At SS&C, automation has long been a core building block for our investment operations and accounting platforms. Historically, we have leveraged sophisticated enterprise tools to improve process efficiency and reduce costs through automation.
Technological advancements present new opportunities to drive even greater value from automation. Within our Application Development and Hosting teams at SS&C, we are seeing that robotic process automation (RPA) – alone or combined with other next-generation technology like machine learning – can provide dramatic improvements in automated workflow, further reduce or eliminate manual processes and create substantial cost savings for our clients.
The global market for software enhanced with robotic process automation (RPA) is forecasted to enjoy tremendous market growth in 2021 and beyond, which represents a big opportunity for SS&C and our clients. Read on to learn more about the evolution of RPA and the advantages of an RPA model over traditional back-end automation.
What is robotic process automation?
Although the term conjures up images of mechanical arms on industrial assembly lines, the “robotic” in RPA refers not to physical machines but to automation software that can execute highly repetitive workflows, activities and tasks without human intervention.
How can RPA benefit my business?
Presently, the most exciting opportunity within the financial services sector is in automating end user tasks – particularly the repetitive, time-consuming and sometimes mundane tasks from the “must-do” list of daily processes. Properly trained robotic automation software (sometimes called “bots”) are well-suited for end user tasks because they are quick and reliable, can work unlimited hours, operate with complete fidelity and can be monitored and audited. Bots offer significant cost savings as they extend the working day to 24/7 and free up the workforce to focus on more value-added tasks.
What processes are good candidates for RPA?
According to a 2017 report from Accenture, simple, high-volume and intensively manual processes with low exception rates and a high risk of human error are good candidates for RPA. These might include new account setup, trade validation, reconciliation or various forms of standard reporting. For example, in the middle-office operations world, RPA can be used to ensure an appropriate accounting entry is inserted or updated in the general ledger every time a trade is modified, or a price or factor is recalculated on a position. RPA can also be used to automate a number of manual steps in position reconciliation, such as fetching multiple independent prices and generating an email with the results to a custodian, when a break is identified due to a nominal amount discrepancy.
What is the different between RPA and Machine Learning?
Machine learning is a type of artificial intelligence that enables computers to “learn” without being specifically programmed to do something. Unlike machine learning, RPA does not have the cumulative learning capability to perform tasks without instruction. Once activated, however, RPA systems can vastly accelerate many processes historically performed manually, while simultaneously improving accuracy. And, RPA can be used in conjunction with machine learning.
How is RPA different from traditional back-end automation?
The chart below outlines some of the ways RPA, alone or in conjunction with other next-gen technology, differs from traditional back-end automation.
Whether we’re talking about traditional automation tools or next-generation technology such as RPA, the value these tools provide is only as good as the application knowledge and industry expertise used to build them.
To be most effective, robotic automation tools must be thoroughly trained and tested to produce very specific and accurate outcomes. This takes highly specialized investment operations and accounting expertise across front-to-back-office functions, and a wide range of asset types, markets, regulatory requirements and financial services business models.
Asset Management, Wealth Management