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Why Credit Card Transactions and Banking Operations Have Successful RPA Implementations

Transaction based companies that are highly regulated are a naturally ripe spot for Robotic Process Automation. Large payment processors like MasterCard, Visa and many banks like Capital One and Barclays have become the poster child for RPA initiatives. When looking at workflows to evaluate KPI for an RPA Implementation, often overlooked criteria are scale and executive buy-ins from business operations to support that scale. Business Operations must push the automation initiatives in multiple sectors of the business to levels that truly make RPA worth the time and investment. This is achieved by addressing core processes within the business for automation as opposed to processes on the fringes.

In this article we will look at some of those operations and ultimately how these companies have been able to save on hundreds of employees and improve bottom lines by hundreds of Millions per year.

Credit Card Authorization Disputes:

In this example, we will discuss disputes for transactions under a certain threshold:

As you could imagine, this is an example of a process that needs to be executed on a regular basis and has significant volume for a large credit card processor. It requires some complicated rules to evaluate each case, as well as an email to the end customer with the results. Although a significant part of the process is based on templates, the average time to manually handle each transaction is 8 minutes. Using a bot, this same process can be performed in under 2 minutes.   This is a type of process that has a very structured workflow and would be ripe for automation, but more importantly, has the scale needed for it to make a major impact to the business operations.

Trade Settlement:

Here we discuss the back-office trade settlement operations for an investment bank. This task often requires significant manual processing of data that is often prone to error and can have a huge monetary impact on the business. The most labor-intensive part comes from the extensive research and communication between different counter-parties and custodians via email to identify unmatched and pending trades.

In this case, the average handling time of trade processing went from 40 minutes down to 3 minutes while also avoiding very costly errors. Depending on the scale this can save the back office over 400 hours per year.

There are many other examples of a front or back office area of these transaction based operations but the point of this is to understand that the most successful implementations look at the scale of each process. Now there is also another challenge to overcome, and that challenge is, ironically, the same thing you need for success, SCALE. In order to accommodate business scale, a business is often left with a CoE that has several years of backlogged work all while still trying to find an affordable development path. The reason for this is as soon as a developer has more than a year of experience in this industry, they will have an opportunity to jump ship (most likely to one of the big 4) where they can often double what they were making their first year. This is where partnering with a niche firm has its short and long-term advantages. Initially, in the short-term, you have senior resources to get initiatives off the ground, but in the long-term, you can bring in lower cost junior resources to help offset development costs. Now, you may think that offshore is another lower cost option, but trends show that while these resources may save you 30-40% on the labor, execution time is often significantly longer, which offsets the cost and ultimately puts the business further behind in recognizing their ROI expectations. Ultimately, to be a poster child for an RPA implementation, you constantly need to be looking at the scale, building up internal resources to become champions of business operations and utilize a strong strategic partner to help “Accelirate” your RPA initiatives.