The Challenge for Traditional Banking Institutions

Traditional banking institutions face significant challenges from alternative fintech solutions such as digital banks, wallets, mobile payments, peer-to-peer lending platforms, and cryptocurrencies. These fintech innovations have embraced DevOps methodologies and technologies from the outset, benefiting from advantages such as zero downtime, rapid delivery of new features, fewer bugs, enhanced performance and scalability, and reduced maintenance costs. In contrast, traditional banks have been slow to adopt new IT methodologies due to their legacy systems, stringent regulations, and conservative IT management frameworks. As a result, they have fallen behind in certain fintech areas.

A slow testing process often stands in the way of development teams striving for fast and efficient releases. For many, manual testing creates a bottleneck where time, resources, and quality are at stake. But there is a solution that can speed up the process while also improving quality: automated testing.

For many companies, production issues bring more than frustration – they result in costly reworks, bug corrections, and retesting, disruptions to user experience, and damage to customer trust. Often, these issues stem from the limitations of manual testing and the pressure on development teams to keep up with release deadlines. Here, we explore how automated testing, further enhanced by AI, allows teams to feel more secure in their deliveries, and can thus keep a higher pace. 

In an age where digital transformation is revolutionizing industries, the importance of Software Quality Assurance (QA) has reached unprecedented levels, particularly within the defense sector. As systems grow more complex and interconnected, safeguarding their security, reliability, and compliance is of utmost importance.

APIs, or Application Programming Interfaces, are the connectors that allow different software systems to communicate. They establish a standardized communication protocol for sending and receiving data, ensuring consistency across platforms. The OpenAPI Specification (OAS) is a popular format used to document these APIs in a machine-readable way (typically in JSON or YAML). Because it’s both comprehensive and machine-readable, OAS powers many automation scenarios in API testing, acting as a blueprint for test generation. 

What is the first thing that crosses your mind when you see the report that a test has failed in the automated run?

• “O-o, we have a bug here,” or
• “What is wrong with this test case now?”

The European Union has just rolled out the InvestAI initiative, a colossal endeavor to rally €200 billion for AI investment. Think of it as Europe's grand plan to become the superstar of AI development and application, sparking innovation and competitiveness across a multitude of industries. But what does this mean for companies in Europe? Let's dive into the potential impact and opportunities that InvestAI brings to the table.

In software development, resolving bugs quickly is a priority. However, the "quick fix" approach often addresses symptoms rather than the actual causes, potentially leading to recurring issues.

QA professionals play a critical role in Root Cause Analysis (RCA) by going beyond testing to understand the reasons behind defects. Unlike developers, who focus on debugging code and fixing technical failures, QA takes a broader view, considering system-wide behaviors and user perspectives.

At System Verification, we are deeply committed to staying at the forefront of technological advancements and delivering the highest quality services to our clients. One of our key contributors to this mission is Dr. Adha Hrusto, an AI Solutions Engineer whose expertise has significantly enhanced our capabilities in quality assurance and software testing.