Reduction in Customer Onboarding Time
Reduction in Loan Processing Time
Reduction in Average Handling Time (AHT)
Banking & Financial Services
Financial Institutions face many challenges including margin pressures, changing customer expectations, non-traditional competitors, and ever-changing regulatory requirements. Given RPA can connect legacy systems, automate repetitive tasks, and tap into disparate data sources, it optimizes the use of data and human capital to keep up with changing customer and regulatory expectations, all while improving the efficiency of internal operations. This results in better and faster insights about your customers.
It is estimated that 44% of Financial Service processes can be automated to drive down costs, improve customer experiences, and even reduce risks. Primary RPA applications include:
Customer Onboarding/KYC Processes
Cycle time for loan processing can be cut by over 50% and increase agent productivity by over 70%.
Contact Center Operations
Financial Institutions handle a high-volume of customer requests and inquiries. These institutions are seeking to develop a best-in-class digital client experience, which requires a solution that gives agents instant access to the complete customer profile. Only then can the agent provide seamless and responsive service. Leveraging RPA and chatbots, leading-edge institutions have reduced AHT (average handling time) by up to 80%, increase transaction NPS by 10%, and reduced employee onboarding by over 20%.
Some examples of high-value added automations in customer contact operations include:
- Consolidation of client data into one interface for agent
- Classifying of customer emails and performing the predefined actions
- Completing a courtesy fee waiver based on predefined criteria
- Identifying cause of debit decline (tapping into multiple applications) during customer call
- Completing post-interaction work
Audit, Risk and Compliance
It is estimated that the cost of meeting regulations will exceed 10% of total costs in 2022. Improving audit and fraud detection processes can reduce regulatory risks, improve compliance, and reduce costs.
For example, a robot can assist the audit process by collecting the relevant documents and information, running it through an AI algorithm for signature & other verification, and flagging exceptions for human decision. RPA can also be deployed in legal document processing, such as policy and contract data validation and administration. Additionally, attended robots can assist in alert investigations by scanning through a customer’s history in seconds, saving precious time.
These automations can reduce manual hours required by up to 40%, so the team can focus on investigation and analysis. It also boosts compliance and reduces loss.