Robotic process automation (RPA) is one of the most exciting trends in business technology right now. RPA software "agents," enhanced with artificial intelligence capabilities to make smarter decisions, are able to automate and optimize a variety of processes.
In particular, RPA is well-suited for companies that need to complete a great deal of repetitive, predictable tasks with a superhuman level of accuracy, which makes the financial services industry the perfect fit. In this article, we'll investigate some of the ways that financial services companies are making use of RPA and the benefits they stand to gain by doing so.
What Are the Advantages of RPA?
- Lower costs: According to a survey by Accenture, RPA offers the potential to decrease costs by up to 80 percent.
- Faster speeds: The same survey also found that RPA agents can make tasks and processes between 80 and 90 percent faster.
- Better scalability: Using RPA agents to deal with surges in customer activity is much easier, faster and more scalable than hiring new employees.
- Increased accuracy: RPA removes the potential for human error from the equation, making results more accurate and predictable.
- Improved compliance: Many financial services companies face industry regulations such as the Sarbanes-Oxley Act. Using RPA makes it easier to document and log your processes to prove compliance.
How Are Financial Services Companies Using RPA?
As mentioned above, RPA is best for repetitive activities that require little intervention and that computers can do much faster than humans. Financial services companies across different sectors are all leveraging RPA and seeing massive benefits in the process.
Many of the activities surrounding customers' bank accounts can be automated using RPA. These include creating new accounts and migrating them to new systems; processing credit card orders and detecting fraudulent activity; and deleting old account data at regular intervals.
RPA agents can also assist in many of the services that consumer banks offer to their clients. For example, they can calculate mortgage and loan rates based on a customer's credit score and history with the bank. You can also use RPA agents to determine whether customers qualify for refinancing their loans and send them notifications about loans that are in delinquency or default.
Capital markets must thoroughly vet potential customers before they begin trading. RPA agents are already used to perform checks of customers' credit and identification. They can also perform fraud detection and other important analyses, such as assessing a customer's risk of money laundering, identity theft or terrorist activity.
Once customers enter the marketplace, companies can leverage RPA to distribute their dividends and interest regularly and in a timely, accurate manner.
RPA agents can assist insurance companies at every stage of the sales funnel, from generating leads to cross-selling and upselling. For example, you can use RPA to automatically download leads from websites that allow visitors to comparison shop with different insurance providers.
From car insurance to life insurance, RPA agents can update a customer's policy based on claims and events. Not only can they accurately distribute payments, they can also find and correct data discrepancies on multiple systems.
As financial services companies see the benefits of using RPA, we expect that more and more of them will take the leap. In the workplace of the future, RPA won't be a competitive edge any longer. Instead, it will be a necessity for companies seeking to provide high-quality performance and service in a crowded financial services landscape.