Evidence map›Paper›PMID 42376438›Full record

ArticleFrontiers in artificial intelligence2026

AI-driven financial risk management in complex mobile economies: a contextual-technology fit and security reassurance model.

Ziwen Jiang, Xu Jiang

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Ziwen JiangXuBeihong Art Academy, Shanghai Maritime University, Shanghai, China.
Xu JiangAcademy of Arts & Design, Tsinghua University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid evolution of artificial intelligence in financial technologies has fundamentally reshaped risk management within complex socio-economic systems. However understanding how users build transactional trust within high-density mobile economies remains a critical challenge. This study integrates technology fit and reassurance confirmation theories to investigate user security perceptions in complex micro-economic environments. A field survey was conducted aboard a mega cruise vessel yielding 329 valid responses that were analyzed through structural equation modeling. The empirical findings reveal that contextual technology fit significantly improves secured sensory interaction and perceived architectural quality. Perceived architectural quality acts as a vital structural intermediary that updates security expectations and enhances reassurance confirmation. Ultimately reassurance confirmation and secured sensory interaction are identified as the primary drivers of overall trust and satisfaction. This research provides a significant conceptual advance by shifting the narrative of technology acceptance from simple functional efficiency to a comprehensive framework encompassing spatial safety and micro-financial risk perception. The conclusions offer actionable strategies for system operators to leverage artificial intelligence interfaces for regulatory compliance and systemic security control in modern financial ecosystems.

Indexed as

complex financial systemscontextual-technology fitreassurance confirmationsecuritytransaction risk management

Identifiers

PMID42376438
PMCPMC13311101

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.