<![CDATA[The novelty of this study lies in its qualitative exploration of how Artificial Intelligence is conceptualized, adopted, and integrated into fraud detection systems in digital financial institutions, especially in developing countries. This study also makes Renaldo-Veronica AI-Fraud Behavior Integration Model. This study uses a qualitative exploratory approach, aiming to understand the perceptions, practices, and challenges associated with the use of Artificial Intelligence (AI) for early detection of financial statement fraud in digital financial institutions. The model uncovers how behavioral drivers of fraud (pressure, opportunity, rationalization) intersect with AI adoption drivers (perceived usefulness, ease of use, intention). The Renaldo-Veronica AFBI Model advances fraud theory by integrating psychological and technological constructs in a single analytical framework. Introduces digital rationalization as a modern form of fraud justification, expanding the Fraud Triangle for the AI era. Future research can use quantitative validation of the Renaldo-Veronica AFBI Model using structural equation modeling (SEM) or PLS to test relationships between fraud and AI adoption constructs.]]>
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