, and actions an AI takes on behalf of the business, the more “breadcrumbs” it leaves, which can be monitored for anomalies, potential fraud, and irregularities.
In this adaptive system, AI is continuously analyzing behavioral patterns and device interactions. If something doesn’t align with typical patterns, the system flags it before the situation escalates. This proactive approach is critical, as fraudsters are increasingly leveraging AI to simulate legitimate transactions and manipulate business systems for financial gain.
AI and Fraud Prevention: A Double-Edged Sword
While AI can significantly reduce human error and automate decision-making, there is a risk that malicious actors can manipulate AI agents to perform fraudulent activities. Mehta explains that fraud is no longer limited to a “man-in-the-middle” attack targeting humans but has evolved into the exploitation of synthetic identities and AI-driven agents impersonating legitimate businesses.
In B2B payments, fraud could take many forms, such as invoice redirection or compromised vendor accounts. As AI agents handle more tasks, the risk grows that fraudsters will manipulate these agents’ training data or prompts, making fraudulent transactions look authentic.
Mehta warned, “AI can automate decisions and remove some of the human error that social engineering exploits. But if an attacker can manipulate an agent’s prompts or training data, the risk shifts rather than disappears.” This highlights the need for ongoing vigilance, continuous data monitoring, and enhanced fraud detection systems to protect businesses from these sophisticated scams.
Real-Time Monitoring Is Now Critical
In today’s fast-paced, digital world, traditional fraud detection methods—such as waiting for months until reconciliation—are no longer viable. Businesses need real-time monitoring to identify potential fraud before it becomes a major issue. Mehta underscores this point, emphasizing that AI’s speed and scale can help detect fraudulent activities in near real-time.
Experian has incorporated this concept into its Ascend ecosystem, offering businesses the ability to design multi-layered strategies combining traditional verification methods, behavioral intelligence, and continuous monitoring. This combination ensures that legitimate transactions are approved without disruption, while fraudulent activities are blocked early in the process.“Trust is the currency of digital commerce,” Mehta said, underscoring the importance of building systems that not only block fraud but also enable legitimate transactions to flow smoothly.
The Future of Trust in AI-Driven Payments
Looking ahead, Mehta believes that adaptive trust will be the key to securing future B2B transactions. As more businesses leverage AI to automate payments and decision-making processes, the ability to maintain real-time, data-driven trust will become more critical. Trust can no longer be a one-time validation—it must be ongoing and dynamic.
The future of finance and payment processing will require businesses to rethink their approach to trust and adapt to new technologies that can continuously monitor, analyze, and adjust based on real-time data. As AI technology evolves, so too must the systems that underpin it.
Frequently Asked Questions
1. What is adaptive trust in AI?
Adaptive trust refers to a system that continuously reassesses and updates trust levels based on real-time data, such as behavioral analytics and device interactions. It’s essential in identifying potential fraud and securing transactions in a digital ecosystem.
2. How does AI help in fraud prevention?
AI can detect fraudulent activities in real-time by analyzing patterns and anomalies, reducing human error, and automating decision-making processes, ultimately preventing fraud before it escalates.
3. What are the challenges of AI in B2B payments?
The primary challenge is ensuring that AI systems are not exploited by fraudsters who may manipulate agent prompts or training data. Continuous monitoring and robust data verification methods are needed to mitigate these risks.
4. How does Experian’s Ascend ecosystem contribute to fraud prevention?
The Ascend ecosystem integrates traditional verification methods with advanced tools like behavioral intelligence and continuous monitoring, allowing businesses to approve legitimate transactions while blocking fraudulent ones.
5. What does “trust is the currency of digital commerce” mean?
This phrase emphasizes that trust is fundamental to secure and efficient digital transactions. In an AI-driven payment ecosystem, trust must be continuously earned and maintained, rather than being assumed.