Banks and financial services firms are rushing to roll out artificial intelligence-powered apps at an unprecedented rate, with many rapidly embracing a host of new technological features.
Quality assurance processes are increasingly led by AI-powered tools and solutions, and software testing at most finance firms is no longer merely carried out manually by human developers and engineers.
There seems to be a conviction that “everyone is doing AI” as a senior executive of LTIMindtree recently summarised.
The Indian software giant’s chief operating officer, Nachiket Deshpande, emphasised the tech’s pivotal role in boosting productivity and operational efficiency.
“AI in everything, AI for everyone, and everything in AI,” Deshpande said. “‘All, and I mean all, our clients are investing in GenAI.”
“Many have already executed proof of concepts and are now in a phase of understanding the precise implementations needed for their enterprises.”
However, the implementation of AI tech in banks’ digital infrastructure may not be as straightforward as it seems or many industry players make us believe.
“Many banks still rely on core banking platforms from a bygone era of technology, making integration with modern applications a delicate dance,” warns Rahul Chaudhari, the founder and CEO of software testing solution provider Qualitia Software.
He does agree AI and automation can help banking and financial institutions “conquer software development challenges” but argues it’s “a balancing act.”
“Cost, time, talent, and accuracy, these are the constant hurdles banks face in their software development sprints,” Chaudhari said.
He said that, beneath the sleek interfaces of mobile wallets and other tech-driven apps, lies “a complex web of software development, riddled with challenges that threaten to delay progress.”
““Traditional manual testing methods, while crucial, are simply not thorough enough in today’s complex software landscape.””.
– Rahul Chaudhari
Chaudhari defines one of the biggest roadblocks as “the heterogeneity burden” as he pointed out that legacy environments are often rife with technical debt, making them brittle and expensive to maintain.
“Even minor code changes in these heterogeneous systems can have cascading effects, slowing down development cycles and increasing the risk of errors,” he stressed.
And it does not end there.
Despite automated testing experiencing a huge uptake, humans are still very much part of the process. Therefore, the lack of global talent is not helping.
“Finding skilled software developers, especially those with expertise in banking and financial regulations and security, is a constant battle,” Chaudhari said.
“This scarce talent pool directly translates to longer development times and higher project costs. The demand for specialists in areas like security testing, performance testing, and compliance testing far outstrips supply.”
Another major challenge for many financial services firms is the use of testing data, or its accuracy rather.
“Accuracy is paramount when dealing with financial data. A single bug in a banking or financial application can have devastating consequences, both financial and reputational damages,” Chaudhari noted.
“Traditional manual testing methods, while crucial, are simply not thorough enough in today’s complex software landscape,” he stated.
Moreover, time constraints often lead to incomplete testing, creating a ticking time bomb for potential errors after launch.
“Manual testing suffers from inherent limitations, including subjectivity, repeatability issues, and inability to handle the growing complexity of modern applications,” Chaudhari said.
The long and costly road to automation
As the digital infrastructure and the use of apps and other online features that banks and other financial services firms us are growing fast, firms are keen to test more, and better.
Automated testing is therefore rapidly gaining momentum, as its scope and reach can simply not be matched by human developers who test manually.
Moreover, the afore-mentioned skills shortage further drives the appetite for automated testing solutions.
“In this high-stakes environment, having test automation emerges as a potential game-changer,” Chaudhari said.
“By automating repetitive testing tasks such as functional testing and regression testing, banks can free up valuable developer time and resources,” he continued.
“Imagine a scenario where account opening processes, and many others, are no longer manually tested hundreds of times, but handled by automated process scripts that can run overnight, flagging potential errors with higher accuracy,” he said.
“This not only reduces the time and cost of testing but also allows for more frequent releases, accelerating the time-to-market and business opportunity loss,” Chaudhari continued.
“The demand for specialists in areas like security testing, performance testing, and compliance testing far outstrips supply.”
– Rahul Chaudhari
To Chaudhari, more automated testing is simply a win-win situation as “the benefits extend beyond efficiency.”
Like many others within the industry, Chaudhari reasons that “automation empowers banks to adhere to the ever-changing regulatory landscape to save precious time to market.”
He pointed out that “test scripts can be constantly updated to reflect new compliance requirements, ensuring software remains compliant with Know Your Customer (KYC) norms and other regulations.”
Additionally, with modern tools available today, 80% of the defects can be found and corrected during the Quality Assurance process itself, Chaudhari continued, instead of in the User Acceptance Testing (UAT) time, a practice widely advocated by us for its ability to improve software quality and reduce time-to-market for their customers.
“Today, such tools offer real AI and real automation, with added advantage of digital traceability in this complex regulated environment, thus making them the clear winner,” he noted.
Embracing automation
Despite global efforts to embrace automated testing solutions, particularly in the US, Europe and rapidly evolving markets such as India, widespread adoption remains a challenge with the latest technologies prevalent in the market.
As a result, many banks, insurance firms and other financial institutions are building partnerships to augment their in-house expertise to develop and maintain robust automation suites.
“By embracing automated AI based software testing, financial institutions can bridge the gap between innovation and stability,” Chaudhari argued.
“It is time to move away from the tightrope walk and step onto a path of faster, more secure, and cost-effective software development,” he added.
“Those who take the leap first will reap the rewards.”
However, this process does mean significant more investment is needed, with concerns around initial investment costs and the need for skilled personnel to manage automation tools often cited as roadblocks.
“These hurdles can be overcome by partnering with those innovative product and service providers who are delivering such solutions,” Chaudhari said.
He is convinced that most investments can be quickly recouped with at least 60% cost and time reduction in testing time and bug fixing costs leading to significant financial benefits.
“The real savings are not just in cost of testing, but in value of deployment ahead of competition, potentially bug free,” Chaudhari claimed.
In summary, to him, “the future of banking belongs to those who can innovate rapidly and deliver exceptional customer experiences. By accelerating their adoption of automation, banks and financial institutions can ensure they stay ahead of the curve in the ever-evolving digital landscape.”
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