Abstract: A method for providing anomaly detection to facilitate individual risk assessments is disclosed. The method includes compiling raw data from a data source, the raw data corresponding to a plurality of advisors; parsing the raw data to extract a data element; generating a structured data set based on the extracted data element; determining, by using a model, an anomaly value for each of the plurality of advisors, the anomaly value relating to a probability of an anomalous action; computing, by using the model, a risk score for each of the plurality of advisors based on the corresponding anomaly value; and generating a report for each of the plurality of advisors, the report including corresponding information that relates to the anomaly value and the risk score.