Perceived service quality and security are paramount for AI adoption in mobile banking

Why It Matters

Understanding the drivers of trust is crucial for designing AI-powered banking services that users will readily adopt. Focusing on these core elements can lead to more successful digital product development and user engagement.

Key Finding

For AI in mobile banking to be adopted, users need to feel confident about the quality of service and the security of their data. While a clear benefit (relative advantage) encourages use, an overemphasis on perceived need or making it too easy might deter adoption.

Key Findings

• Perceived service quality and security are the primary drivers of trust in AI for mobile banking.
• Trust positively influences attitudes towards AI and comfort with its use.
• Relative advantage significantly promotes intentions to use AI in mobile banking.
• Perceived need and excessive comfort unexpectedly reduce the likelihood of AI adoption.

Research Evidence

Aim: What are the key factors influencing Portuguese consumers' behavioral intentions to use artificial intelligence in mobile banking applications?

Method: Quantitative research using multiple linear regression.

Procedure: Collected survey data from 452 Portuguese consumers regarding their perceptions of AI in mobile banking, including factors like perceived service quality, security, relative advantage, perceived need, and comfort.

Sample Size: 452 participants

Context: Mobile banking applications in Portugal.

Design Principle

Trust is a foundational element for user adoption of AI in sensitive applications like mobile banking, built upon perceived service quality and security.

How to Apply

When designing AI features for financial applications, conduct user research to validate perceptions of service quality and security, and test different levels of perceived need and interaction complexity.

Limitations

Findings are specific to Portuguese consumers and may not generalize to other cultural contexts. The study focuses on intentions rather than actual behavior.

Student Guide (IB Design Technology)

Simple Explanation: People are more likely to use AI in their banking apps if they think the service is good and their information is safe. Surprisingly, if they think they don't really need it or it's too simple, they might not use it.

Why This Matters: This research highlights that user trust, driven by service quality and security, is critical for the success of new technologies like AI in banking. It shows that simply adding AI isn't enough; it needs to be perceived as valuable and safe.

Critical Thinking: How might the 'perceived need' and 'excessive comfort' findings be explained? Could this relate to user anxiety about control or a desire for human interaction in financial matters?

IA-Ready Paragraph: Research indicates that user adoption of AI in mobile banking is significantly influenced by perceived service quality and security, which are key components of trust. While a clear relative advantage of AI features promotes usage intentions, an overestimation of perceived need or excessive simplicity can paradoxically reduce adoption rates, suggesting a nuanced approach to feature design and user education is required.

Project Tips

• When researching user needs for a new digital product, consider how perceived quality and security will impact adoption.
• Explore the 'sweet spot' for feature complexity; too simple might be as bad as too complex.

How to Use in IA

• Reference this study when discussing user adoption barriers and facilitators for technology in your design project, particularly concerning trust and perceived value.

Examiner Tips

• Demonstrate an understanding of how psychological factors like trust and perceived need influence user adoption of technology.

Independent Variable: ["Perceived service quality","Security","Relative advantage","Perceived need","Comfort"]

Dependent Variable: ["Behavioral intentions to use AI in mobile banking","Attitudes towards AI","Comfort with AI use"]

Controlled Variables: ["Nationality (Portuguese consumers)","Context (mobile banking)"]

Strengths

• Large sample size provides statistical power.
• Investigates a combination of factors, including counter-intuitive ones.

Critical Questions

• How would these findings differ in a market with lower digital literacy?
• What are the ethical implications of designing AI to 'feel' necessary versus genuinely being so?

Extended Essay Application

• Investigate the cross-cultural applicability of these AI adoption factors in financial services.
• Explore the long-term impact of AI trust on customer loyalty in banking.

Source

The role of artificial intelligence in mobile banking: decoding portuguese consumers’ perceptions and intentions to engage · Future Business Journal · 2025 · 10.1186/s43093-025-00510-0