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August 20, 2014

IDology Unveils ExpectID Score

IDology, a company that offers solutions to identity verification and fraud prevention, announced the availability of ExpectID Score, a new real-time, risk-based scoring feature for the ExpectID suite of identity verification solutions.

Risk Scores are quick ways 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. ExpectID Score allows one to create a risk-based score to enhance identity verification and evaluate customer behavior. It is customizable, allowing identity attributes and fraud indicators to be assigned values and ranked within fraud thresholds. Results and decisioning are presented in real-time, reducing friction while providing analytical insights into transactions.

Delivered in real-time, ExpectID Score helps customers reduce risk, improve compliance and gain more insights into transactions.

"Fraud tactics are constantly evolving, and different industries have fraud challenges that are unique to them. ExpectID Score with Adaptive Scoring will help organizations gain a broader view of the fraud tactics that they experience on a daily basis and be able to adapt to them more quickly," John Dancu, CEO of IDology said in a statement.

ExpectID Score utilizes adaptive scoring that gives organizations the ability to create custom scoring models derived from identity and fraud attributes that can be easily adapted to changes in their business rules.

Companies from a wide range of industries can now enhance their risk evaluation process by adding ExpectID Score to ExpectID's Identity verification solutions. This gives risk managers more options to pass fail or escalate transactions and group identity risk factors into distinct risk categories.

"We wanted to de-mystify the whole scoring process and bring a new level of transparency and utility that will help organizations really understand the underlying factors that create a score and ultimately strengthen their risk models with insights gathered from scoring,” added John Dancu.




Edited by Maurice Nagle
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