Evidence map›Paper›PMID 40873495›Full record

ArticleFrontiers in artificial intelligence2025

The impact of artificial intelligence on behavioral intentions to use mobile banking in the post-COVID-19 era.

Johannes Schrank

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Johannes SchrankInternational College, Khon Kaen University, Khon Kaen, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This quantitative research investigates the determinants of behavioral intentions to use mobile banking in the post-COVID-19 era. The study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) framework by incorporating two key characteristics of AI, i.e. perceived intelligence and perceived anthropomorphism. Methods: It uses the UTAUT as a theoretical framework, and extends it by integrating core features of AI. Data has been collected from 412 respondents in Thailand, and structural equation modeling has been employed for the data analysis. Results: The findings reveal significant positive effects of performance expectancy, effort expectancy, social influence, facilitating conditions, trust, perceived privacy, perceived intelligence and anthropomorphism of AI on users' behavioral intentions to use mobile banking. Price value, habits, and perceived security do not significantly influence behavioral intentions. The results highlight the transformative potential of AI technology in the mobile banking industry as consumers' behaviors are greatly influenced by perceived intelligence and anthropomorphism. Discussion: The positive impact of perceived intelligence and anthropomorphism indicates that consumers value advanced, human-like interactions with AI. M-banking platforms may focus on developing AI systems that offer intuitive, intelligent, and emotionally engaging experiences. Financial institutions may invest in AI that can analyze user data to offer personalized financial advice, predict future needs, and automate routine tasks effectively.

Indexed as

artificial intelligencefinancial servicesFinTechmobile bankingUTAUT

Identifiers

PMID40873495
PMCPMC12378666

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.