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Real time fraud prevention

Optimize Acquisition & Reduce Wastage

TTI Report

TTI report or Time to install report gives the time difference between when the user clicked on the ad and the time when he first opened the app (the install postback is sent). Time to install is very important in identifying whether the traffic from a traffic fraud or not. If the size of the app is significant and the TTI is very low then it signifies click injection or organic stuffing. If TTI is very high then it signifies click spamming. Also much depends upon the ration of the installs with low and high TTI. If large volume of the installs are coming in the high TTI range then it generally is clear case of organic stuffing. mTraction FaaS not only highlights conversions with TTI fraud but also the sources adding to this kind of fraud.

mTraction FaaS | Summary Dashboard

mTraction FaaS provides you an interactive dashboard to check the fraud status of the traffic on your app in a single view. This is mTraction FaaS’s Summary Dashboard, which provides you a quick overview of the top affected campaigns and topfraud sources on your app. Also, it tells you the top reason codes or the fraud reasons which are leading to fraud on your app.

Geographic Matching

This tracks anomalies between click and install geographic distance. Generally users clicks and installs within a short duration and within a short distance. Our matching report homes in on mismatching geographic distance and highlights this for blacklisting.

mTraction FaaS | Summary Dashboard

mTraction FaaS provides you an interactive dashboard to check the fraud status of the traffic on your app in a single view. This is mTraction FaaS’s Summary Dashboard, which provides you a quick overview of the top affected campaigns and top fraud sources on your app. Also, it tells you the top reason codes or the fraud reasons which are leading to fraud on your app.

mTraction FaaS | Summary Dashboard

mTraction FaaS provides you an interactive dashboard to check the fraud status of the traffic on your app in a single view. This is mTraction FaaS’s Summary Dashboard, which provides you a quick overview of the top affected campaigns and topfraud sources on your app. Also, it tells you the top reason codes or the fraud reasons which are leading to fraud on your app.

Incent Fraud Report

mIncent fraud report highlights if there is any incent mixing happening on the non-incent traffic type campaign. This is one of the most prevalent kind of app fraud in which the publishers mix the incentivised traffic to achieve campaign KPIs and show high conversion rate on the campaigns. traction FaaS highlights the subids providing incent traffic on the non-incent campaigns.

Device Matching

There are two major ways fraud occurs at a device level: Invalid device Ids: Our system has identified over 50+ different Id variants that is automatically filtered out from our system. Modified device Ids: Some people are still using invalid Ids, ranging from the phone number, IMEI (which is discouraged by the industry) and hashed devices ids.

mTraction FaaS | Summary Dashboard

mTraction FaaS provides you an interactive dashboard to check the fraud status of the traffic on your app in a single view. This is mTraction FaaS’s Summary Dashboard, which provides you a quick overview of the top affected campaigns and topfraud sources on your app. Also, it tells you the top reason codes or the fraud reasons which are leading to fraud on your app.

Organic Stuffing Report

Organic stuffing report highlights the click injection and organic stuffing during the user acquisition. This happens close to 10% of the times when the user acquisition process is aggressive and is done from non-standard sources. This organic stuffing is a fraud as it is more of a cannibalising on the organic sources of traffic and hence this fraud leads to attribution of a high quality conversion to a paid source instead of a non-paid organic source.

multi type fRAUD DETECTION

Click Stuffing/Spamming

Sending bulk and huge quantity of
clicks

Spoofing

The user’s device and browser were manipulated
to resemble a different device or browser.

Device Farms

Building a large segment of Fake
Device IDs

BOT Traffic

Automated traffic
–Impressions/Clicks/In-App activity

APK Scams

Hacking the app including
attribution

Ad Stacking

Multiple ads stacked together to trigger multiple
clicks at a time from users

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