Banks and other financial institutions that take advantage of RPA have seen first-hand how this AI technology is both labor-saving and cost-effective. Business Insider Intelligence’s AI in Banking report details three RPA examples:
OCBC: The Singaporean bank has been able to reduce the amount of time to re-price home loans from 45 minutes to just one minute by using RPA. The RPA checks the customer’s eligibility to have their home loan re-priced, recommends re-priced options, and even drafts the recommendation email.
Sumitomo Mitsui: Automation in banking has allowed this Japanese financial institution to cut out 400,000 hours of manual labor for employees.
DBS: DBS partnered with IBM to scale an enterprise-wide Centre of Excellence (COE) in RPA – highlighting the growing desire of financial institutions to expand RPA beyond back-end operations. Just five months after the COE was initially set up in June of 2017, DBS had already optimized more than 50 complex business processes.
RPA has proven to reduce employee workload, significantly lower the amount of time it takes to complete manual tasks, and reduce costs. With artificial intelligence technology becoming more prominent across the industry, RPA has become a meaningful investment for banks and financial institutions.
According to Business Insider Intelligence’s AI in Banking report, financial institutions’ implementation of AI could account for $416 billion of the total potential AI-enabled cost cuts across industries, which are estimated to be $447 billion by 2030.