Why the industry needs a Fraud-Database

Why the Industry needs a Fraud Database

6 Min Read

Its no secret – The industry is plagued by AdFraud. But what many don’t know is that one of the reasons why Fraud is still so problematic as we struggle with a lack of transparency, data insights and automation. In this post I want to cover the underlying reasons of fraud and why it is still such a big problem and also give a proposed solution on how to automate rejections and drastically reduce fraud.

The underlying reasons of unresolved Fraud issues

Whether you are in Affiliate, Programmatic RTB or buy traffic on a CPC basis. Fraud is ubiquitous and hard to tackle. Here are are the reasons why:

• Traffic Rebrokering
• Lack of Datapoints (Advertiser Data vs Networks Data)
• Lack of Trust and Transparency (Advertiser does not share Customer Details like Emails)
• Lack of Automation (exchanging manual Excel Lists for rejections is still common)
• Differences between IP-Databases (Different Fraud Solutions have different databases and algorithmns)

Why we need a Anti-Fraud Database based on Advertiser Data ?

To overcome the known problems we need a solution that is privacy friendly, realtime, works across all industries, easy to implement and has the ability to share the missing data points with the traffic source without compromising the real identity.

Further it should be Advertiser specific as each advertiser has different settings, solutions etc. in place. As you can see and certainly most of us have already experienced its a problem that cannot be solely solved from the network / agency side.

What problem does a Anti-Fraud Database solve ?

1. Realtime Click Prevention on users that are fraudulent or already converted
2. Very high rejection accuracy as the Data is selected by the Advertiser
3. DataInsights without sharing confidential Data (e.g. Email addresses)
4. Data Privacy Issues (GDRP / COPPA) to collect and store data (e.g. IP-Addresses etc.)
5. Rejection Automation for Conversions as Data can now be synchronized between parties in realtime.
6. Adding more Transparency and Trust between Advertisers and Partners

Benefits for Advertisers

A Fraud Database filled with Hashed Values from IP-address, Device IDs, Domain Data is also highly beneficial for the advertiser.

1. Free of Charge for anyone wanting to blacklist unwanted User Data, Domains etc.
2. Advertiser specific Database to ensure high quality rejection data
3. Immediately Fraud reduction as blacklisted users are not sent to the Advertiser anymore
4. No false positives as this data is generated by the Advertiser himself.
5. Automated rejections for Conversions
6. Possibility to block unwanted users / IPs / Device Ids etc. at Click Level
7. Adding Transparency of Rejections with Partners
8. Increased Campaign efficiency as e.g already converted users can also be listed in this Database

Benefits for Networks / Agencies

They also benefit greatly from such a system as they can get more transparency and get the ability to block certain known fraudsters before sending them to the Advertiser.

1. Much greater Data-Insight (e.g. Hashed Email Data, Phone Numbers, Device IDs) of rejected users.
2. Ability to stop bad actors at Click-Level.
3. Its an Advertiser specific Database meaning that there a no false positives due to mix up of Databases
4. Much improved reputation with the Advertiser as their campaigns will be less affected by Fraud
5. Automatic Rejections for their Conversions with added Transparency from the Advertiser

Technical Implementation

We are achieving this by using a Cryptographic Hashing Algorithm called SHA-256 which an industry standard for secure hashing. What it does is turning private Advertiser Data into unique non reversible values. We also include the last rejection reason of this data (e.g. [email protected] | Invalid Email Domain) or IP: 8.1.1.1 | DataCenter.

In the example below we use the email support@24metrics and generate a hash value of it. This is done within 9 microsencds which is extremely fast and allows us to perform these checks even at Click and Impression Level!

We are extending the hand to all other Fraud Solution Providers to built up a joint Fraud Database to synchronizing results between our solutions. To accelerate adoption we are providing this solution fully free of charge to Advertisers.

Sending Data into the Fraud Database

The processing time to generate the hash for this email only takes 9 nanoseconds which is very fast and can be used even at Click or Impression Level without impacting the performance of a campaign. The hashing Algorithm will be made open source by 24metrics and hosted on Github for Public Review.

To enable a clear rejection reason the following Data in Bold must be passed to the Fraud Database:

• Advertiser Domain (to identify the related Fraud Database).
• IP Address
• Rejection Reason

Rejection Table Example

* AdvertiserDomain	Conversion Time	* IP – Address	Email	* Rejection Reason	Publisher Click ID
advertiser.com	2023-07-12 08:30:10	Hashed IP	Hashed Email	Bot	ce7we27de7cfbe
Domain Validation	Time of Insert	IP Validation	Email Validation	Max 40 Characters	Max 40 characters

Optional Parameters are Email, Device ID, Publisher Click ID, Fingerprint, Domain, Phone Number. Publisher Click ID allows automatic rejection syncing between the Advertiser and the Publisher. It is highly recommended to send as much data as possible to increase accuracy.

We need your support

We welcome everyone from Advertisers, Fraud Solution Providers, Agencies to join us in changing the industry to a more transparent and automated Fraud handling.

The technology is available and scalable to solve the industry’s fraud problem that so many suffer from. We are convinced that this can be achieved when everyone in the industry works together.

Let’s make it happen. Please share this idea / article as we need to spread awareness that there is a solution to the problem.

You can also reach out to us under support@24metrics