Retail Fuel

Allowing our customers to take control – simply increase customer acceptance with frictionless payments.

Working with Retail Fuel

There is more and more pressure to move people and transport goods in most efficient manner. In order to meet the demands, governments and fuel retailers around the world are facing the same question: how to optimise transportation mobility in the future?

Currently ai plays a small role in helping provide solutions to the global mobility issue but we are looking to use our technology in a more proactive manner in the future. Leading industry experts believe that artificial intelligence will play a bigger and bigger as energy-demand continues to increase and the uninterrupted availability of fuel types at an affordable price, becomes ever more crucial. Being able to take all these data points in an efficient/optimization way will require smart technology that can be used by the fuel retailers – so they can Take Control.

Put simply, we believe we are well positioned to help our customers increase acceptance on their forecourts by making sure the consumer can access the right products every time and simply pay in a frictionless manner.

ai’s cloud based modular approach means, you can either take part or all of our end to end payment solutions. This set product and services covers the whole end to end payment chain including omni-channel switching, issuing, risk and analytics. Our self-service risk and analytical modules use state of the art machine learning tools that are designed to help our customers, resolve analytical questions efficiently.

As all our solutions are cloud based, a series of APIs are available so our clients can integrate quickly and using standardised approaches (such as IFSF protocol).

ai’s recommended solution for Retail Fuel

aiGateway™
EazyFuel™
RiskNet®
SmartRule™
SmartScore®
SmartIntelligence™
SmartAlerts™
SmartCase™
SmartMinds™
*Reference performance values are calculated against the average system. Results may vary.

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12Sep

Retail Risk – Dallas

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