At the recent QA Financial Forum in New York City, one of the key speakers was California-based Applitools.
The American-Israeli company, which is a provider of AI-based automated visual testing and monitoring solutions, was represented at the event by Dave Piacente, the firm’s content and customer advocacy lead, who demonstrated the capabilities of autonomous testing.
His talk came after Applitools only recently launched a new testing platform, called Autonomous, which the company claims is “the first fully autonomous test automation solution” that automatically generates tests on websites and multi-page web applications by using natural language processing to allow developers, test engineers and business users to author automated tests using plain English.
Following the conference, QA Financial checked in with Applitools’ COO Moshe Milman, who co-founded the company in 2013.
QA: Financial firms businesses are facing enormous challenges with traditional QA and testing methodologies. Increasing the speed of application development and deployment, without compromising on quality, has become a critical factor for success. In New York on May 15, you plan to argue that a robust test automation strategy is not just an advantage – it’s a necessity for remaining competitive. Can you elaborate?
Moshe Milman: In today’s fast-paced digital economy, financial firms are under immense pressure to accelerate their application development and deployment cycles. Traditional QA and testing methodologies often struggle to keep up due to their time-intensive nature and the human resources they require. This lag can be a significant bottleneck, leading to slower time-to-market and potentially higher costs due to delayed product launches or fixes.
In Piacente’s talk, he discussed why a robust test automation strategy is no longer just a competitive advantage. It’s a cornerstone of modern business strategy for anyone in the financial sector. With the right test automation strategy and tools, companies can drastically reduce the time spent on repetitive testing tasks, enabling engineering and QA teams to focus on more complex challenges and innovations.
“The risk of over-reliance on automation should not be underestimated.”
– Moshe Milman
Furthermore, Piacente covered some of the latest developments in the space specifically around GenAI, and how these can help address current testing challenges. He also showcased some of the latest progress around Autonomous Testing implementation, demonstrating how these innovations can predict, detect and mitigate issues before they impact the business.
QA: What are the essential components of a successful test automation strategy?
Moshe Milman: To thoroughly address this question, we have collaborated with thought leaders from several leading companies within the industry. Piacente‘s presentation at the QA Financial Forum in New York City included a blend of our insights and the valuable perspectives of these experts, he will explore the essential components of a successful test automation strategy, demonstrating not just theoretical approaches but practical, proven solutions.
QA: To focus on this last element a bit more, can you share some practical steps for implementation within any financial services firm?
Moshe Milman: Implementing a successful test automation strategy and test framework within a financial services firm involves several practical steps. First, begin with a thorough assessment of your current testing processes to identify areas where automation can provide the most benefit. Prioritize those areas that are critical to your business operations and promise a high return on investment in automation.
Next, select the right tools that align with your technology stack and meet specific business needs. For financial services, it’s essential to choose tools with robust security features and compliance with industry regulations. Applitools, for example, offers solutions specifically designed to handle complex financial applications and ensure that visual elements remain consistent across different platforms and devices.
A critical step is ensuring you have the right talent on your team. This includes training your existing staff on new tools and potentially hiring specialists with experience in software development, automated testing, and AI.
Moreover, fostering the right culture of quality throughout your organization is crucial—this topic alone could be a full conference discussion. Finally, continuously monitor and optimize your automation processes. Gather feedback from the testing phases, make necessary adjustments, and strive for continuous improvement in your testing cycles. This iterative approach helps ensure that your automation strategy remains effective and aligned with your firm’s evolving needs.
QA: The impact of GenAI and LLMs is revolutionary, to say the least. How can these technologies best be exploited? And any pitfalls business should look out for?
Moshe Milman: The impact of Generative AI and LLMs is indeed transformative, enhancing capabilities in data analysis, test creation, test data generation, and test maintenance, among others. To best leverage these technologies for testing, businesses should integrate them in ways that augment human capabilities and streamline processes. However, several pitfalls need careful consideration.
QA: Can you elaborate?
Moshe Milman: First, the quality of data is paramount. AI systems are only as good as the data they are trained on. Biased or poor-quality data can lead to inaccurate outcomes. Therefore, it is crucial to ensure data integrity and select AI testing tools that are mature and stable, beyond those that merely produce impressive demos.
Another significant concern is privacy and security. Since these technologies often process sensitive information, safeguarding this data against breaches and ensuring compliance with regulations, such as GDPR, is vital. It is important to choose vendors whose tools provide robust protection and adhere to necessary compliance standards.
“With the right test automation strategy and tools, companies can drastically reduce the time spent on repetitive testing tasks, enabling engineering and QA teams to focus on more complex challenges and innovations.”.
– Moshe Milman
Lastly, the risk of over-reliance on automation should not be underestimated. It is essential to maintain a balance where human oversight is integrated into AI-driven processes. This approach helps mitigate risks associated with AI errors that could lead to operational disruptions or customer dissatisfaction.
In summary, while Generative AI and LLMs offer substantial benefits, they must be deployed thoughtfully. A clear strategy for vendor selection, data management, security, and human oversight is essential to harness their potential fully without falling into costly pitfalls.
QA: Testing the quality of AI apps is a timely issue, as there are no global standards yet. How do you think businesses should go about that?
Moshe Milman: Testing the quality of AI applications presents unique challenges, particularly because of the lack of universal standards. However, businesses can adopt a proactive approach to ensure the robustness and reliability of their AI systems. Firstly, developing internal guidelines and benchmarks based on industry best practices and relevant regulatory requirements is crucial. These guidelines should focus on accuracy, fairness, transparency, and safety of AI applications.
Secondly, businesses should implement rigorous testing phases that mimic real-world scenarios as closely as possible. This involves diverse datasets to test against, to help ensure the AI behaves as expected across varied and unexpected inputs.
Thirdly, continuous monitoring and updating of AI systems is essential. AI applications learn and evolve over time, which means their behaviour can change. Regular audits and updates help in maintaining the integrity and performance of the system.
QA: Thank you. Finally, anything else you would like to share with our readers?
Moshe Milman: As we look ahead, the role of test automation and AI in financial services will only continue to grow. It’s important for firms to stay proactive, not only in adopting these technologies but also in continuously refining their approach to ensure they remain at the forefront of innovation.
Embracing tools which leverage AI to enhance testing accuracy and efficiency while reducing costs, is a step towards maintaining competitive advantage in a rapidly evolving industry.
Additionally, I would emphasize the importance of a culture that values quality assurance and continuous learning. As technologies advance, so too must the skills and strategies we employ. Encouraging ongoing education and experimentation within your teams can foster an environment where innovation thrives.
Finally, never underestimate the power of community. Engaging with other professionals through conferences, workshops, and forums can provide invaluable insights and foster partnerships that propel your strategies forward. Together, we can drive the future of financial services, ensuring robust, reliable, and user-friendly products.
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