The notification pings on your phone. Your digital wallet wants permission to access your account. Your banking app needs an update. A new cryptocurrency exchange promises revolutionary security. You pause, finger hovering over the screen, and ask yourself the question millions ask every day: Can I really trust this?
That moment of hesitation contains a universe of concerns that researchers have struggled to understand, let alone measure. Until now.
The Trust Gap Nobody Could Measure
Picture this: You're standing at a coffee shop, ready to pay with your phone instead of cash or card. In that split second before you tap, your brain processes an incredibly complex calculation. Is my data safe? Will my money actually transfer? What happens if something goes wrong? Can hackers intercept this transaction? Does the government regulate this app?
These questions aren't just individual worries. They represent a massive global challenge that's been hiding in plain sight.
Financial technology, commonly called FinTech, has exploded across the world. From 2019 to 2023, the market value of FinTech companies doubled to reach a staggering 550 billion dollars. Mobile banking apps saw downloads surge by 132% in 2020 alone. Digital wallets, cryptocurrency platforms, robo-advisors, and countless other innovations now handle trillions of dollars in transactions daily.
Yet despite this incredible growth, something critical was missing from the equation. Scientists and companies had no reliable way to measure what users actually thought about security. They couldn't accurately gauge the complex web of concerns that make someone trust or distrust these technologies.
Think about that for a moment. The entire FinTech industry was building on a foundation it couldn't properly measure. Companies were making billion-dollar decisions based on incomplete information. Researchers couldn't compare security perceptions across different services or countries. Regulators had no standard tool to evaluate whether security measures were actually working in the eyes of users.
This gap between the explosive growth of FinTech and our ability to understand user security perceptions created real problems. Studies found that security concerns remained the primary barrier preventing people from adopting FinTech services. Users consistently raised alarm bells about data privacy, authentication methods, network vulnerabilities, and fraudulent service providers. Yet without a proper measurement tool, nobody could precisely diagnose the problem or test whether solutions actually worked.
The Birth of a New Measurement
A research team based in the United Arab Emirates decided to tackle this seemingly impossible challenge. Their goal was ambitious: create the first scientifically rigorous tool that could measure the intricate, multifaceted ways people perceive security in FinTech services.
What made this so difficult? Security perception isn't simple. It's not just one thing you can ask about and get a clear answer. When someone decides whether to trust a digital banking app, their decision emerges from a complex interplay of factors. Some are obvious, like whether the app displays security badges or uses encryption. Others are subtle, like how the government regulates the industry or how much the person understands about the technology.
Previous attempts to measure FinTech security had fallen short in crucial ways. Some researchers borrowed measurement tools designed for entirely different technologies, like general website security from the early 2000s or Internet of Things devices. Others cobbled together questions from various sources without rigorous validation. None captured the full picture.
The research team spent years developing what they call the FinTech Security Adoption Scale, or FT-SAS for short. They used a meticulous five-stage process involving systematic review of existing research, consultation with two dozen FinTech experts, and surveys of nearly 1,400 FinTech users across the United States and United Kingdom.
Why focus on the US and UK? These countries represent the world's most advanced FinTech markets. The United States and United Kingdom rank first and second globally in FinTech ecosystem development. They're home to the top startup hubs for financial technology. Yet most previous research had focused heavily on developing nations, particularly China, India, and South Korea. This left a gap in understanding how users in mature markets perceive security challenges.
Five Dimensions of Digital Trust
What the researchers discovered fundamentally changes how we understand FinTech security. Instead of being one simple thing, security perception operates along five distinct but interconnected dimensions. Think of them as five different lenses through which people view whether a financial technology is safe.
The first dimension they identified is what they call perceived protection. This captures how users react to visible security signals. When you see a padlock icon on a website, or security badges, or certification seals, these visual markers communicate that protective measures exist. Research shows these symbols genuinely influence whether people trust a service. Companies that display strong security statements and implement visible privacy policies substantially enhance user confidence.
But symbols alone aren't enough, which leads to the second dimension: the transactional procedure itself. Every step of a digital transaction creates an opportunity for security perceptions to form. How does the system verify you're actually you? Is it easy to complete a transaction or frustratingly complex? What happens if something goes wrong? The authentication method matters enormously. Some systems use simple passwords, others use biometric data like fingerprints, still others employ graphical patterns or multi-factor authentication. Each choice affects both actual security and how secure users feel. Studies show that clunky, difficult authentication processes don't just annoy users; they actively erode trust and reduce continued usage. The payment source matters too. People perceive credit cards, debit cards, and digital wallets differently in terms of security.
The third dimension focuses on something many people overlook: device security. Your phone or computer becomes the gateway for all FinTech interactions. A transaction is only as secure as the device running the application. This creates a dependency that makes many users nervous. After all, personal devices face countless security threats. Data can be intercepted during collection, management, storage, or delivery. Any perceived inability of FinTech providers to secure personal devices can prevent people from trying new applications, regardless of how innovative they might be.
