Fraud & Risk
Detect Fraud Without Adding User Friction
Digital Body Language Is The Key To Detecting The Most Difficult Fraud Typologies
Identity Verification Via Digital Body Language
Moonsense provides actionable signals and access to the underlying data with the flexibility and control customers need for the best outcomes.
Each user's unique behavior patterns form a virtual signature, allowing fraud teams to verify and authenticate users, device usage, account activity, and more. How quickly someone enters their password, how hard they press on a touch screen and style of swiping are all data points for validating a user.
Control Over Risk Scoring
Eliminate the rigid pre-set scoring systems that are commonly associated with fraud and risk solutions. With Moonsense, you can determine how to score risk for accounts and transactions based on the behavioral data selected by your team.
Protect User Privacy
With Moonsense, you have the flexibility to manage and store data in compliance with your company's best practices and privacy standards. We support multiple deployment models, ranging from secure storage in the Moonsense Cloud to direct data transfer to your own internal systems.
Build What Matters
Data acquisition and related solutions require true heavy lifting (we would know). Resources lost to creating internal solutions—hiring, additional salary, significant person hours—all come at the expense of your priority projects and overall business.
Moonsense's real world perception capabilities are redefining possibilities for Bureau. The sensor data accelerates our real-time ability to fight fraud across industries and expands horizons for us.
Difficult to Detect Fraud Attacks
Leveraging User Behavioral and User Network Intelligence data is key to detecting difficult fraud typologies without adding user friction.
Account Opening Fraud
Account opening fraud takes place when a bad actor steals fragments of information from various real individuals to create a composite “synthetic identity.” Because there is no one consumer victim to report a stolen identity, these synthetic accounts often go undetected.
Profile the behavior of legitimate users, based on signals including keystrokes, various touch events, and more, to flag malicious users or bot activity that falls outside of normal expected human behavior.
An account takeover occurs when an attacker uses valid credentials to log into an account that they do not own. This is typically accomplished through stolen or leaked credentials, at scale.
By collecting user behavioral data there is a baseline that can be established across all users. Fraudulent activity typically falls outside of the baseline. Taken a step further you can build individual user behavior profiles.