Abstract

Our research focuses on studying blockchain transactions in financial metaverse to estimate their risk. By focusing on high -risk transactions, such as phishing and scams, we modeled the risk with high accuracy. We use a quantitative approach to scrutinise anomalies and fraud in blockchain transactions in the metaverse. Our analysis is based on the data supplied by the Open Metaverse Foundation. The data covers the timeframe from January 1, 2022, to December 31, 2022. This data has been meticulously crafted to illustrate the intricate and ever -evolving nature of blockchain activity in the Open Metaverse. Quantitative data reveals that new users conduct fraudulent transactions during unconventional hours. To avoid being traced, fraudsters create new accounts f or each fraudulent transaction, which they carry out in the evening when there is less human control over the metaverse. The timing of the transaction also contributes to the overall risk. The amounts of fraudulent transactions are, on average, slightly lo wer than normal to avoid raising suspicions

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