Sibos 2026: FIS's James Johnson on Orchestrating Intelligence and Digital Assets

Quick Summary

The transition to real-time financial environments requires a fundamental shift in how institutions handle risk, verification, and data. James Johnson of FIS explains at Sibos 2026 how the company is building trust by design into its digital asset systems and leveraging orchestrated intelligence to overcome the challenges of legacy data fragmentation.

Why is foundational trust critical for real-time payments?

In the traditional history of payments, financial institutions have always had the luxury of time to review, analyse, and repair transactions if necessary. James Johnson notes that with the move toward real-time payments, that luxury no longer exists. Control, trust, and verification must be built into the very foundation of the payment infrastructure.

To address this, FIS developed its digital asset system, Lyric, with these concepts integrated from the start. Rather than treating security as an overlay, the system is designed with:

• Risk controls embedded at the foundational level.
• Clear audit trails for every decision made.
• Transparency regarding how technology answers critical risk questions.

This architecture with confidence and trust by design ensures that as payments move faster, the underlying systems remain secure and verifiable.

How do Glasswing and Lyric differ in their approach to security?

James Johnson describes these two endeavours as separate tracks grounded in the same goal of security and confidence. Glasswing provides FIS with the ability to detect vulnerabilities that were previously undetectable, allowing the company to fix them quickly and make existing technology stacks safer for customers.

While Glasswing focuses on securing current stacks, Lyric is aimed at the future of digital currency. In this track, FIS is building safety, access controls, and risk management into the foundation of the system. Both tracks aim for the same result: ensuring that every transaction and process is backed by a high level of trust, whether it is on a legacy system or a new digital asset platform.

What are the primary obstacles to effective AI implementation in banking?

Banks have shifted their mindset from simply asking how to employ Artificial Intelligence to asking how they can drive specific results. According to James Johnson, banks are currently focused on three main goals: improving user experience through insights, driving operational efficiency, and creating more secure products. However, the significant challenge remains data fragmentation.

Many organisations struggle with data that is separated by product, channel, or customer segment within legacy stacks. FIS is tackling this through orchestrated intelligence, which focuses on making data from these legacy systems available for real-time analytics. James Johnson stresses that AI cannot be truly operational unless it is deployed with trust, risk controls, and transparency that align with an organisation's risk profile.

How does the scale of FIS data influence its AI capabilities?

The scale and breadth of data at FIS provide a unique context for powering AI tools. James Johnson highlights several key figures that illustrate this reach:

• Over one billion credit card accounts on file.
• Coverage of over 60 percent of the US population and a large international customer base.
• Processing a significant percentage of trading transactions on global markets.

By combining transactional data with event data, such as address changes, marital status, or loan balances, FIS can provide a depth of context that was previously unavailable. This allows the company to embed AI capabilities directly into customer workflows, giving them decision-making power and insights they have not been able to deploy before.

FF NEWS TAKE:

The move toward real-time payments and agentic commerce is no longer a future prospect but a current reality that demands a total rethink of infrastructure. By embedding risk controls directly into the architecture of systems like Lyric, FIS is addressing the trust gap that often plagues rapid digital transformation. The concept of orchestrated intelligence suggests that the next phase of fintech innovation will not be about the AI models themselves, but about the ability to unify fragmented legacy data to make those models actionable, secure, and transparent in a high-speed environment.