How to Avoid the Pitfalls of RPA and AI in Banking

Pressure is mounting for the banking industry to find better ways to meet evolving customer demands and service a quickly expanding number of customers.

Demands on the banking industry are mounting

As you can probably imagine, consumers’ expectations and demands when it comes to banking are extremely high. Today, we all expect that banks will protect our hard-earned money, while providing high quality and fast service, around the clock. And if they don’t, we’ll simply take our money elsewhere.

During the last century, banking has experienced a huge expansion, in large part due to technological advancements. These advancements have greatly increased the number of people worldwide that now have one or even multiple banking accounts. And this, of course, means that the systems and people that used to work with a few hundred customers, now need to service to thousands.

This last point begs the question, “but how is that possible?” Well, it all comes down to optimization. Banks need to optimize both systems and processes to handle a growing number of customers as well as the increasing expectations and demands those customers place on banks.

How emerging technologies like RPA and AI can help banks optimize…everything

The good news? Groundbreaking technologies like artificial intelligence (AI) and robotic process automation (RPA) are providing powerful ways to optimize systems and processes in banking (and many other industries), helping banks ensure growth and sustainability into the future. The effect these technologies will have in the coming years cannot be underestimated – it can be likened to the monumental shift the discovery of electricity had on businesses and individuals in the 18th century. And just like that fateful moment in time, today, it will be the companies that most fully leverage technologies like AI and RPA that come out on top.

To learn more about what RPA is and what it is not, check out our infographic!

But before diving headfirst into AI and RPA, it’s important to consider a few key areas of caution.

Pitfall #1: Tunnel vision

Knowledge of RPA and AI is still quite limited. This lack of understanding could lead many organizations to severely limit the application of the technologies. For example, having a chatbot is a well-known form of automation and AI. But a chatbot, or any other singular application, is just the tip of the iceberg. Be sure to do your research and consult with an RPA expert to ensure you identify all areas of the business where RPA and AI can optimize processes and systems. A few of the many areas to consider include loan processing, credit analysis, fraud detection, opening or closing accounts, cybersecurity, among many others.

Pitfall #2: Applying RPA to inefficient processes

Many companies that jump on the RPA bandwagon too quickly don’t stop to first evaluate the efficiency of processes they intend to automate. Automating inefficient or ineffective processes is possible but will greatly hinder the benefits you can expect to see in the long run. To ensure you maximize the cost- and time-saving benefits of RPA, be sure to thoroughly review each process you intend to automate and ensure it’s designed in the most streamlined way possible.

Pitfall #3: Failing to fully leverage the combined power of RPA and AI

The third and final area of caution relates to the difference between RPA and AI, and how the two can work together to provide optimal results. RPA is a great tool to automate processes, but it’s also a fundamental pillar of artificial intelligence. For example, the processes automated by RPA can provide the input artificial intelligence needs to make decisions. Individually, these two powerful technologies offer a set of solutions, but when combined, they can become part of true innovation that helps accelerate your organization’s digital transformation. A lack of a deep understanding of how each of these technologies works and how they can impact your business both separately and together, will likely result in a series of temporary solutions with limited impact on long-term business objectives.

The Bottom Line

The speed at which banks are able to correctly implement these revolutionary technologies will have a considerable impact on their growth and success in the coming years. This becomes even more significant when you consider the results of recent socioeconomic studies that describe the close relationship between a country’s financial system and its economic growth. In other words, the growth of banking will determine the growth of modern economies, significantly influencing global economic progress as a whole, particularly that of developing nations.

Although speed is key in the banking industry, it’s worth taking a moment of pause to consider the three areas of caution outlined in this article to ensure you apply RPA and AI to the right areas of the business, don’t miss out on the full time- and cost-saving benefits by automating inefficient processes, and take full advantage of the combined power of RPA and AI.

Juan Barajas

RPA Developer

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