Robotic process automation (RPA) is increasingly being adopted by investment banks to improve efficiency and reduce costs. By automating repetitive, rules-based tasks, RPA allows banks to cut costs, improve operations, and focus on more value-adding activities. In this article, we will look at some examples of how leading investment banks are using RPA in their operations.
Client onboarding and KYC
One major use of RPA in investment banking is for client onboarding and know-your-client (KYC) processes. Tasks like data entry, document collection and review are prime candidates for automation. Banks like Goldman Sachs, Morgan Stanley and Credit Suisse are using RPA bots to reduce manual work in KYC and improve turnaround time. Bots can also ensure standards and compliance in client onboarding.
Trade processing
Post-trade activities like trade confirmation, settlement instructions and registrations can be automated using RPA bots. This improves accuracy, reduces settlement failures and allows faster trade processing. Many banks have achieved straight through processing rates above 90% through automation. RPA also helps banks reconcile internal systems and ensure adherence to regulations.
Report generation
By pulling data from multiple systems, RPA bots can automate the generation of client reports, portfolio summaries, risk reports etc. This reduces the manual effort required to generate these reports. The bots can also check for anomalies or errors in the reports. Standardized reports can be completely automated while exceptions may require human review.
RPA improves efficiency and reduces costs for investment banks by automating repetitive, manual tasks. Client onboarding, trade processing and report generation are some examples where RPA is adding value. As the technology matures, we can expect more intelligent automation in banking operations.