Omniscore is a transaction safety rating that can be used in rule creation and during the manual review process to determine the disposition of an order (approve, decline, or review). It is the output of our next-generation AI model analyzing hundreds of millions of transactions, including their outcomes (such as approvals, declines, chargebacks, and refunds) and their real-time linkages and patterns.
Omniscore differs from previous scores. It incorporates the most predictive components of both our supervised machine learning and our unsupervised machine learning into one score.
Omniscore now includes features like Melissa data and Email Insights in the safety rating. These features help combat fraud attacks that use address manipulation and cross-merchant card testing.
Omniscore uses two types of machine learning — unsupervised and supervised. The unsupervised machine learning focuses on short-term linkages and patterns, enabling it to catch emerging fraud attacks and anomalies that supervised machine learning cannot yet learn about due to the recentness of unseen attack types. Our supervised machine learning technology learns from historical data, such as decisioned orders and their outcomes.
The AI simulates how an experienced fraud analyst would review a transaction. The unsupervised machine learning aspect of Omniscore evaluates the transaction as a human would use instinct. The supervised machine learning aspect evaluates the transaction like the historical experience of seasoned fraud analysts. Together they allow us to calculate one highly-predictive transaction safety rating that can be relied upon for decisioning orders, so that there is less reliance on manual review and reactive fraud rules. The result is catching more fraud and allowing more legitimate transactions to generate revenue.
Transaction safety is the inverse of transaction risk. Omniscore is an indicator of a transaction’s safety ranging from 0.1 (unsafe) to 99.9 (safe). A safe transaction will have a relatively high Omniscore and an unsafe transaction will have a relatively low Omniscore.
Designed to make good decisions more intuitive, the Omniscore can be likened to U.S. academic letter grades that range from F to A. Most transactions will rate in the 80s and 90s (Bs and As). Transactions with issues will rate in the 60s to 70s (Ds and Cs). The riskiest transactions rate below 60 (F).
|
Omniscore |
Grade |
Description |
|
90 – 99.9 |
A |
Very safe, multiple indicators of safety found |
|
80 – 89.9 |
B |
Indicators of safety found |
|
70 – 79.9> |
C |
Typically a mix of safe and risky indicators |
|
60 – 69.9 |
D |
Indicators of risk found |
|
0.1 – 59.9 |
F |
Very risky, significant indicators of risk found |
Omniscore is not a decision. It is a prediction of safety that is used by customers to decision a transaction, either automatically by creating a rule or manually while under review.
Since Omniscore is so accurate in predicting fraud, you can set one rule around it instead of creating a large ruleset.
A suggested rule is to determine the decisioning threshold (at what value the Omniscore is set) based on the decline rate your expected fraud rate:
|
Desired Decline Rate |
Omniscore Fraud Rule |
|
5% |
If Omniscore < 60 Decline |
|
4% |
If Omniscore < 48 Decline |
|
3% |
If Omniscore < 36 Decline |
|
2% |
If Omniscore < 24 Decline |
|
1% |
If Omniscore < 12 Decline |
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