for Banking and Finance

The following are three of the top applications of RPA in Banking and Finance:

1. 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.
2. 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.
3. 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.