Machine-Learning-Based Identification of Financial Transaction Supervision Events

Abstract

There is provided a processor-based system of identifying a financial transactions supervisory event, the processor configured to: utilize machine learning models to classify a plurality of financial transactions of an organization, thereby resulting, for each of the financials transactions, in one or more respective generated transaction attributes, apply a predefined transaction rule to the classified transactions, the applying comprising: evaluating a transaction matching criterion that is at least partially based on one or more of the respective generated attributes of the classified transactions, the classified transactions matching the transaction matching criterion thereby constituting a set of selected transactions, determining a selected transactions characteristic (STC), based on, one or more transaction characteristics of the transactions constituted in the set of selected transactions, evaluating a supervisory event criterion (SEC), the supervisory action criterion being based on the STC, and identifying a financial transactions supervisory event, responsive to positive evaluation of the SEC.

CPC Classifications