CREDIT, DATA, AND OPERATIONAL EFFICIENCY: AI'S REAL IMPACT

As a Media Partner of Money20/20 Europe 2026, we spent the first week of June speaking with fintech founders, technology leaders, data specialists, and financial services operators to understand how organizations are using AI beyond the headlines.

While discussions around generative AI, agentic systems, and automation were everywhere, a consistent message emerged across conversations: the real value of AI is increasingly being found behind the scenes.

Rather than replacing people, organizations are using AI to improve operational efficiency, support decision-making, automate routine processes, and extract value from growing volumes of data.

Across discussions with leaders from Infinian Data Solutions, Flagstone, PayX Group, Digital Commerce Group, Tracetronic, and Enfuce, several themes surfaced most.

AI Is Only as Good as the Data Behind It

While many organizations are eager to deploy AI, several industry leaders stressed that success still depends on getting the fundamentals right.

Emma Steeley of Infinian Data Solutions emphasized that data quality, governance, and bias management remain critical foundations for any successful AI strategy. Organizations that rush into AI initiatives without addressing underlying data challenges often struggle to achieve reliable outcomes.

This reflects a broader shift in industry thinking. The conversation is moving away from simply adopting AI tools and toward building the data infrastructure required to support them effectively.

Emma also highlighted the growing use of AI-assisted software development, where code generation tools are helping engineering teams accelerate delivery while allowing developers to focus on higher-value activities.

In many organizations, AI is becoming less about replacing work and more about removing friction.

Operational Efficiency Has Become a Competitive Advantage

A recurring theme throughout Money20/20 was the growing focus on operational scalability.

For many fintechs, the challenge is no longer proving product-market fit. It is scaling efficiently while maintaining customer experience, compliance standards, and profitability.

Francesco Fulcoli of Flagstone shared how automation has helped the company scale while managing more than £20 billion in assets under management. Through extensive automation of onboarding, compliance, and risk management processes, the organization has achieved straight-through processing rates of up to 90%.

What stood out was not the technology itself, but the mindset behind it.

Across many conversations, operational efficiency is no longer viewed as a back-office initiative. It is increasingly becoming a strategic capability that enables growth without requiring proportional increases in headcount.

Cole Jones of Digital Commerce Group described a similar trend, explaining how workflow automation and AI have significantly reduced time spent on repetitive administrative activities, allowing teams to focus more on customer relationships, revenue generation, and strategic initiatives.

From Automation to Decision Intelligence

One of the more mature applications of AI discussed throughout the event was the ability to identify patterns and insights across large datasets.

Stefan Kasek of Tracetronic shared how AI helps engineering teams analyze millions of software testing results, identify recurring issues, and group similar failures together. Rather than spending valuable engineering time manually reviewing data, teams can focus on root-cause analysis and problem resolution.

The principle extends far beyond software testing.

As financial institutions, lenders, and technology companies continue to generate growing volumes of operational data, the ability to transform information into actionable insights is becoming increasingly important.

Organizations are beginning to move beyond automation toward what could be described as decision intelligence, or systems that help employees understand what is happening, why it is happening, and where attention should be focused.
Human Expertise Remains Essential

Despite the excitement around AI, few industry leaders described a future where humans are removed from the process entirely.

Scott Anthony of PayX Group discussed how AI agents are increasingly supporting architects, analysts, developers, testers, and delivery teams throughout the software development lifecycle. While these tools can significantly increase productivity, human expertise remains critical for validation, governance, and decision-making.

This sentiment appeared repeatedly throughout Money20/20.

The most successful organizations are not replacing employees with AI. They are augmenting employees with AI.

The emphasis is shifting from automation for automation's sake toward creating systems where people and technology work together more effectively.

Innovation Must Operate Within Governance

As organizations deploy AI more broadly, governance remains a critical consideration.

Vanessa Schotes of Enfuce highlighted opportunities to leverage AI within fraud management, dispute resolution, and operational workflows, while also emphasizing the importance of customer protection, regulatory compliance, and responsible data usage.

This reflects a reality facing many financial institutions today.

Innovation alone is no longer enough.

Organizations must balance speed with trust, efficiency with transparency, and automation with accountability.

Particularly within regulated sectors such as financial services, AI adoption is increasingly being evaluated not only by what it can do, but by how safely and responsibly it can be implemented.

The New Competitive Advantage

Perhaps the most important takeaway from Money20/20 Europe 2026 was that AI is becoming less visible to customers and more embedded into how organizations operate.

The companies seeing the greatest impact are not necessarily those launching AI-branded products. They are often the ones quietly transforming onboarding, compliance, engineering, analytics, operations, customer support, and decision-making processes behind the scenes.

The conversation has moved beyond experimentation.

The new challenge is execution.

And increasingly, the organizations that combine strong data foundations, operational discipline, and responsible AI adoption may be the ones best positioned to scale in the years ahead.

Reporting by the UAtech team, on the ground at Money20/20 Europe 2026.