Institutional FOMO Syndrome: AI-Based Digital Asset Valuation on Banking Asset Quality and Risk Disclosure
DOI:
https://doi.org/10.56456/jebdeker.v6i2.955Keywords:
Artificial Intelligence, Institutional FOMO Syndrome, Banking Asset Quality, Risk DisclosureAbstract
The global financial transformation triggered by the convergence of digital assets and artificial intelligence (AI) has given rise to the phenomenon of Fear of Missing Out (FOMO) syndrome among banking institutions. These hasty portfolio integration decisions create fundamental challenges for conventional accounting reporting, particularly regarding instrument valuation and risk measurement. This study aims to analyze the impact of adopting digital assets valued using AI on banking asset quality metrics, as well as to evaluate the gaps in the current risk disclosure framework. Utilizing a library research method with a descriptive-critical qualitative approach, this study synthesizes various academic literature, accounting regulatory standards, and industry risk profile reports. The analysis results indicate that the prioritization of crypto assets creates an illusion of liquidity that can instantaneously erode banking asset quality due to extreme market volatility. Furthermore, the use of AI as a valuation instrument (black-box) carries the risk of failing to anticipate market anomalies such as flash crashes, leading to fair value distortions in the balance sheet. In conclusion, the adoption of AI-based digital assets without being balanced by updates to accounting standards triggers systemic vulnerability and information asymmetry. Therefore, it is recommended that regulators and accounting standard boards intervene to formulate AI algorithm audit guidelines, more specific crypto asset classifications, and mandatory narrative and qualitative risk disclosures to maintain the transparency of banking financial reporting.
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