Computerized-method and computerized-system for identifying fraud transactions in transactions classified as legit transactions by a classification machine learning model

Computerized-method for identifying fraud transactions in transactions classified as legit transactions by a classification Machine Learning (ML) model, in a financial system, the computerized-method comprising:

• in a system comprising one or more processors and a data store of transactions which are fraud-labeled transactions and legit-labeled transactions, said one or more processors is configured to:
• operate training by:
• (i) retrieving from the data store a dataset of fraud-labeled transactions to train a ML fraud model on the dataset of fraud-labeled transactions, to mark transactions as ‘similar’ or ‘novel’;
• and
• (ii) retrieving from the data store a dataset of legit-labeled transactions to train a ML legit model on the dataset of legit-labeled transactions, to mark transactions as ‘similar’ or ‘novel’;
• deploy a classification ML model, a trained ML fraud model and a trained ML legit model in a computerized environment to identify fraud transactions in transactions which have been classified as legit transactions by the classification ML model,
• wherein the trained classification ML model has been trained on a dataset of preconfigured transactions from the data store, to mark transactions as ‘legit’ or ‘fraud’.