At the heart of SCDO’s blockchain analytics is its anomaly detection system. This system leverages machine learning and artificial intelligence to identify patterns that deviate from the norm.

These anomalies can include unusual transaction sizes, atypical transaction timings, or abnormal frequency of transactions between certain accounts.

Machine learning models are trained on vast datasets, encompassing both legitimate and illegitimate transaction patterns.

As these models are exposed to more data, they become increasingly adept at distinguishing between regular and suspicious activities.

This continuous learning process enables SCDO to stay ahead of emerging money laundering techniques, adapting to new threats as they arise