Risk Scores are an easy way to assess the risk associated with a transaction. Viewing a transaction as high, medium or low risk can simplify approval processes and enhance business rules regarding fraud. Scoring can also help organizations view trends in their transactional data to gain insights into customer behavior.
ExpectID Score allows you to create a risk-based score to enhance identity verification and evaluate customer behavior. ExpectID Score is customizable, allowing identity attributes and fraud indicators to be assigned values and ranked within fraud thresholds that you control. Results and decisioning are presented in real-time, reducing friction while providing analytical insights into transactions.
Real Time Delivery. Real Time Control.
Just like Expect ID, ExpectID Score is delivered in real-time. Decisioning is performed instantly from the score and users have the ability to view the identity attributes that created the score. Transactions can be passed, failed or escalated from a score or individual ID Notes depending on the rules that you define.
Adaptive Scoring allows you to create scoring models that fit your business rules and adapt to evolving fraud tactics. Identity attributes and fraud indicators can be assigned values based on risk and placed into risk thresholds that you score.
Enhance Risk Evaluation
ExpectID Score complements Expect ID’s delivery of identity attributes by offering an additional view into transactions. Increase your decisioning power by viewing an identity as high, medium or low risk in addition to viewing the identity attributes individually that created the risk score.
Meet Compliance Regulations
ExpectID Score gives you the ability to group customers into high, medium and low risk levels. These levels can be used to evaluate overall risk profiles and meet regulatory compliance requirements for creating a risk-based approach to KYC and AML guidelines.
Gain Customer Insights
ExpectID Score helps you to create risk profiles and develop trending analysis for different customer types. By utilizing score data from transactions, businesses can better perform customer modeling to improve predictability of customer behavior and reduce risk.