stdClass Object
(
    [id] => 16785
    [paper_index] => 202506-07-022818
    [title] => ARTIFICIAL INTELLIGENCE IN FINANCIAL ANALYSIS
    [description] => 
    [author] => Sudeep Tholar, Sowmya D.S
    [googlescholar] => 
    [doi] =>  https://doi.org/10.36713/epra22818
    [year] => 2025
    [month] => June
    [volume] => 12
    [issue] => 6
    [file] => fm/jpanel/upload/2025/June/202506-07-022818.pdf
    [abstract] => This study examines the role of artificial intelligence in financial analysis through a comprehensive survey of 240 respondents across various age groups and educational backgrounds. Using chi-square and regression analyses, the research investigates relationships between demographic factors, AI understanding, and attitudes toward AI financial applications. Key findings reveal a significant association between age group and trust in AI financial systems (χ²(20) = 44.9, p = 0.001, Cramer's V = 0.216), with middle-aged respondents (45-54 years) demonstrating the highest trust levels. Additionally, AI understanding significantly predicts comfort with AI analyzing personal financial data (β = 0.167, p = 0.016), though the effect is modest (R² = 0.0240). The study identifies investment management (24.6%) and fraud detection (22.9%) as the areas most improved by AI, while revealing substantial concerns regarding algorithmic bias (65.8% moderately to extremely concerned) and data security (only 4.6% expressing complete trust). These insights provide valuable guidance for financial institutions implementing AI solutions and highlight the importance of transparency and education in fostering AI adoption.
    [keywords] => : Artificial Intelligence, Financial Analysis, Trust, Algorithmic Bias, Transparency, Consumer Attitudes
    [doj] => 2025-06-29
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 33
    [journal_id] => 7
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Economics, Business and Management Studies (EBMS)
    [short_code] => IJHS
    [eissn] => 2347-4378
    [pissn] => 
    [home_page_wrapper] => images/products_image/2.EBMS.png
)
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