DEFENSESTORM BLOG

Fraud Prevention Releases: User Behavior Analytics (UBA) model in GRID Active

Monday, November 13th, 2023

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Cyber security risk management solutions from DefenseStorm.

GRID Active Fraud Prevention is powered by machine learning and helps financial institutions to proactively detect fraud and monitor suspicious non-monetary activities, complementing rules-based approaches to detect fraudulent activities.

GRID Active Fraud Prevention has added a User Behavior Analytics (UBA) model, powered by machine learning, to help better proactively detect fraud. By tracking individual user data and activities to identify suspicious deviations from the user’s normal behavior, financial institutions can monitor suspicious non-monetary activities for individuals to complement rules-based approaches and detect fraudulent activities.  With this enhancement, customers will see an alert within GRID Active based on their defined risk factors.

A sample of the risk factors for fraud detection are defined as follows:

New Device/OS/Browser

  • An account was accessed with a device/Operating System (OS)/browser not used by this person before.

New City/State

  • An account was accessed from a city/state this person has not logged in from before.

Improbable Travel

  • An account was accessed from two locations in a short period of time where it would not have been possible for the person to travel between them.

Unusual Login Time of Day

  • An account was accessed at a time of day that is unusual for this person.

Changed Password/email address/phone number.

  • An account password, email, or phone number was changed along with another risk factor.

The machine learning model is used for tracking, collecting, and assessing individual user data and activities to find fraud that might be detectable by changes to an individual user’s behavior. If the model detects a change from what has been seen before across any of these parameters, a risk score will be generated, and if the cumulative score is over a configurable threshold, GRID Active triggers an alert.

WHY DEFENSESTORM FRAUD Detection and Prevention

Built for Banking, GRID Active Fraud Prevention provides continuous monitoring and alerts from data across the network, online banking platform, and core to proactively detect and stay ahead of evolving fraud threats and stop cyber fraud before funds leave the organization. Integrating Information Security and Fraud departments in a single platform, we defend against threats, including fraudulent account opening/loan applications, account takeovers, payment fraud, money laundering, and internal fraud.

DefenseStorm is committed to providing solutions that stay ahead of the ever-changing threat landscape. We continually innovate and update our technologies to ensure that our clients receive the best possible protection against both known and emerging threats.

Adam

Adam Barrett

Sr. Product Manager, Fraud Detection

Adam is the DefenseStorm Fraud Geek with an extreme passion for protecting financial institutions and the people who trust them to provide a safe banking experience. He is currently the Senior Product Manager for DefenseStorm GRID Active Fraud Detection product. With 25 years of experience in banking operations, fraud and risk, you would think he’s seen it all, however, the constantly evolving schemes keep him motivated to stay in the fight.