Case Study:
Flexpay.io

Driven by a strong retail background, FlexPay.io leads the payment salvage industry with advance machine learning models that intelligently determine the best way to recover declined, recurring payment card transactions where the credit card isn’t present.

A cloud-computing veteran, CTO Steve Mathieu selected Azure without hesitation. To maximize their Azure investment, ensure the stability of the environment, and to provide ongoing managed services, FlexPay.io chose Green House Data.

“We have always taken a cloud-first, and in fact, a cloud-only, perspective, but cloud does not mean set-it-and-forget it.”

Innovating Payment Salvage in the Cloud

Payment salvage as an industry has grown hand-in-hand with payment card processing. As both consumers and businesses transition to fewer cash or check transactions, and as the subscription economy continues to rise, declined cards represent a real source of lost revenue—some industry sources estimate that up to 1.9 billion card-not-present—the kinds of purchases where you are not in-person with your payment card, like when shopping online or auto-renewing a magazine subscription—transactions are declined each year globally, representing a projected $331B in lost revenue for 2018 alone according to industry sources.

What makes FlexPay.io different is the way that we have applied machine learning to the applications that interact with the payment gateways,” said Mathieu. “This allows us to capture a higher percentage of what would otherwise be lost sales for our customers—and because we only bill on the money we have recovered, our model compels us to do what is right for our clients.”

In order to be responsive and successful in an industry that is rapidly changing and always has to be on high-alert for fraud, Mathieu and his team require an Azure environment that is not only optimize for FlexPay.io’s specific applications, but also for the space at large. Secured, stable and burstable infrastructure, and ongoing management are paramount.

“We have always taken a cloud-first, and in fact, a cloud-only, perspective, but cloud does not mean set-it-and-forget it,” said Mathieu. “At the same time, I want my staff to be working on innovation projects and interacting with our algorithms, not tracking down infrastructure performance issues or applying patches. That said, if the platform fails, we fail, which is precisely why we engaged Green House Data as a partner.”

Green House Data performs ongoing management of the Azure platform for FlexPay.io’s platform, which leverages critical Azure components like AI and Machine Learning, API calls, native analytics, DevTest labs, and Azure DevOps on top of compute and storage resources.

 

Enabling DevOps

Managed Service providers have evolved beyond legacy break/fix models to become enablement organizations who deliver on DevOps frameworks, upstack application management, and automation strategies. Constant improvement and iterations are key in the fast-paced application development world.

“We release new versions close to every two weeks, which means we are constantly in a development cycle. We have members of the team who are specialized in mathematics and statistics, but in order to keep up, we have to push the platform,” said Mathieu.

Flexpay.io’s machine models make decisions based on multiple input sources. For example, leveraging data from financial institutions to find batch windows where higher numbers of transactions are accepted, and sifting through feeds of social data to identify behaviors that might indicate fraud, and synthesizing new information from every transaction to give merchants the best chance of recovering.

“Ultimately,” said Mathieu, “We are in the business of building trust. From the merchant through the payment gateway, through processor and back to the consumer, we must protect our customers. The better their reputation is, the more revenue we can capture. We support our clients in the same way that Green House Data supports us.”

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