What is RPA in the Banking and Finance Industries?
RPA in the banking and finance industries provides operational cost savings and improved accuracy in many ways. Today, RPA is performing tasks to improve efficiency in Commercial Banking, Retail Banking, Lending, and Finance.Get In Touch
RPA Use Cases for Banking and Finance
The following are three of the top applications of RPA in Banking and Finance:
- Data Entry
- One of the strongest applications of RPA in banking is to improve the speed and accuracy of manual data entry. RPA can complete manual data entry tasks with 99.99% accuracy. Not only does data integrity vastly improve, but employees who are in these manual roles see notable increases in employee engagement metrics across the board.
- Customer Onboarding
- Customer onboarding is a vital process for banks and one that involves multiple layers of security and identification validation. RPA can help eliminate manual errors that can occur during the process while saving significant time and effort for the back-office operations team.
- Anti-money Laundering (AML)
- One of the most recent use cases for RPA in banking and finance is the automation of Anti-money Laundering processes. Typically, this process is highly manual and can take 45-60 minutes to complete a single case. The repetitive nature of each case lends itself well to automation with RPA and can drastically cut processing time, resulting in faster case resolution.
RPA Benefits in Banking and Finance
- Improved security
- Because RPA shifts much of the work typically done by humans to machines, there is significantly less opportunity for fraudulent activity to occur. In addition, irregularities in the process can be monitored and responded to in real-time, making it more difficult for internal and external bad actors to take advantage of the system.
- Regulatory Compliance
- The banking industry is held to a high standard for documenting work and creating audit trails. With so many error-prone processes, the risk of regulatory non-compliance can be a costly issue. RPA can help improve the accuracy of validating customer information as well as improve regulatory reporting. Lastly, reports can be generated automatically and provided to stakeholders at custom intervals.