Skip to main content

Even Major Banks Are Lagging in Digital Experience

Mehdi Daoudi
Catchpoint

For banks, today digital experience is the foundation for their services. Every digital interaction is a critical touchpoint for quietly building trust — or breaking it with undetected delays and disruption.

Despite how critical digital experience can be for financial institutions, Catchpoint's 2025 Banking Website Performance Benchmark Report reveals a surprising reality: only 25% of global banks deliver homepage load times under three seconds. That means 75% are falling short of customer expectations. In fact, some of the most recognized financial institutions require seven, nine, or even 10 seconds to fully load a page. Several well-known global institutions did not even appear in the top 30 rankings. These findings are more than technical details. Several big-name banks with low rankings in the report have already made headlines for digital disruptions in just the first half of 2025. The report represents a real warning for institutions competing in a digital marketplace.

Performance Is the New Currency of Trust

Many banks monitor infrastructure from the inside out. Instead of getting a full picture, they are focused on uptime and internal server metrics, which are important to track, but neglect to address the actual end-user experience. However, the user experience (UX) is shaped by dozens of factors beyond the application itself. Consumers expect their banking applications to load quickly, operate smoothly and remain visually stable regardless of their location or device. At best, a sub-par digital experience erodes confidence at best, and at worst, for financial institutions, can even cause panic among customers who can't access their money.

The top performers in the benchmark study (UBS, ING (Voya), and State Street) achieved high rankings by delivering a seamless digital experience. These banks demonstrated near-perfect uptime, server response times below 200 milliseconds and homepage loads within 2-3 seconds. Their sites offered clean layouts with minimal visual shifts, proving that simplicity, consistency and speed matter.

The Most Urgent Findings

  • Only one in four banking websites load within the three-second threshold of what customers consider acceptable.
  • Several high-profile banks, ranked outside the top 30.
  • Banks with strong backend response times frequently lost ground due to frontend performance issues such as excessive layout shifts and bloated content.

A bank that appears online but takes more than five seconds to respond is not delivering a reliable digital experience. And across industries, business leaders agree that slow is the new down. Users are no longer willing to wait.

Implications for Financial Institutions

Financial institutions are no longer competing on new customer promotions or product offerings. They are competing on the quality of their digital experiences. Every delay and every stalled transaction represents a potential loss in customer engagement and long-term trust.

This year's benchmark data shows that front-end optimization is a baseline requirement for competing in global markets. While backend availability remains essential, it is only one component of a broader digital performance strategy.

Institutions must transition from tracking selfish uptime metrics to measuring real-world experience across diverse geographies and network conditions. This requires the adoption of Experience Level Objectives (XLOs) that reflect what customers actually encounter when they visit a banking website or mobile application.

Lessons from Leading Banks

The highest-ranking banks share several best practices:

  • They maintain globally distributed infrastructure and deploy robust CDN strategies to reduce latency across regions.
  • They monitor real user journeys from the end-user perspective, not just from cloud regions.
  • They prioritize front-end performance indicators- like Largest Contentful Paint (LCP) and Cumulative Layout Shift (CLS).
  • They treat real-world web performance as a core aspect of their brand experience.

By contrast, banks that ignore front-end challenges, regional disparities, and API dependencies are falling behind. This is where institutions introduce vulnerability to digital friction that diminishes user satisfaction, particularly in underserved markets.

Investing in Performance Pays Dividends in Digital Experience

The findings of this year's Banking Benchmark Report ring clear: Financial institutions must take immediate and sustained action to improve their digital performance. This could mean compressing content, streamlining pages, improving layout stability and expanding regional infrastructure to ensure equitable access. It could also include elevating performance as a board-level priority, investing in comprehensive Internet Performance Monitoring tools and measuring digital reliability as closely as the bottom line.

Digital performance is a strategic imperative. Banks that fail to act risk losing not just customers, but their competitive edge. This is why businesses need to continuously measure from thousands of global vantage points, ensuring the visibility they need to lead, not fall behind.

