What is Omniscore?
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, review). It is the output of Kount's next-generation AI model analyzing hundreds of millions of transactions—their outcomes (including approvals, declines, chargebacks, refunds, etc.) and their real-time linkages and patterns. The AI weighs the risk of fraud against the value of the customer and provides an evaluation (approximating an experienced human fraud analyst) in the form of a score which helps identify good customers, bad customers, and fraudsters.
Omniscore differs from previous scores in that it incorporates the most predictive components of both our supervised machine learning and our unsupervised machine learning, as well as other predictive factors, into one score.
The result is a score that is twice as good at catching fraud and minimizing false positives as any score Kount has ever produced.
The best of both worlds in one score
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—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 Kount 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 true fraud and allowing more good transactions to generate revenue.
Interpreting Omniscore
Transaction safety is the inverse of transaction risk. Omniscore is an indicator of a transaction’s safety ranging from .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 |
It is important to note that Omniscore is not a decision. It is a prediction of safety that is used by customers to decision a transaction (either automatically via creating a rule or manually while under review).
Creating a fraud rule with Omniscore
Since Omniscore is so accurate in predicting fraud, you can set one rule around it instead of creating large rulesets targeting fraud.
A suggested rule of thumb is to determine the decisioning threshold (at what value the Omniscore is set) based on your desired decline rate:
|
Desired Decline Rate |
Omniscore Fraud Rule |
|
5% |
If Omniscore < 61 Decline |
|
4% |
If Omniscore < 49 Decline |
|
3% |
If Omniscore < 37 Decline |
|
2% |
If Omniscore < 25 Decline |
|
1% |
If Omniscore < 13 Decline |
The decisioning threshold can be adjusted after analyzing decline and chargeback rates, and any other measures of performance important to the merchant.
Testing Omniscore without affecting transactions
A customer can create a "No Change" rule using Omniscore. This will allow the customer to watch how the score performs while not impacting actual transactions. While Kount is confident that Omniscore should be the only score used for fraud rule creation, some customers will want to test it. After three months (enough time for outcome data to be collected), the customer will be able to compare performance with and without Omniscore.
Omniscore Webinar
Want to learn more about Omniscore? Check out this webinar featuring Tricia Phillips Sr. VP Product and Strategy, Josh Johnston Director of AI Science and Kelly Reynolds VP Customer Success as they dig deeper on what Omniscore is and how to implement it in your payments fraud prevention program.