Imagine people logging on their bank account and presented not with their own bank accounts but with those of completely different customers. Imagine people seeing their life savings suddenly missing from their account. This is what happened in April 2018, when a series of outages led to the meltdown of TSB’s online banking system, costing the bank £366 million in ‘post-migration charges’ and a big loss of customers. A bill of £153 million was sent to Sabis, the bank’s IT provider, for its role in the crisis. The overall cost of the software failure could increase further if fines are subsequently imposed by regulators.

In today’s digital era, banks and financial institutions need to implement continuous intelligent testing solutions to succeed in their digital transformation initiatives, mobile technology integration and modernisation of their core systems.

Artificial Intelligence has gradually made its way into every industry and is shaping the future. As we now live in the era of digital transformation, testing needs to be transformed to keep up with the latest trends and inevitably move towards greater automation. The future of automation is Artificial Intelligence (AI) and Machine Learning (ML).

With the adoption and spread of digital technology, software testing helps different organizations stay competitive and shows exponential growth during the last four years. While not every institution will be impacted equally by fast-changing technology, IT undoubtedly plays a significant role in all industries. In this article we emphasize in the eight most important tech trends that banks and financial services organisations will continue to experience within 2020:

Traditional test automation tools have achieved little in terms of automation, keeping automation levels below 25% even after years of software testing. These tools were built more than a decade ago – some even more- to cover a limited set of technologies and the Waterfall Methodology, and are ineffective to meet the business demands of faster application delivery and faster time-to-market. In addition, businesses, are increasingly adopting Agile and Continuous Delivery, which introduces a new set of challenges.

On May 2019, Deutsche Bank found out that its software, which is meant to Detect Money Laundering activity, had a bug that prevents a program from retroactively scanning and analyzing corporate payments to flag potentially suspicious transactions and identify patterns that can be notified to regulators. The AML software program “was configured erroneously with two out of 121 parameters defined incorrectly,” the financial institution said in a statement. This was not the first time Deutsche Bank has been repeatedly fined for failing to fight money laundering as well as to comply with sanctions against foreign countries and entities.

Testing in Production means to perform testing activities in a production state or live environment which is accessible by the end user. As companies move to implement Agile, DevOps or Continuous Integration and Delivery, testing in production tends to become an integral part of the process.

Validata Group extends its leading Digital Automation platform to support DevOps for Temenos Core Banking, with risk-based impact analysis and Continuous Testing, focusing on exposing user interface software and user experience issues early in the lifecycle.

Model-based testing can be considered as the natural evolution of software testing, addressing the challenges of current software testing market and distinguishing itself away from traditional testing methods. Traditional approaches have achieved little in terms of automation, keeping automation levels below 25% even after 30 years of software testing.

Agile and DevOps practices have brought a revolutionary wave in testing. The shift-left way of thinking has made testing and development no longer separate tasks and gave to testing the ability to track the quality metrics right from the inception and on a regular basis thanks to a more ‘continuous’ approach (Continuous Testing, Continuous Development and Continuous Deployment).