D1R4Payments Testing Accelerator
RedCompass Labs
Using AI and machine learning algorithms, D1R4Payments profiles everything that happens in your production environment to find all the unique test scenarios AND edge cases. So what used to take your test teams 4–6 weeks, we can now do in just five days. And with machine learning, we will profile in just four hours.
Once you know what you need to test, D1R4Payments runs millions of real transactions through the test environment and displays the results for payments experts to investigate and evaluate your Day-1 readiness.
By using masked customer transactions to test, you not only ensure 100% coverage, but you will also be able to identify patterns and insights hidden in your production data. That can help you improve operational processes and increase customer intelligence.
RedCompass Labs D1R4Payments is a game-changing, data-driven testing solution that accelerates your testing by using AI to profile, compare and analyse millions of production transactions in your test environment. D1R4Payments enables you to know WHAT you should be testing to avoid any outages on DAY 1 of your payment transformation, regulatory updates, or cloud migration project release.
D1R4Payments makes testing over 200 times faster, enabling you to meet all regulatory and industry upgrade deadlines. Going faster and being sure of your coverage and efficiencies also helps you to cut operational costs by 30%.
By using D1R4Payments, you will be able to:
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Accelerate the adoption of FusionFabric.cloud.
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Understand how your customers and correspondents behave and assess your test coverage.
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Use technology to cut costs and reduce human errors.
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Eliminate the risk of business reputation damage caused by that one missing test case that on Day 1 could put your name in the newspapers.
Key features:
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Platform-agnostic and therefore able to integrate easily to FusionFabric.cloud.
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It can also be used on-premises.
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No maintenance required, in contrast to traditional automation testing tools.
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The capability of creating synthetic data based on your production data and real customer transactions.
