Abstract: A method and computer-implemented process for identifying behavioral anomalies and risk factors is disclosed. The method includes (A) obtaining, by a risk assessment module, first data associated with activity information of a digital identity with respect to a digital development tool; (B) associating, by the risk assessment module, second data with a first risk tag based on a risk-anomaly matrix; (C) generating, by the risk assessment module, a first predicted anomaly using a machine learning module trained using a first training set, wherein the first training set comprises the second data and the first risk tag; (D) associating, by the risk assessment module, the first predicted anomaly with a second risk tag based on the risk-anomaly matrix; and, (E) transmitting, by the risk assessment module, a notification associated with at least one of (i) the anomaly and (ii) the predicted anomaly, and the digital identity.