How Banking Industry Is Lagging In Test Automation: Its Time To Change

Although the bank works with a lot of start-ups and midsize partners who are at the cutting edge of technology, some of the technologies such as text mining are built in-house by the development team. Automation, AI, and analytics were the key levers for transformation. The structure for scaling up automation had to be rooted in the operations function, which in turn supports the business strategy. Many people still prefer human advisors for big financial decisions. AI-driven banking can feel impersonal, and not everyone is comfortable letting algorithms manage their money.

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With digital technologies influencing every aspect of consumer routine, it has indisputably brought a fresh wave of change and innovation in the financial domain. Axis Bank is a year and half into a multi-year technology transformation programme driven in large part by intelligent automation. The bank, India’s third largest in the private sector by total assets, has adopted agile methodology with multiple cross-functional squads working on over 220 high-priority, organization-wide transformation projects. The real shift isn’t just about moving online – it’s about how banks operate.

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Automation, artificial intelligence (AI), and hyper-personalized finance are reshaping everything from loan approvals to customer service. The automated business, combined with agile frameworks, provides opportunities for better-informed decision making, generated through a more holistic data picture throughout the organisation. “The pace and application of automation has changed dramatically over the last few years. Adoption of intelligent automation initiatives coupled with large-scale digitisation is helping us solve complex problems at a faster time frame,” says Axis Bank executive vice-president and head of information technology Avinash Raghavendra. For instance, mortgage processes sometimes take up to 50 days to approve. Automation, paired with emerging technology like blockchain, could combine to validate customer data from multiple sources automatically or reduce attrition from customers pulling applications due to minor errors on forms that caused delays.

Increased automation will be crucial to ensuring the industry can reach and retain its next generation of wealth and asset management clients. Equally important is the effective blending of automated and high touch services. We are, first and foremost, a client driven industry, so maintaining interpersonal relationships is really key. Simpler applications, such as streamlining backend processes, free up resources and time for banks to offer the high-quality, personalised service needed to maintain strong customer relationships – the bedrock of any private banking practice. Teller positions are declining, and AI is handling tasks once done by loan officers and customer service reps. While some fear job losses, others see an opportunity-new roles are emerging in AI oversight, cybersecurity, and data analytics.

• These are real concerns that regulators and consumers need to address.
• AI and automation are transforming everything – from how we save and invest to how loans are approved.
• Deloitte suggests that the post-pandemic bank will emerge a lot different to the one that went in.
• Many people still prefer human advisors for big financial decisions.
• This is what we learned after surveying chief technology officers, chief innovation officers, startup founders, and venture capitalists.

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• Testing such domains and lifecycles that involve heterogeneous platforms, intensive in calculations and lengthy transaction time with huge dependencies on batch processing certainly brings its own unique list of challenges.
• In the report, the World Bank notes widespread anxiety about automation’s impact on jobs.
• Increased automation will be crucial to ensuring the industry can reach and retain its next generation of wealth and asset management clients.

RPA has revolutionized the banking industry by enabling banks to complete back-end tasks more accurately and efficiently without completely overhauling existing operating systems. RPA has proven to reduce employee workload, significantly lower the amount of time it takes to complete manual tasks, and reduce costs. With artificial intelligence technology becoming more prominent across the industry, RPA has become a meaningful investment for banks and financial institutions. The bank invested in modernizing the core systems, scaling up the cloud portfolio for supporting the real-time business models, and building resilience across its operations. For example, the bank has a cloud-first approach for its digital banking platform, and has over 50 initiatives on cloud.Intelligent automation has been at the core of these transformation projects. It is not only the biggest driver for operational excellence, but also a powerful strategy tool to deliver on the growth, profitability, and sustainability goals.

From automating onboarding processes in lending to improving data quality and utility for better decision making, hyper-automation has the potential to augment workers ability, whilst reducing operational costs and human error. It’s well-known fact that manual testing cannot address the needs of a modern world of Banking Industry. Saying so, it should not become a forced choice just because the generic automation choices are failing to be smart and agile. The key lies in choosing the new age automation tool that is made for the industry and that caters to its ever-growing need for digitization, complex calculations, and lengthy transactions.

However, back-end processes are ripe for automation possibilities. This is driven by the sheer volume of records and documents many banks continue to add to, even in the digital age. Coined by Gartner in 2019, hyper-automation is the full automation of the business processes and customer processes.

In order to drive seamless integration with partners, the bank’s open API platform has been further enhanced to on-board merchants, generating more business and driving volumes. Banks that utilize RPA have given employees back time to spend on more complex tasks while artificial intelligence technology handles back-end operations. Ratan says the bank has set annual targets for improving its customer experience Index, with the goal of being the best-in-class in the banking space in India in three years. Banks that fail to integrate AI and automation risk losing customers to tech-savvy competitors. For years, banks relied on tellers and paperwork to process transactions. AI can approve loans, detect fraud, and even predict financial behavior before a person makes a decision.

In reality, technology is being used by asset and wealth managers to drive alpha generation and distribution, allowing banks to offer AI-driven investment strategies which maximise returns. The IT team also works on creating the technology foundation for collaboration within the bank and partnering with external organizations. For reuse, the bank has created a bot store and AI model store based on its experience in automating 300+ processes.

These banks operate without physical branches and provide everything online. However, there’s a fine line between convenience and privacy concerns. As banks collect more personal data, consumers worry about how that information is used. Banks track spending habits , savings goals, and even lifestyle choices to make customized recommendations. Instead of a generic savings account, you might be offered a travel-focused account with special perks if you spend heavily on flights.