At the time of account opening, the internal data available to the organization can be limited.  Additional information can be gleaned from account information, but needs significant accumulation. Ideally, additional third-party data about the customer would be available to enable better identification of fraudulent accounts. Finally, the fraud data is often kept at a transaction level and may not distinguish between account takeover vs new account fraud. All this data needs to be cleaned, joined and transformed into valuable ML features before going into model training. This pre-modeling prep process can be frustrating and time consuming. We are here to help.