How AI can solve the biggest challenges in online banking for traditional banks

In the age where consumer preferences are shaped by digital convenience, online banking stands as a pivotal factor in the selection of financial institutions. Interestingly enough, an overwhelming 91% of people consider digital banking crucial when choosing a bank. 

Despite this, the satisfaction with online banking services has seen a decline, with users reporting difficulties in customer service and timely problem resolution. This underscores the fact that there is still plenty of space for online banking to develop.

One of the more promising avenues towards such development is the implementation of AI. And in this article I am going to explain why I believe this to be the case. 

Key Challenges in Implementing Online Banking

First of all, let’s take a look at what problems banks face today when confronted with the idea of setting up online banking services.

Number one on the list are legacy systems. Many banks rely on outdated IT infrastructures, making integration with modern digital solutions complex and cumbersome. And yet, migrating to a new, contemporary core-banking system can be very expensive and time-consuming, often taking 1.5 to 3 years.

Next, there is internal resistance to consider. Employees and management accustomed to traditional operations may resist change, stemming from a skill gap and fear of job loss. The lack of digital expertise within the organization can further complicate the transition. And all the while, global technological development keeps marching forward. The number of professionals specifically skilled in servicing outdated legacy systems grows lower, which further exacerbates the problem. 

Upgrading or replacing old systems demands significant financial resources. Finding specialized talent familiar with both modern and outdated technologies is challenging, and ongoing maintenance of complex integrated systems can strain available resources. 

Not only that, but the integration process means the risk of downtime, which can lead to reputational and financial losses, marking yet another reason why many banks are reluctant to consider upgrading.

One last thing to bring up here is the risk of fraud. Online banking amplifies the risk of fraudulent activities, which are difficult to detect and prevent without automation. Traditional methods of fraud detection, which often rely on manual oversight and reactive measures, are insufficient in the face of cyber threats that grow more and more sophisticated. And implementing advanced fraud detection systems, once again, requires both labor and financial investments that banks may not be able to afford.

How AI Can Help Overcome These Challenges

Now, given everything we’ve covered above, how can artificial intelligence help the situation?

First of all, AI can facilitate a smoother transition from legacy systems to modern solutions. Banks can adopt a step-by-step approach, replacing components and services incrementally and integrating them with legacy systems through APIs. AI-driven automation can handle routine tasks, streamlining processes and taking over a lion’s share of the burden. Automated customer support, onboarding, AML monitoring, fraud detection, credit scoring, and document processing – all of these can free up a lot of resources and pave the way for further development.

Furthermore, by conducting replacements in stages, banks can better manage their expenses and the complexity of the whole process. Later on, the use of AI and Machine Learning components can yield returns that would offset the transition costs by automating low-level tasks and shifting human roles towards overseeing AI operations. This way, you can not only reduce staffing costs but also enhance operational efficiency in the long-term.

Lastly, AI can provide 24/7 monitoring with quicker response times and higher accuracy in detecting fraudulent activities. AI-driven fraud detection systems would vastly enhance the security of online banking, fostering greater customer trust.

All in all, while initial investments in AI systems can be considered substantial, to my mind, these costs are ultimately outweighed by the possible gains in terms of both reputation and prevented losses, as well as reduced labor costs.

Automize But Personalize Should Be the Motto

Taking a slight detour, I would also like to say that while automation is a crucial element in online banking, personalization also remains vital in enhancing customer experience and loyalty. 

According to a UK study, personalized banking is instrumental in restoring confidence in online banking, suggesting that a tailored approach can significantly improve customer satisfaction and retention.

By identifying and addressing unique customer needs, banks can tailor their services to individual preferences, fostering a greater sense of connection and trust. This approach enables clients to feel valued and understood, rather than just another account number. Enhanced customer experience, in turn, leads to increased customer retention. 

And given how competitive the financial landscape is, personalization offers a significant competitive edge. Banks that excel in delivering tailor-made experiences stand out from their crowd, attracting more customers by demonstrating their commitment to meeting their needs in a meaningful manner.

To sum up, the future of banking lies in a balanced integration of advanced technology and personalized customer service, paving the way for a more secure and user-friendly banking experience.