AI has changed the game for banks in the areas of operational resilience and customer experience, as the events of 2020 have demonstrated. However, as banks develop into AI-driven businesses, AI itself will cease to be only a tool for business enablement and instead become a key enabler of revolutionary business strategy.
Challenger Banks are the modern banks that have emerged as a result of technical and governmental advancements. According to marketwatch, “Over the next six years the Challenger Bank Market will register an Impressive CAGR in terms of revenue, the global market size will reach multimillion USD by 2028.”
These banks are typically entirely digital and don't have any physical locations, saving the customer a tonne of money and making the entire transaction convenient and affordable.
And therefore, they are becoming more and more well-known each year and have already dominated some sectors, such as payments and transfers.
Challenger banks primarily concentrate on the customer experience, and the majority of their offers meet or exceed client expectations. Challenger banks do numerous kinds of tasks, from simple ones like accepting payment transactions to complicated ones like commercial lending.
Challenger banks outperform traditional banks in the majority of banking categories, thanks to benefits like lower costs, faster processing, improved client relations, etc. The use of chatbots to comprehend consumer requirements is among challenger banks' remarkable technical features. Customers can obtain immediate assistance from chatbots, who can also answer any of their questions. Chatbots' overall goal is to provide a remarkable client experience.
By incorporating advanced technologies like Machine Learning, Artificial Intelligence Cognitive Computing, Natural Language Processing, etc., challenger banks are currently moving up a level or two. On the other side, the pandemic turned out to be a gift in disguise for them because over time, more and more customers have begun to favour digital banking platforms over traditional banks.
Image source: Fintechnews
Despite the fact that challenger banks are in high demand right now, they had to overcome some big obstacles before recovering. Leading challenger banks experienced a large decline in app downloads of 23.38% during the start of the Coronavirus pandemic, imperilling their position on a global scale.
Additionally, because to the first global lockdown, many diners and travellers stopped using their cards, which had an impact on the bank's liquidity. There are two key obstacles preventing challenger banks from expanding globally, despite their efforts to adapt to the situation and explore new ideas:
1. Increased Competition
2. Gaining License
Increased Competition
A challenger bank is either made or broken by the subtleties of various services. There are a lot of Fin-Techs and other banking organizations vying for clients' business in the market that is open to new financial businesses. Challenger banks must therefore constantly monitor their rivals and research novel concepts aimed at attracting and keeping customers.
Getting A Licence
The failure to obtain a licence is the only reason for the majority of challenger banks' first problems. To obtain a licence, these banks must meet a variety of requirements, and in some circumstances, in addition to federal restrictions, they must also abide by several state regulations. Different sets of data privacy standards, such as GDPR, etc., further compound this difficulty. Such massive procedures ultimately exhaust the banks, resulting in the fallout.
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The performance of the entire application is completely handled by AI-driven strategies. It aids in resolving problems with middleware and API performance, monitoring transaction metrics and traces continually, and other problems with performance.
Report Development
AI-driven AMS offers a precise examination of the numerous aspects influencing the application's improvements for a better understanding of how the application functions. It features things like Scalability, SLA predictions, Custom dashboards, and reports on capacity assessments.
Problem Management
AI-driven AMS aids in ticket management and problem detection, preventing significant escalations. It ensures proactive and adaptive maintenance and carries out a routine inspection to guarantee easy access to and use of the application.
Three-level Support
L1, L2, and L3 levels are supported by AI-driven AMS in a variety of ways. It aids in tracking down the source of flaws, resolving ad hoc problems, keeping track of ticket records, making minor improvements, etc.
QA helps in Driving Quality and Performance with Robust Testing for challenger banks. Quality assurance (QA) initiatives like choosing the right kind of banking software testing tools helps in delivering quality products that effectively meet customer needs and preferences. With the help of Optimized QA processes and right test management programs, challenger banks can reduce post-production defects.
Quality assurance helps in increasing the reliability & security of core systems, and one can reduce the cost with the help of automation, which we will discuss later in the article. In any sort of fintech service, an end-to-end testing methodology is required. It should include Omni-channel testing, continuous testing, cybersecurity testing, customer experience testing, along with stress and load testing. Thanks to QA procedures as it ensures complete coverage of all business requirements as well as the functional aspect of the application.
