Abstract :

The Rapid Development Of Artificial Intelligence (AI) Is Bringing Significant Changes To The Way Financial Information Is Accessed, Analyzed And Used For Decision-making. AI-based Financial Tools Can Process Large Amounts Of Information And Provide Recommendations Within A Short Period, But The Usefulness Of These Systems Ultimately Depends On How People Understand And Respond To Their Recommendations. In This Context, The Present Study Examines The Role Of AI Explainability, Algorithmic Trust And Financial Literacy In Human–AI Financial Decision-making. The Study Focuses On Whether Individuals Are More Willing And Able To Rely On AI-supported Financial Decisions When They Can Understand The Basis Of AI Recommendations, Trust The Algorithms Involved And Possess Adequate Financial Knowledge. Primary Data Were Collected From 320 Respondents Through A Structured Questionnaire Using A Five-point Likert Scale. The Reliability Analysis Indicated Satisfactory Internal Consistency, With Cronbachs Alpha Values Above The Generally Accepted Threshold Of 0.70 For The Study Constructs. The Findings From Descriptive And Correlation Analyses Indicated Positive Associations Among AI Explainability, Algorithmic Trust, Financial Literacy And Human– AI Financial Decision-making. Multiple Regression Analysis Revealed That The Three Independent Variables Jointly Explained 64.0% Of The Variation In Human–AI Financial Decisionmaking (R² = 0.640; Adjusted R² = 0.636). Among The Predictors, Algorithmic Trust Showed The Strongest Positive Influence (β = 0.38, P < 0.001), Followed By AI Explainability (β = 0.31, P < 0.001) And Financial Literacy (β = 0.24, P < 0.001). The Overall Regression Model Was Statistically Significant (F = 187.42, P < 0.001). These Findings Suggest That Technological Capability Alone Is Not Sufficient To Ensure Effective AI-supported Financial Decisionmaking. Users Need To Understand The Reasoning Behind AI-generated Recommendations, Have Confidence In The Reliability And Fairness Of The Algorithms, And Possess Sufficient Financial Knowledge To Evaluate The Information Provided By AI Systems. The Study Concludes That Effective Human–AI Collaboration In Finance Requires A Balanced Approach In Which Technological Innovation Is Supported By Transparency, Trust And Informed Human Judgement. The Findings Provide Useful Implications For Financial Institutions, Fintech Companies, Policymakers And AI Developers In Designing Financial Technologies That Are More Understandable, Trustworthy And Responsive To Users Needs.

Published:

19-9-2026

Issue:

Vol. 26 No. 9 (2026)

Page Nos:

265-284

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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