Transaction Scoring API features are costly to businesses. Using transaction scoring to detect and prevent fraud, organizations can minimize financial losses and protect their reputations. Transaction risk scoring is a method that leverages data science, machine learning, and statistical analysis to monitor transactional behavior and identify emerging trends in fraudulent activity. By comparing transactions with models of what is normal for each customer, transaction risk scores help businesses identify suspicious behaviors and flag them for further scrutiny.

Transaction Scoring API Features: Key Benefits Explained

A transaction risk score is a value that indicates how likely a particular transaction is to be fraudulent and is based on a variety of risk factors including transactional data, device information, user behavior, location, and more. This score is used to evaluate the risk of a transaction and can trigger additional authentication processes such as two-factor verification, selfie IDs, or other verification methods to ensure that the transaction is legitimate.

To create a transaction risk score, you need to submit a create assessment API request with the payment details or user data parameters you want to evaluate. The response includes a score and reason code, where applicable. The reason codes are grouped into custom categories for easy reference.

The response also includes a list of rule details that you can use to define the rules that will impact the risk score. This includes the number of services and risk signals called as well as the values of any rules that were triggered for the transaction or user. The overall risk score is calculated as a weighted average, with the values of more significant services and risk signals having a larger impact than less important ones.