SYSTEMS AND METHODS FOR CUSTOM RANKING OBJECTIVES FOR MACHINE LEARNING MODELS APPLICABLE TO FRAUD AND CREDIT RISK ASSESSMENTS

摘要

A system for analyzing risk using machine learning models may be trained using a data set to generate a risk assessment model that is optimized for metrics commonly used in for financial risk evaluation. The metrics may include Gini and CaptureRate, for example. The system may receive a request for a financial service, and generate a risk assessment by applying the risk assessment model to factors associated with the request. The system may also decide on the request in response to the risk assessment.