RPA mimics the ways human execute a job by manipulating data, interpreting existing applications and triggering communication using a user-friendly interface. These robots learn from prior decisions and data pattern to make their own decisions. However, they need expert supervision to choose the right methods to be used in meeting organizational goals.
RPA Use Cases
Accounting: In the financial industry, the impact of RPA is enormous. First, it helps in operational accounting by maintaining data for accounts receivable and billing. It also works well in general accounting procedures by taking care of allocations, adjustments and journal entry procedures. RPA can bring reduce the number of people needed to carry out simple data entry and repetitive task. It can also take care of planning, budgeting processes, forecasting, and financial reporting. Even in a shared service environment RPA can be successfully implemented to replace some human workforce and also reduce risk if human error.
Quick account opening: Banks needs to verify customer’s identity and details before opening an account. RPA works well here because it can help in the validation of customers identity and details such as past credit records. With RPA new accounts can be created using software robots and delivered to the client with little or no stress.
Reduces challenges with card activation: When activating a customer card a lot of processes are involved from checking compliance rules to coordination between departments to ensure data consistency. Software robots help address inconsistencies that might be generated through human error. With RPA the organization is left with more satisfied customers and fewer stressed employees.
Track Investment value: RPA helps to track the value of investment despite changes that might occur over time. They have access to an investor’s portfolio, and RPA tools can also serve as financial advisors without human intervention.
Prevents money laundering: Preventing money laundering is a priority and RPA can make a significant contribution in helping companies fight money laundering. They make use of validation rules to cross-check information supplied by the customer and check for discrepancies, thereby boosting the reputation of the financial institution.
The impact of RPA in financial services is likely to be enormous. Businesses that want to remain competitive, reduce human error and increase productivity need to take advantage of all the benefits this technology offers.Last modified on Thursday, 15 November 2018