Fast, stable and consistent websites are the new expectation for trust, loyalty and growth in banking.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Even Major Banks Are Lagging in Digital Experience

Mehdi Daoudi
Catchpoint

For banks, today digital experience is the foundation for their services. Every digital interaction is a critical touchpoint for quietly building trust — or breaking it with undetected delays and disruption.

Despite how critical digital experience can be for financial institutions, Catchpoint's 2025 Banking Website Performance Benchmark Report reveals a surprising reality: only 25% of global banks deliver homepage load times under three seconds. That means 75% are falling short of customer expectations. In fact, some of the most recognized financial institutions require seven, nine, or even 10 seconds to fully load a page. Several well-known global institutions did not even appear in the top 30 rankings. These findings are more than technical details. Several big-name banks with low rankings in the report have already made headlines for digital disruptions in just the first half of 2025. The report represents a real warning for institutions competing in a digital marketplace.

Performance Is the New Currency of Trust

Many banks monitor infrastructure from the inside out. Instead of getting a full picture, they are focused on uptime and internal server metrics, which are important to track, but neglect to address the actual end-user experience. However, the user experience (UX) is shaped by dozens of factors beyond the application itself. Consumers expect their banking applications to load quickly, operate smoothly and remain visually stable regardless of their location or device. At best, a sub-par digital experience erodes confidence at best, and at worst, for financial institutions, can even cause panic among customers who can't access their money.

The top performers in the benchmark study (UBS, ING (Voya), and State Street) achieved high rankings by delivering a seamless digital experience. These banks demonstrated near-perfect uptime, server response times below 200 milliseconds and homepage loads within 2-3 seconds. Their sites offered clean layouts with minimal visual shifts, proving that simplicity, consistency and speed matter.

The Most Urgent Findings

  • Only one in four banking websites load within the three-second threshold of what customers consider acceptable.
  • Several high-profile banks, ranked outside the top 30.
  • Banks with strong backend response times frequently lost ground due to frontend performance issues such as excessive layout shifts and bloated content.

A bank that appears online but takes more than five seconds to respond is not delivering a reliable digital experience. And across industries, business leaders agree that slow is the new down. Users are no longer willing to wait.

Implications for Financial Institutions

Financial institutions are no longer competing on new customer promotions or product offerings. They are competing on the quality of their digital experiences. Every delay and every stalled transaction represents a potential loss in customer engagement and long-term trust.

This year's benchmark data shows that front-end optimization is a baseline requirement for competing in global markets. While backend availability remains essential, it is only one component of a broader digital performance strategy.

Institutions must transition from tracking selfish uptime metrics to measuring real-world experience across diverse geographies and network conditions. This requires the adoption of Experience Level Objectives (XLOs) that reflect what customers actually encounter when they visit a banking website or mobile application.

Lessons from Leading Banks

The highest-ranking banks share several best practices:

  • They maintain globally distributed infrastructure and deploy robust CDN strategies to reduce latency across regions.
  • They monitor real user journeys from the end-user perspective, not just from cloud regions.
  • They prioritize front-end performance indicators- like Largest Contentful Paint (LCP) and Cumulative Layout Shift (CLS).
  • They treat real-world web performance as a core aspect of their brand experience.

By contrast, banks that ignore front-end challenges, regional disparities, and API dependencies are falling behind. This is where institutions introduce vulnerability to digital friction that diminishes user satisfaction, particularly in underserved markets.

Investing in Performance Pays Dividends in Digital Experience

The findings of this year's Banking Benchmark Report ring clear: Financial institutions must take immediate and sustained action to improve their digital performance. This could mean compressing content, streamlining pages, improving layout stability and expanding regional infrastructure to ensure equitable access. It could also include elevating performance as a board-level priority, investing in comprehensive Internet Performance Monitoring tools and measuring digital reliability as closely as the bottom line.

Digital performance is a strategic imperative. Banks that fail to act risk losing not just customers, but their competitive edge. This is why businesses need to continuously measure from thousands of global vantage points, ensuring the visibility they need to lead, not fall behind.

Fast, stable and consistent websites are the new expectation for trust, loyalty and growth in banking.

Mehdi Daoudi is CEO and Co-Founder of Catchpoint

The Latest

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...