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AI Case Study

Mastercard achieves 11% increase in transactions approval and a reduction in fraud with the use of deep learning

Mastercard has launched a new system to authenticate transactions. It is based on deep learning to process data like historical patterns, user behaviour, the IP address of the computer used, location and other in real-time at the point of sale. By analysing up to 150 data fields, the company aims to achieve fewer false positives, less fraud, and faster approvals. So far, Mastercard Identity Check has resulted in an 11% increase in approvals and a reduction in fraud, according to the company.


Financial Services


Project Overview

"Chris Reid, Mastercard’s executive vice president of services for North America, recently briefed Datanami on its implementation of 3D-Secure 2.0, dubbed Mastercard Identity Check, and – most importantly for our readers — how big data and AI factor in the new process.

“We’re making it much easier from a consumer perspective and much better from a merchant and issuer perspective,” Reid says. “How we’re doing that is we’ve dramatically increased the data that is going to enable the issuer and the merchants to make the right decision on the transaction.”

According to Reid, the Mastercard Identity Check program will utilize up to 150 different data fields in its algorithmic decision-making processes. That’s 10x more than previous methods fed into the automated sytems.

“There’s a large amount of data elements that the merchant has, and a large amount of data elements that the bank has, and what we’re aiming to do is to piece these together and let the merchant and the issuer make the right decisions around authorizing those transactions,” he says. “The more data that you can apply into making a decision, the greater level of confidence you can have about that decision, and as a rule the more accurate you’re going to make that decision.”

The new program will enable banks to take into account a lot more information than previously, such as:

* Whether a buyer has authenticated himself into the merchant’s environment;
* The bill-to and ship-to addresses, and whether the buyer has used them before;
* Whether there have been problems with buyer’s previous purchases;
* If the buyer is using expedited shipping;
* The value of the item being purchased;
* The IP address of the computer where the purchase originated from;
* Whether the buyer is shopping during normal times of day;
* The brightness of the handheld device’s screen;
* Whether device owner gestures match historical patterns;
* And other pieces of data.

Mastercard needed the power of neural networks to be able to process all of this data quickly at the point of sale. “We’re able to apply newer technologies and advance computing power to crunch the incremental data,” Reid says.

The new program will also reduce friction by providing so-called “one-way” data flows for certain merchants. Today’s transaction typically has a two-way flow of data, but merchants increasingly want a one-way flow of data, where banks make the ultimate determination to approve or deny, because it reduces latency, although merchants also have the option of doing “step up” validation for certain transactions, Reid says.

“So what we’re seeing with the frictionless flow is the transaction being orders of magnitude quicker than traditional flow, powered by AI, because it can ingest data, make a decision, and pass it through into a trust score,” he says.

Reported Results

"As a result of processing up to 150 data fields, Mastercard will be more confident in the identity and authenticity of card-not-present transactions, which will result in lower false positive and false negatives too. In places where the Mastercard Identity Check has been rolled out, the company has seen an 11% increase in approvals and a reduction in fraud, Reid says."




"Have you ever had a legitimate credit card transaction declined on the Web or your smartphone? It’s a real hassle, to be sure. But now, thanks to a new payment protocol being introduced by Mastercard that relies on deep learning to authenticate purchasers, you should see fewer false positives, less fraud, and faster approvals to boot."



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