For challenger banks in the digital age, that are evolving than ever before, Quality Assurance is indispensable for the smooth and hassle-free running of financial applications. There are several challenges that are taken care of with the help of QA and software testing.
Complexity of Challenger banks
Challenger banking apps are complex; there are legacy systems. They require constant updates as well to stay in the competition and regulatory requirements. For a typical web or mobile app, there are 200 test scripts that need to be created and run. Thus, the whole process is complicated. Then there is added pressure of reducing the time to market. The end result is there is less time for testing, which increases the risks to quality.
Heterogeneous testing environment
QA teams test on a huge number of devices, operating systems (OS) or browser combinations such as Windows, Safari on an iPhone7, etc. To test these combinations, you require a large number of testers in manual testing. Also, as ‘wearable banking’ is around the corner, testers will need to test banking apps on Apple Watch and Google Glass to serve digitally-savvy consumers.
Regression Testing and Data Security
In quality assurance digital transformation, it is challenging to perform cost-effective regression testing over an application’s lifecycle. It is necessary to ensure that testing takes into account system integration and test data usage is as per data confidentiality norms. To tackle these challenges, an effective test suite is mandatory, along with effective and robust test data management.
One of the best ways to deliver high-performance challenger banking application is to embrace Intelligent test automation. Automated tests are great for repeatedly; they provide exceptional accuracy and speed and helps in identifying errors in the starting phase of the development cycle. Developing a long-term testing framework and roadmap helps in the proper management of resources.
Comprehensive regression suites and performance scenarios can be executed numerous times daily through intelligent automation testing. It helps to allow changes to flow through the two final quality gates quickly and regularly while providing the business with the necessary confidence to implement the changes successfully into production. Intelligent test automation allows Development teams to give clear feedback on the reasons for failing change which over time improved the quality of future changes.
The challenger banks successfully introduced new solutions while enhancing their service offerings, internal processes, and industry compliance standards by implementing Artificial Intelligence and Machine Learning.
Here are some examples of common applications for these technologies:
Credit scoring and churn prediction
Process control and optimization (PCO)
Chatbots/customer service
Improved fraud prevention
customised products and services
Besides, the use of AI-driven strategies offers so many benefits. Some of these could be explained as:
1. Cost-effective
You can save up to 70% on application management costs with the use of AI-driven AMS. AI-driven AMS automates ticket management tasks, cutting down on the number of staff needed for the help-desk team and lowering costs.
2. Gain in productivity
By addressing the influx of recurrent tickets, AI-driven AMS lends the support team a helping hand and frees them up to focus more on other areas. The strong mentoring and knowledge management structure that replaces the reoccurring tickets boosts staff productivity.
3. Real-time knowledge of the growing trend
Knowing the most recent financial trends is usually advantageous for your bank. As a result, AI-driven AMS actively spots significant tendencies that can be improved.
4. Increased customer involvement
An organised view of the tickets is provided by AI-driven AMS, which aids in quicker issue debugging and prompt customer service. Additionally, AI-driven AMS offers insightful data that enables banks to better comprehend consumer preferences and improve customer engagement.
The popularity of digital banking among millennials and Generation Z presents a fantastic chance for challenger banks to excel. It goes without saying that the number of people using digital banking will only keep rising in the future, thus challenger banks should think about successful innovation.
Customers have already been drawn to challenger banks by their digital presence, and demand is rising. Challenger banks merely need to think strategically and generate concepts that will best serve their customers. Innovative solutions that are built to automatically obey rules, like AI-driven AMS, can also assist for more betterment.
At Bugraptors our experts provide strategic solutions for your challenger banking objectives.
For more information, contact us on info@bugraptors.com
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BugRaptors is one of the best software testing companies headquartered in India and the US, which is committed to catering to the diverse QA needs of any business. We are one of the fastest-growing QA companies; striving to deliver technology-oriented QA services, worldwide. BugRaptors is a team of 200+ ISTQB-certified testers, along with ISO 9001:2018 and ISO 27001 certifications.
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