Online Fraud Prevention Tools

Geolocation for Online Fraud Prevention

IP Intelligence Insights for Online Fraud Prevention Solutions

Online fraud can take many shapes, from account takeovers on banking or social media sites to card-not-present fraud on retail sites. As companies look for innovative ways to offer a safe and secure environment for their online customers, they continue to turn to a single technology that has been proven to reduce online fraud by more than 90 percent.

Digital Element’s NetAcuity® IP Intelligence and geolocation technologies provide information about online users including location, connection type, and proxy data to name a few. All of this information is collected solely from a user’s IP address, providing strong authentication of user identity without violating user privacy. This accurate and reliable information about online users is helping to break down the anonymity barriers of the internet and is proving to be an integral and necessary part of any online security or fraud prevention strategy.

How to Prevent Online Fraud with IP Intelligence

IP intelligence and geolocation technologies can play a key role in keeping companies safe from the risk of fraud, but how does online fraud prevention with NetAcuity work? Here are some of the key factors that make Digital Element’s online fraud prevention tools work.

  • Balance Risk Management – Leverage geolocation information to determine which transactions to review and which to approve, allowing you to accept legitimate customers and decrease losses from fraud
  • Shore Up Fraud Controls – Leverage real-time user information to strengthen identity verification, such as flagging account access from unusual or high-fraud areas
  • Detect Proxies – Identify access from proxies, which are notorious for allowing users to remain anonymous and avoid detection – a major red flag in online fraud detection and prevention
  • Strengthen Digital Profiles – Expand user profiles by adding IP Intelligence-based attributes that allow detection of out-of-the-ordinary access and transactions based on normal user patterns

Types of Online Fraud

Ad Fraud

Ad fraud occurs when a person or bot imitates a legitimate user to make a fraudulent impression, whether that be viewing, clicking, or converting on a web asset to generate revenue for themselves and manipulate the results on a digital advertising campaign. NetAcuity is an ad fraud solution that provides ad fraud detection to prevent the manipulation of digital ad campaigns.

CTV Fraud

CTV Fraud is a specific type of ad fraud that manipulates the number of impressions on digital advertising campaigns on connected television or CTV. With NetAcuity, advertisers can detect and prevent CTV fraud.

Mobile App Fraud

Mobile app fraud can refer to fraudulent apps created by bad actors to gain access to users’ personal data. It can also refer to other types of fraud leverage through mobile apps, such as making purchases with stolen credit card information.

Account Takeover Fraud

Account takeover fraud refers to when a bad actor takes over a user’s account to perform fraudulent activities. These can include stealing payment information, making fraudulent purchases, or attempting to gain access to sensitive data. It can also entail using a user’s personal information to open a new account.

Card-Not-Present Fraud

Card-Not-Present fraud refers to when a fraudster uses stolen or fraudulent credit card information to make purchases online without the physical card present. For example, if a fraudster gains access to credit card information but not the physical card itself.

Helpful Links

Blog Article

Digital Element Adds Deterministic IP Address Metadata to Nodify

Get unmatched insights into anonymous traffic to understand and manage online activities effectively.

Blog Article

Fight Ad Fraud with IP Intelligence Data

IP data can help teams detect fraudulent clicks that originate from click farms or bots.

Case Study

AppsFlyer Case Study

AppsFlyer trusts the accuracy of Digital Element’s IP address intelligence data to improve mobile attribution and help prevent fraud.

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