In today’s digital world, we understand preventing and stopping automated fraud. With increasing numbers of account takeovers, automated attacks, and new account fraud, our integration partnership with NuData Security, a Mastercard company, offers you the technology necessary to validate your real end users from fraudsters.
How does it work?
NuDetect is a behavioral analysis product that utilizes tracked end user behavioral data to determine fraudulent activity and assigning it a “score.” As an admin user, configuring your NuDetect settings gives you the ability to set and enforce a score threshold that will trigger a risk event on suspicious and fraudulent activity. For example, if an end user’s activity is given a score of 300 (red) and the institution has a score threshold of 225 (yellow), then the end user’s session would require extra authorization through 2FA.
- Score configuration
The numeric score returned by Mastercard NuDetect indicates the level of risk. Scores that are equal to or above the configured threshold triggers a risk event that is different depending on the location.
- Suspicious traffic: A score equal to or above this number triggers the end user to complete 2FA (even if the end user previously checked Remember Me). While Mastercard recommends setting a score at or less than 200, we suggest you start with a score slightly higher based on your institution’s existing traffic.
Fraudulent traffic: A score equal to or above this number prevents the end user from logging in to Banno Apps. This score should be set higher than the Suspicious traffic score and high enough that only obvious fraudulent activity is blocked. If login is blocked for a suspected fraudster or bot, an error message displays on the login page stating, We couldn’t find you. Please check the information that you provided and try again, with the option for the end user to select a Call now button or OK button. In the rare event that a legitimate end user is blocked, there’s no way to unblock the individual, because our typical methods—–manually resetting enrollment or self-serve account recovery—–are unavailable. Instead, the end user needs to work with your institution to understand why they have a high NuDetect score so they can take measures to lower their score.
- A score equal to or above this number prevents the end user from proceeding to enroll. When recovery fails, the following 403 error displays to the end user: Oops! Something went wrong on our end. Please try again. While Mastercard recommends setting a score at or less than 500, we suggest you start with a score slightly higher based on your institution’s existing traffic.
- A score equal to or above this number prevents the end user from recovering an account. When recovery fails, the following 403 error displays to the end user: We couldn’t find that for you. Please check the information that you provided and try again. If you haven’t enrolled yet, try that instead. While Mastercard recommends setting a score at or less than 500, we suggest you start with a score slightly higher based on your institution’s existing traffic.
- High risk prompt
- A score equal to or above this number prevents the end user from proceeding through the high risk action, deauthorizes the device, and forces the user back out to the login to reauthorize by logging in. By deauthorizing the device, the user will be forced to re-enter a new 2FA code. Traffic passing through the High Risk Prompt will be displayed as “AuthorizeHighRisk”. For a list of high risk actions please view this link.
As you become more comfortable with the NuDetect platform, we suggest you eventually adjust scores closer to Mastercards’ recommendations.
Resources & training
In addition to utilizing NuDetect within Banno People, a separate dashboard through NuDetect displays detailed analytics surrounding end user interactions in your digital environments. This video demo will help train you on how to drill into events and their impacts, filter data, build rules using the configuration engine, and much more. You can also watch the video demo separated into the following sections:
Additionally, there is a monthly NuDetect orientation call where employees from Jack Henry and MasterCard discuss the product. Sign up for orientation here.
- How does a blacklisted IP impact configured NuDetect scores?
- After adding a blacklist IP, Mastercard adds an automatic 500 score on top of the configured score. For example, if you have a 200 score set at login, it will effectively be a 700 score if it’s blacklisted.
- How does an end user lower their score?
- Please refer to your NuDetect documentation for information on score responses and behavioral signals.
- What happens to a user if they exceed a set score on a high risk prompt?
- After the user tries to enter their password, they will receive a 403 error stating: “For security purposes, you’ll need to sign-in again.” They will then be pushed back to the login and their device will be de-authorized. Meaning they will need to re-authorize their session and the device by entering their password and 2FA code.