Banking The introduction of RPA in the financial world has helped banks significantly minimize human intervention in the execution of tasks and decision-making process. RPA makes it possible to increase operational process efficiency, lower costs, including regulatory compliance costs, while affording deeper analytical insight for banks. Today, most banks use RPA primarily for improving processes such as accounts management, loans attribution, financial monitoring, card operations, and reconciliation. RPA is also gaining increased popularity in such other key areas of the banking sector as regulatory and compliance, financial risk management, cyber risk and resilience, sourcing and procurement, and finance and accounting.
Software robots used in RPA can access multiple internal and external applications, thereby reducing delays in performing tasks caused by staff workloads.
Robots can check such credit applicant information as income, expenses and exposure across several databases and then assemble this information into a report for the credit analyst.
RPA software robots reduce the need for employee involvement in fraud detection by monitoring bank accounts and card activity in real-time. Robots also check internal and external data sources for suspicious activity.