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Chargebacks911® & Microsoft Partnership Featured in Nilson Report

Chargebacks911® & Microsoft Partnership Featured in Nilson Report

Major Industry Publication Spotlights Our Latest Major Partnership

The recently-announced partnership between Chargebacks911 and Microsoft is major news for the payments space. So much so, in fact, that it was recently picked up in the latest issue of The Nilson Report.

The Nilson Report is one of the most respected sources of news and analysis in the global card and mobile payment industry. For half a century, their subscription-only paper has provided news and statistics not found in any other trade journal, as well as concise technology, personnel, and product news and updates.

In the last decade, Microsoft began to develop in-house technology to mitigate losses incurred on their digital platforms. Just two years ago, Microsoft dubbed their new anti-fraud mechanism the Dynamics 365 Fraud Protection Solution. Dynamics 365 has been on the market since 2020 and boasts customers like Capital One and Worldwide. Now, as noted in the piece, Microsoft are joining forces with us here at Chargebacks911 to take this technology to the next level.

The two companies will combine technological data sets to develop a machine learning model that will provide merchants with a more advanced risk-scoring process to identify fraud through pre-authorization. Machine learning tech depends upon measurable patterns throughout customer-related data points. These data points include information provided by Chargebacks911 regarding disputes and chargebacks and will help merchants fight friendly fraud, fraudulent returns, and omnichannel discounts.

The expectation between both companies is that their integration between front and back-end fraud monitoring will be readily welcomed by banks and merchants en masse. Its appeal is obvious: with a two-fold approach, fraud prevention would no longer exacerbate the checkout process and additionally provide improved analysis and response to chargebacks and post-purchase fraud.