The fourth dimension might surprise you: user knowledge of FinTech services. How much someone understands about how these systems work directly influences their security perceptions. An informed user base proves integral to strong security perceptions. Previous research established that system security can be enhanced by understanding how users perceive specific security mechanisms. The spread of new technology depends heavily on potential users' knowledge levels and confidence. Experience and learning emerge as key determinants influencing trust and usage patterns. Put simply, people who understand the technology better tend to feel more secure using it.
The fifth and final dimension involves something beyond individual control: government security regulations. Government agencies play a critical role as facilitators of technology adoption and security. Regulatory bodies have increased security measures to match the pace of online transactions. However, government concerns also rank among the key barriers hindering effective FinTech integration. Regulations can either promote or hinder technological development. Some countries ban certain FinTech services outright, while others create supportive regulatory environments. Users are keenly aware of this governmental role, and it shapes their comfort level with different services.
The Continuum Revelation
Here's where the research gets truly fascinating. These five dimensions don't operate in isolation. They exist along a continuum, constantly interacting and influencing each other in complex ways.
Traditional research approaches tried to measure each factor separately, as if they were completely independent. Imagine trying to understand a symphony by listening to each instrument alone, never hearing how they blend together. That's essentially what previous studies were doing.
The research team used an innovative statistical technique called bifactor exploratory structural equation modeling. The name sounds intimidating, but the concept is powerful. This approach allows researchers to measure both the specific, individual dimensions of security perception AND the overall, general sense of security that emerges from their interaction.
Think of it like this: When you evaluate whether to trust a FinTech app, you're simultaneously considering specific factors (Is the authentication easy? Does it have security badges? Do I understand how it works?) while also forming an overall gut feeling about whether it seems secure. Previous measurement tools could only capture one or the other. This new approach captures both simultaneously.
The findings revealed something remarkable. All five dimensions loaded significantly onto a general security factor, meaning they all contribute to your overall sense of whether something is secure. But they also retained their unique characteristics as specific factors. Government security, for instance, played an interesting role. When examined microscopically as just one factor, its direct relationship with whether people found FinTech useful was only marginally significant. But when examined as part of the bigger picture, government security contributed substantially to overall security perceptions.
This discovery has profound implications. It means that to truly understand whether users trust a FinTech service, you need to measure both the forest and the trees. You need to understand their overall security perception while also diagnosing specific pain points. Ignoring either level gives you only half the truth.
Why This Matters to You
So what? Why should you care about academic researchers developing a new measurement scale? The answer touches everyone who uses digital financial services, which increasingly means everyone.
First, this research provides companies with a roadmap to build better, more trustworthy products. For the first time, FinTech providers can systematically identify which specific security vulnerabilities users actually worry about. They can test whether their solutions work by measuring changes in user perceptions across all five dimensions. A company might discover, for example, that users feel insecure not because of weak encryption, but because they don't understand how the authentication process works. That insight leads to very different solutions than if the company assumed the problem was purely technical.
Second, this tool gives regulators and policymakers a way to evaluate whether security regulations actually make users feel more secure. Governments can compare security perceptions across different regulatory approaches. They can identify where their interventions help build trust and where they fall short. This evidence-based approach to policymaking could prevent situations where regulations that look good on paper fail to address users' actual concerns.
Third, for users, this research validates something you probably already felt intuitively: your hesitation about FinTech security is rational and complex. You're not being paranoid when you worry about multiple aspects of security simultaneously. Your concerns about government regulation, device security, transaction procedures, and your own knowledge levels are all legitimate parts of evaluating whether a service is trustworthy.
The research also reveals a critical gap between corporate FinTech adoption and individual user trust. Companies have rapidly embraced these technologies, but individuals remain substantially more skeptical about security. This trust deficit has real consequences. It slows adoption of beneficial innovations, creates market inefficiencies, and leaves vulnerable populations even more excluded from financial services.
The Global Picture
The study focused on the United States and United Kingdom for good reasons, but the implications extend far beyond these two countries. The researchers designed the measurement scale to be applicable globally, with potential to capture diverse cultural and economic contexts.
FinTech looks different around the world. In Kenya, mobile money through services like M-Pesa has revolutionized financial inclusion. In China, WeChat Pay and Alipay dominate daily transactions. In India, massive digital payment infrastructure initiatives aim to bring hundreds of millions into the formal economy. Each context presents unique security challenges and user perceptions.
The beauty of a well-designed measurement tool is its adaptability. Future researchers can use the FT-SAS to compare security perceptions across countries, identifying which dimensions matter most in different cultural contexts. Maybe device security concerns dominate in regions where personal smartphones are primary internet access points. Perhaps government security perceptions vary dramatically between countries with different regulatory traditions. These insights could guide more nuanced, locally appropriate security solutions.
What Comes Next
The researchers themselves acknowledge limitations and point toward exciting future directions. The current tool focuses on users who already have FinTech experience. What about people who have never used these services? Understanding their security perceptions could help break down adoption barriers for populations currently excluded from digital financial services.
