Validata Blog: Talk AI-powered Testing

CRM Testing:  Ensure quality for optimal customer experiences

CRM Testing: Ensure quality for optimal customer experiences

When people talk about CRM, they are usually referring to a Customer Relationship Management system, a tool that is used for contact management, sales management, productivity, and more. The goal of a CRM system is simple: Improve business relationships.

Breaking Bank: How an IT migration corrupted 1.3 billion customer records

Breaking Bank: How an IT migration corrupted 1.3 billion customer records

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.
AI and Analytics at the Core of next-gen Continuous Testing

AI and Analytics at the Core of next-gen Continuous Testing

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.
The hidden costs of traditional automation frameworks

The hidden costs of traditional automation frameworks

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.

The impact of poor software quality in banking

The impact of poor software quality in banking

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.
Why testing in production?

Why testing in production?

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.

Common challenges faced when choosing Selenium

Common challenges faced when choosing Selenium

Selenium is an open-source solution for ‘automating’ web application testing. Self-made automation frameworks such as Selenium are fundamentally about testing the low-level code, not the user experience,

Why model-based test automation?

Why model-based test automation?

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.
AI, Analytics and Test Management, All in One!

AI, Analytics and Test Management, All in One!

Getting Quality Performance right is key to the success of every area of the QA business. Organisations need to see results across projects, departments and geographies  in order to make faster and more informed decisions.

Getting ready for Big Data Testing

As Testers, we need trustworthy data! Data is often the root cause of testing issues; we don’t always have the data we need, which causes blocked test cases, and defects get returned as “data issues.”

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