ML-aaS for Advertisers
Advanced Machine Learning Algorithms
to deterministically detect invalid traffic.
State of the art Generalised Discriminant Analysis(GDA), Network Analysis and Graph Theory and other advanced machine learning algorithms.
Abnormal Behaviour Detection
First of the kind, fraud coefficients namely Alpha, Beta & Gamma makes our reports interpretation easy and fast.
Technology would help risk professionals audit their data assets without any conflict of interest.
Cyber Fraud as a problem cannot be solved by technology itself, it needs a cyber technology intervention.
SINGLE TEST TO DETERMINISTICALLY DETECT
PRESENCE OF FRAUDULENT ADVERTISING TRAFFIC
Auto Identify Anomalous Consumer Behaviour/Clusters
1. Evaluate behaviour weekly/monthly
2. Highlight anomalies
3. Check your traffic for quality
Deterministically Differentiate Anomalous Behaviour
Self visualise bot traffic, engaged and disengaged users.
Study the fraud clusters in size and strategise to reduce cluster size
Save weekly reports for reference
Highlight and Identify Source
Self identify bot traffic sub/sources.
Self visualise fraud traffic reduction on source takedown.
DETERMINISTIC TEST FOR ORGANIC HIJACKING
Com Olho Method
Studying time to install or landing behaviours is a good way to estimate amount of organic traffic that is being hijacked. This allows the advertiser to understand if they are at a risk of financial and performance losses. This method is a widely adopted method among marketers.
Studying time to install or landing behaviours is indeed a good way, but because of its simplicity, it can be easily programatically manipulated making the invalid traffic valid.
DETERMINISTIC TEST FOR BOT MIXING
The industry is deploying fraud teams to look into wide variety of data points, in order to highlight abnormality or finding organised data structures in order to understand fraud. For bot mixing, there isn’t any method available to segregate good and bad traffic.
Some of the manual research efforts done :
Com Olho Method
Bot traffic generated using device farms, SDK Spoofing, APK drops is often delivered with almost human mimicking attribution data. We deploy state of the art patented technology to distinguish valid and invalid traffic.
Uncover digital fraud plaguing your business using Nex-Gen Tech
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