The study also primarily addresses one risk response strategy: mitigation, or reducing risk exposure below an acceptable threshold. But FinTech providers use other strategies too, including transferring risk to third parties through insurance or guarantees. Future research could explore how these different risk management approaches affect user perceptions.
Technology keeps evolving. Today's FinTech landscape includes InsurTech (insurance technology), GovTech (government technology), RegTech (regulatory technology), RoboAdvisory (automated investment advice), and alternative lending platforms. Each subset faces distinct security challenges. Can this measurement tool adapt to evaluate security perceptions across all these domains? That question remains open for future investigation.
Perhaps most intriguingly, the researchers suggest exploring whether perceived protection, which relates closely to trust, might itself be a higher-order construct capable of predicting behavioral intentions and attitudes. This could unlock new understandings of how security perceptions translate into actual decisions to use or avoid FinTech services.
The Methodology Revolution
Beyond its practical applications, this research demonstrates something important about scientific methodology itself. The bifactor exploratory structural equation modeling approach represents a significant advancement over traditional techniques.
For decades, researchers relied on two main statistical approaches: exploratory factor analysis and confirmatory factor analysis. The first helps discover patterns in data; the second tests whether predicted patterns actually exist. Each had limitations. Exploratory approaches couldn't confirm structures. Confirmatory approaches forced unrealistic assumptions, like requiring each survey question to relate to only one underlying concept.
Real human perceptions don't work that way. When you answer a question about whether you trust the authentication process of a banking app, that response reflects not just your view of authentication, but also your general sense of the app's security, your understanding of technology, and more. Previous statistical methods couldn't handle this complexity well.
The new approach integrates the strengths of multiple techniques into one framework. It allows questions to relate to multiple concepts simultaneously while still maintaining clear measurement. It separates general and specific factors explicitly. This methodological innovation has applications far beyond FinTech research.
Other fields studying complex human perceptions could benefit from similar approaches. Consumer behavior, health psychology, educational assessment, and organizational research all grapple with multidimensional constructs that don't fit neatly into traditional measurement boxes.
Security in the Age of Digital Everything
Step back and consider the bigger picture. We're living through a massive transformation in how money works. For thousands of years, financial transactions required physical presence, tangible currency, or at minimum, identifiable human intermediaries. Within a few decades, much of that has dissolved into streams of digital information moving through invisible networks.
This transformation brings tremendous benefits: convenience, speed, financial inclusion, reduced transaction costs, and new economic possibilities. But it also introduces vulnerabilities that previous generations never faced. Your grandmother might have worried about pickpockets. You worry about hackers halfway around the world stealing your identity through a compromised app.
Security in this new world isn't just about technology. It's about psychology, sociology, regulation, education, and trust. The research we've explored today recognizes this complexity and provides tools to navigate it.
When companies understand the multifaceted nature of security perceptions, they can design solutions that address actual human concerns rather than just technical vulnerabilities. When regulators grasp how government security interacts with other dimensions of trust, they can craft policies that genuinely enhance user confidence. When individuals understand their own security reasoning across these five dimensions, they can make more informed decisions about which services to trust.
Your Role in the Secure Future
So the next time you hesitate before tapping that payment button, recognize that your caution reflects a sophisticated evaluation process. You're not simply afraid of technology. You're assessing perceived protection through security symbols, evaluating transactional procedures, considering device security, reflecting on your own knowledge, and weighing government regulatory frameworks.
Your expectations matter. By demanding better security, clearer explanations, stronger regulations, and more transparent practices, you shape how this technology evolves. Companies that ignore the five dimensions of security perception do so at their own peril. Those that address them systematically will build the trust necessary for long-term success.
The FinTech revolution will continue, bringing innovations we can barely imagine today. Digital currencies, decentralized finance, artificial intelligence-powered advisors, and technologies yet uninvented will reshape financial services. But one thing will remain constant: the fundamental human need to trust that our financial resources are secure.
This research provides a foundation for building that trust scientifically, systematically, and sensibly. It moves the conversation beyond vague reassurances toward measurable, addressable concerns. It acknowledges the complexity of human psychology while providing practical tools for improvement.
The next time you download a banking app, you're participating in one of humanity's great experiments: learning to trust systems we can't see, understand completely, or control directly. That's a profound challenge. But armed with better understanding of what security really means to users, we're better equipped to meet it.
Your finger hovers over the screen. The app awaits. The decision is yours. Now, at least, we can understand what goes into making it.
Publication Details
Published: April 16, 2025 (online)
Journal: European Journal of Information Systems
Publisher: Taylor & Francis Group
DOI: https://doi.org/10.1080/0960085X.2025.2491449
Credit and Disclaimer
This article is based on original research published in the European Journal of Information Systems by researchers from Abu Dhabi University and Canadian University Dubai. The content has been adapted for a general audience while maintaining full scientific accuracy. For complete technical details, comprehensive statistical analyses, methodological procedures, validation results, and all supporting data, readers are strongly encouraged to access the full peer-reviewed research article through the DOI link provided above. All factual information, research findings, and scientific conclusions presented here are derived directly from the original publication, and full credit goes to the research team and their institutions.






