Kochava adds new feature to validate installs and eradicate mobile advertising fraud

Mobile advertising fraud continues to be a growing problem for the ad industry. Now, Kochava, the measurement solutions provider for connected devices, has launched Checksum – a feature that validates installs and payloads ahead of attribution. In addition, the company added three new views to its Fraud Console suite for mobile ad fraud visualization.

“We’ve been identifying data abnormalities deemed potentially fraudulent for the past three years. During this time, we’ve been developing tools to identify fraud based on patterns,” says Grant Simmons, Director of Client Analytics at Kochava. “From what we’re seeing now, 84% of fraudulent clicks come from the 10 highest volume networks; and approximately 27% of installs on these networks have been flagged as fraudulent.”

The company explains that fake installs usually try to mimic human behaviour. This makes it significantly harder to identify them. Kochava’s Fraud Console automatically scans for suspicious patterns and flags such activities.

Simmons adds that marketers are used to looking for installs or conversions.

“They’re not used to questioning what they see. While those rates may initially look normal, there’s a good chance that at least a portion of the installs or conversions are fraudulent,” he adds.

The company has been working on a range of automated ad fraud detection and prevention tools over the last 12 months. Checksum has been built to validate install receipts. It does this by comparing them with receipt identifiers. If an install doesn’t match, it is dropped ahead of attribution. This helps to prevent fraudulent installs.

Clients can choose from two types of Checksum filters – strict, which drops any and all unverifiable installs regardless of SDK version, or lenient, which only drops installs that do not pass for a valid SDK.

In addition to Checksum, Kochava has added three new mobile ad fraud algorithms to its Fraud Console – Click Flooding, Time-to-Install (TTI) Outliers and TTI Distribution.

Visualizations for Click Flooding enable advertisers to flag this type of ad fraud, which happens when networks flood their channels with clicks to claim attribution.

Meanwhile, TTI Outliers records the time between a click and an install, making fraud more visible. TTI Distribution highlights networks which had a higher number of installs outside of the nirmal range.

Simmons added, “Because the mobile ecosystem is unregulated, everyone in the industry must use the resources available to mitigate fraud and report within the ecosystem those entities they identify as fraudulent.”