Did you know that AI in the banking market is poised to skyrocket to $64.03 billion by 2030, growing at a rapid annual rate of 32.6%?
This isn’t just impressive—it signifies a transformative shift in banking operations.
Take it from Jamie Dimon, CEO of JP Morgan Chase, who has noted the use of over 400 AI applications, highlighting the technology’s vast potential.
While many of these applications are well-known for automating routine tasks like customer verification, transaction processing, and data entry, AI is also making significant strides in monitoring and improving performance, availability, security, and scalability across the sector.
This article will focus on these innovative yet less visible AI strategies, which are critical for ensuring a seamless banking experience for customers while allowing IT teams to concentrate on strategic initiatives and innovation.
So, without further ado, let’s dive in!
1. Automation of Test Cases Generation and Execution
Banks serve millions of customers who access banking applications on various devices (mobile, tablet, laptop) running on different operating systems (Android, iOS, Windows, and more) and connected to networks with varying bandwidths. This results in thousands of permutations and combinations, making it practically and manually impossible to test each scenario comprehensively.
Additionally, these millions of customers range from regular users making simple UPI payments for everyday purchases to business users transferring millions of dollars in critical transactions. Banking applications are, therefore, heavily utilized and relied upon by a vast number of users. Furthermore, fraudsters are constantly seeking weaknesses or vulnerabilities in banking apps to exploit. Banks cannot afford to compromise on security, as safeguarding customers’ money is paramount.
To ensure that the apps perform as expected, even during peak usage, thorough testing is essential. However, even the most meticulous manual testers might overlook some test cases, potentially leading to disruptions, frustrated customers, and financial losses for banks.
In contrast, AI offers a transformative approach to software testing, greatly enhancing both the efficiency and reliability of banking applications. Here is how:
- Test Cases Generation – AI leverages historical data, such as previous test results, software usage patterns, and bug reports along with user interaction logs to identify critical test scenarios. It then creates targeted test cases that ensure comprehensive coverage, continually optimizing based on new data to adapt to changing application use.
- Test Cases Execution – AI automates the selection and prioritization of test cases based on their historical failure rates, the complexity of the tests, the urgency of critical functions such as payments or account checks, and any recent updates or untested changes made to the software’s codebase.
Additionally, this automation shifts IT staff from repetitive tasks to strategic initiatives that foster innovation and strengthen the bank’s competitive edge in the market.
However, an important consideration here would be selecting the right technology partner who can customize these automated testing solutions to seamlessly integrate with your bank operations, thereby boosting operational efficiency and ensuring compliance with stringent quality standards.
Also check – How to Select the Perfect Test Automation Services Vendor?
2. Anomaly Detection and Self-Healing Capabilities
In banking operations, anomalies can cause significant issues. These include sudden slowdowns, crashes, and unusual spikes in resource usage, which suggest system malfunctions. Significant fluctuations in network traffic may indicate a cyber attack. Odd login patterns could signal unauthorized access. Such anomalies can lead to downtime, service interruptions, and ultimately, customer dissatisfaction.
These anomalies can be detected by application monitoring tools like Dynatrace, AppDynamics, Datadog, etc., which log extensive information about application performance. Going through this information manually is slow and error-prone.
However, with the advent of AIOps—Artificial Intelligence for IT Operations—banks are now equipped with tools that blend machine learning and big data analytics to automate and enhance anomaly detection. AIOps monitor systems continuously, identify root causes by connecting data points, and predict potential issues, making detection not only faster but more accurate.
Upon detecting anomalies, AIOps can initiate automated corrective actions. This might include reallocating resources, optimizing workflows, or applying software patches, effectively allowing the system to self-heal.
Such capabilities transition the bank’s approach from reactive problem-solving to proactive problem prevention, reducing downtime and enhancing overall customer satisfaction.
3. Effectively Managing IT Infrastructure
AI can predict potential failures in IT hardware and software components.
It can foresee impending issues such as server failures, storage capacity constraints, or network bandwidth bottlenecks, enabling banks to schedule maintenance activities in advance.
This proactive approach is crucial for maintaining the reliability and availability of banking services, which are expected to operate 24/7 without interruption.
AI algorithms can also dynamically allocate computing resources based on workload demands and performance metrics. For instance, during peak transaction periods, it can automatically allocate more server power or bandwidth to handle the increased load efficiently.
Conversely, during periods of low demand, it can reduce resource use, thus saving on energy costs and reducing operational expenses.
This intelligent scaling ensures that the bank’s IT infrastructure is not only effectively performing but also cost-efficient, adapting in real-time to changing demands without human intervention.
As we’ve explored, AI’s role in enhancing banking application performance is undeniable. It offers banks the ability to automate complex operations and predict potential system issues before they impact service. However, it is crucial to choose a technology partner that excels not only in enhancing performance with AI but also in scaling and securing banking operations.
This is where Avekshaa Technologies can be a standout choice for you to partner with. Let’s understand why.
Why Banks Choose Avekshaa to Improve their Application Performance?
The potential of AI to supercharge banking is immense, and as this technology evolves, the benefits will only multiply. It frees up time from mundane tasks, allowing banks to focus more on innovation. This is where Avekshaa Technologies excels, positioning itself as the ideal partner for integrating smart, AI-powered solutions in the banking sector.
With over 12+ years of expertise, Avekshaa helps banks enhance operations and manage IT infrastructure by detecting anomalies and implementing self-healing mechanisms to improve performance, reliability, and security.
Specializing in digital transformation and application performance management, Avekshaa offers tailored solutions to enable seamless banking operations. We conduct regular infrastructure assessments, provide advanced monitoring solutions (AIOps), and ensure smooth migration of banking applications to new platforms while preserving performance and reliability. Our cloud engineering capabilities handle increased data loads and guarantee flawless migrations.
In a notable case study, Avekshaa’s P-A-S-S™ optimization resolved performance and availability issues across 3,000 branches and 10,000 ATMs, achieving significant database performance improvements.
Avekshaa minimizes performance, availability, and scalability risks while ensuring compliance with industry regulations. Partnering with Avekshaa not only enhances IT performance but also gives banks a competitive edge.
Get in touch with the experts at Avekshaa to discover how AI can transform your bank’s operations and elevate your digital transformation journey.
FAQ
What is the Future of AI in Banking?
AI is set to dramatically enhance banking by automating complex decision-making processes and improving customer interactions through personalized services. It will also increase efficiency and security, handling everything from risk assessment to compliance with evolving regulations.
How Does AI Improve Customer Experience in Banking?
AI enhances customer experience in banking by offering personalized recommendations, enabling efficient query resolution via chatbots, and ensuring seamless digital interactions across platforms.
What is AIOps?
AIOps (Artificial Intelligence for IT Operations) integrates AI and machine learning to automate and optimize IT operations. It enhances system reliability, improves efficiency, and reduces operational risks.
Which is the Best AIOps Provider for Banks?
Avekshaa Technologies stands out as a top AIOps provider for banks. It is known for proactive management of IT anomalies, performance optimization, and operational excellence through innovative AI solutions.
How Does AI Improve Reporting and Compliance in Banks?
AI simplifies report creation by quickly summarizing large amounts of data and helps banks follow rules accurately. It also helps in making better decisions by analyzing financial trends.