AmBank Group

About AmBank Group

The AmBank Group is one of Malaysia’s premier financial services groups, offering comprehensive products in retail, commercial, investment banking and insurance sectors. The company has in the region of 200 branches providing individuals and businesses with a range of financial services and products.

With the Micro Focus Silk Suite, AmBank Group gained a complete QA solution, offering test management, change and configuration management, and automated testing.

AmBank Group had used the Compuware suite of testing tools in the past and upgraded to Borland (now part of Micro Focus), with its integrated suite of testing solutions. The flexible investment structure proposed by Borland suited AmBank’s requirements, and it liked the benefits of tool integration within a testing framework as well as the additional features offered.

The core banking system replacement project uses the test management tool (Silk Central) to facilitate manual test case planning and execution. This ensures efficient use of resources and a targeted approach to quality goals. The second tool used was a change and configuration management tool (StarTeam), which is used to track defects as well as changes to the source code. It provides defect integration into the test management tool and avoids duplication of effort.

Test automation (Silk Test) was used across a number of projects, including the core banking system replacement project. Here, automating regression testing allows faster changes to applications as less resources and time are required to retest functions each time an application is changed. Margaret Koh, Head IS, Retail Banking, AmBank Group, commented that using Silk Test to automate the testing process has significantly reduced the testing time and manual input. Through regression testing, changes to applications are more comprehensively tested, so any effect on other functionality is discovered at an early stage and pre-emptive action can be taken before it impacts the business.

Similarly, by conducting performance testing (Silk Performer) using 1,000-2,000 virtual users on a web protocol, issues are identified early on which would not be picked up during the normal functional testing process, significantly improving application performance across the board. The thorough performance testing process has resulted in more stable applications that fully meet the requirements of AmBank business users.

Other than the core banking replacement project, the improved testing framework is also put to work on Internet Banking, Contact Center Customer Relationship Management, Insurance Application Integration and Enterprise Process Workflow, all providing key business services to the bank and its customers.

Charles Tan recognizes the value that the new testing framework brings in supporting a flexible approach to the application release schedule. Previously, AmBank was tied to quarterly releases, but with the discipline injected into testing, responses are received much more quickly and pro-actively, providing the business with higher-quality solutions.

Introducing the Borland (now part of Micro Focus) tools has given AmBank Group a way to govern the entire testing process, developing templates and designing good testing principles to sit at the heart of each project. This has required a paradigm shift in working methods, as Margaret Koh comments: “Management support was key to the success of this. Once it became clear that we could save costs by reducing testing time and increase customer confidence by delivering higher-quality products, the fundamentals and importance of the testing framework were quickly understood. Now, AmBank Group’s governance dictates that large projects conform to the Silk-based testing framework to take advantage of these benefits.”

The foundation has been laid for a continuous testing cycle. Test automation will manage new application patches and releases without much manual involvement. Quality controls have been introduced into the development process itself so that most potential errors are identified early on, creating a more stable and higher-performance application.