Automate Oracle FLEXCUBE Testing
By: Curiosity Software
Tags: Test Automation, Fintech, Banking Technology, Testing Framework, Banking

Banks globally rely on Oracle FLEXCUBE to provide their agile banking infrastructure, and more today are migrating to FLEXCUBE to retain a competitive edge over young and agile Fintech startups.

FLEXCUBE provides the flexibility to progressively transform componentised core banking systems, while supporting moves to modern cloud infrastructure. It enables established financial players to innovate rapidly, even against the backdrop of historical infrastructure and complex end-to-end processes.

However, every migration and update must be tested rigorously. Otherwise, organisations risk exposing critical banking systems to costly defects, downtime, and security vulnerabilities.

That means rigorously testing migrations to FLEXCUBE, mitigating against the risk of exposing the most sensitive part of an organisation to costly bugs and data breaches. Every upgrade must then be tested rigorously, realising the value of new functionality without breaking custom implementations.

This article will discuss common barriers to rapid and rigorous FLEXCUBE testing, before setting out how model-based test automation enables organisations to keep up with the latest in FLEXCUBE innovation. To see this approach in action, join Curiosity and Coforge for Oracle FLEXCUBE: De-risk upgrades and migrations in core banking with rigorous test automation.

TESTING UNCERTAINTY INTRODUCES RISK TO CRITICAL CORE BANKING SYSTEMS

FLEXCUBE testing can be a slow and complex process for the hundreds of banks who rely on custom FLEXCUBE implementations.

In-house testing teams typically lack the niche knowledge needed to test complex parameters and custom configurations during FLEXCUBE migrations and upgrades. The complexity of end-to-end scenarios further means that there are more tests than could ever be executed before the next release, but testers lack an automated or reliable way of creating an executable number of tests.

This introduces uncertainty to core banking systems, as testers cannot reliably approve an update or migration. Slow and manual testing do not provide the necessary assurance, as testers often struggle with manual test case creation, repetitive scripting, test data bottlenecks, and slow test maintenance.

These time-consuming and typically unsystematic testing processes force testing further behind FLEXCUBE updates, while only covering a fraction of the scenarios needed to migrate or upgrade with confidence. For banks to keep pace with the latest in fintech innovation, an automated and systematic approach is needed to Oracle FLEXCUBE testing.

DE-RISK FLEXCUBE ADOPTION AND MAINTENANCE

Visual, model-based test automation offers one approach to simplify, streamline and automate FLEXCUBE testing. Instead of struggling uphill with poorly understood systems and manual test creation, testers can quickly scan FLEXCUBE UIs, assembling a library of reusable components into visual models. These models auto-generate the tests, scripts and data needed during a FLEXCUBE migration or upgrade.

Using a UI scanner, test importers and a library of out-of-the-box components, in-house test teams no longer require niche FLEXCUBE knowledge. They can visually assemble reusable subprocesses into end-to-end flowcharts, making quick adjustments for customisation and parametrisation. The quick-to-build tests then generate everything needed for rapid and rigorous FLEXCUBE testing:

The visual models generate optimised FLEXCUBE tests, while also building and maintaining living documentation of core banking systems. The easy-to-maintain flowcharts build and retain in-house knowledge, future-proofing core banking systems. In-house testing and development teams can innovate broader banking processes and integrated technologies, understanding the impact that their changes will have on custom FLEXCUBE implementations.

While boosting testing agility and building FLEXCUBE knowledge in-house, the model-based test automation further provides the test coverage needed to innovate core banking processes.

The automated test generation creates the smallest set of tests needed to “cover” the modelled scenarios, while risk-based generation can target particular functionality based on time and risk. This reduces test volume without compromising test coverage, providing confidence before every upgrade or migration.

The rapid test generation further avoids test data bottlenecks and helps reduce the risk of costly data breaches. With integrated Test Data Automation, every end-to-end test scenario can come equipped with anonymous or synthetic data on-the-fly. This data is found, made and prepared “just in time” as tests are generated or run from Test Modeller, providing all the data needed to test during a FLEXCUBE migration or upgrade.

Using Test Modeller, organisations can enjoy the innovation of the latest Oracle releases, while mitigating against the risk of breaking custom FLEXCUBE implementations. Test maintenance is as quick and simple as updating the central flows, hitting “regenerate” to rapidly and rigorously test FLEXCUBE before every update.

Test Modeller allows organisations to realise the value of the latest FLEXCUBE releases, while reducing the risk of damaging bugs and downtime. They can build and retain in-house knowledge of core banking systems, while generating the tests needed to keep FLEXCUBE up-to-date.

To discover rigorous test automation for Oracle FLEXCUBE, join Curiosity and Coforge for Oracle FLEXCUBE: De-risk upgrades and migrations in core banking with rigorous test automation.

About the author: Thomas Pryce is the Communications Manager at Curiosity. He has been with Curiosity since 2018, where he enjoys researching and advising on test data, test automation, and SDLC transformations.