Robotic Process Automation (RPA)

An increasing number of financial institutions are identifying processes suitable for Robotic Process Automation (RPA). However, much of the technology’s potential remains untapped. Intelligent RPA in the banking sector needs to be seen not just as a one-time phenomenon that will increase productivity and efficiency by driving down costs and increasing profitability, but as an evolving paradigm that will have distinct stages of maturation spanning from transactional to transformational and disruptive. What we are currently seeing is just the first stage.

According to trade analysts, the BFSI sector is set to make approximately 44% of investments in RPA over the next couple of years. Financial institutions are increasing their budgets for robotic automation, with a focus on managing regulatory pressures, risk and fraud, aggressive competition, and innovation.


Current Applications implementations of RPA in below areas:

Today, most banks use Robotic Process Automation within a transactional framework primarily for improving processes such as accounts management, loans attribution, cards operations, or reconciliation. Banks are embracing intelligent automation to stay relevant and drive higher bank performance and productivity. Some banks have improved their productivity by 35% to 50% as an aggregated benefit from automating thousands of transactions, thereby ensuring greater agility. Banks are adopting robotic automation to reduce costs and increase efficiency in their operations in areas such as mortgage lending, customer service and support and IT.

RPA is also gaining increased traction in other key areas in the banking value chain such as regulatory and compliance, financial risk management, cyber risk and resilience, sourcing and procurement, and finance and accounting. In regulatory and compliance, RPA can drive unparalleled efficiency in critical areas of governance and compliance and risk assessment, while facilitating detailed auditing and reporting processes. Apart from ensuring data quality control, RPA is increasingly being deployed to automate processes of credit and market risk exposure and operational and transactional risk in financial risk management.

RPA can ensure robust and resilient processes in the area of cyber risk, where it is being deployed to build resilience strategies, anti-money laundering protocols, zero-fault tolerance architectures and faster recovery in events of security breaches.

End-to-end sourcing and procurement processes, which encompass procure-to-pay, contract management, supplier management, spend analysis, and order-to-cash, have also become one of the key reasons for increased deployment of RPA in banks.

RPA is becoming ubiquitous in finance and accounting functions of banks, wherein benefits of faster and error-free P&L reporting and analysis, on-time management of accounts payable, account receivable, efficient treasury management, effective deployment of internal controls, and record to report (R2R) are some of the benefits that banks can derive by deploying RPA.

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