Robotic Process Automation (RPA) is one of the most compelling automation use cases in the financial services industry. Financial institutions are under constant pressure to reduce costs and eliminate errors, and RPA makes efficiency easy.
The Impact of Human Error in Banking
Human error in financial services can lead to considerable financial losses. Gartner estimates these mistakes lead to over $878,000 in wasted time and labour each year. As banks aim to minimise errors and streamline their processes, there is a clear place for automation-led improvements.
RPA vs. AI: Understanding the Difference
While RPA and Artificial Intelligence are often mentioned together, they serve different purposes. Automation software developers, Appian, describe their differences in relation to humans: RPA mimics how people act, whereas AI mimics how people think.
RPA focuses on automating repetitive manual tasks, such as data entry and processing transactions, whereas AI handles tasks that require cognitive abilities, such as decision-making and problem-solving.
Combined, RPA and AI have the potential to significantly enhance process efficiency and accuracy.
The Crucial Role of RPA in Financial Services
Financial institutions face several challenges, including:
- Scarcity of skilled labour
- Increasing labour costs
- The need for improved process efficiency
The power of RPA lies in its ability to automate routine tasks, freeing up human resources to focus on more strategic activities. It lets banks reimagine what is possible within their operations.
This enhanced efficiency means more productive workforces for lower costs.
Benefits of RPA in Financial Services
The benefits of RPA in financial services include:
- Improved Accuracy: By automating repetitive tasks, RPA eliminates the risk of human error and ensures data processing accuracy.
- Cost Savings: Automation reduces the need for manual labour, leading to significant cost savings in operations.
- Enhanced Efficiency: RPA can process transactions and tasks much faster than humans, increasing the overall efficiency of banking operations.
- Regulatory Compliance: RPA ensures processes are consistently executed according to regulatory requirements, reducing compliance risks.
- Scalability: RPA solutions can be easily scaled up to handle increased volumes of work without proportional increases in human resource costs.
Popular Use Cases of RPA in Banking and Finance
RPA is already being used in various ways within the banking and finance sectors. Some common use cases include:
- Customer Onboarding: Automating the process of collecting and verifying customer information during account opening.
- Transaction Processing: Speeding up the processing of transactions, such as payments and fund transfers.
- Regulatory Reporting: Ensuring accurate and timely submission of regulatory reports by automating data extraction and reporting processes.
- Fraud Detection: Enhancing fraud detection capabilities by continuously monitoring transactions and identifying suspicious activities.
- Loan Processing: Automating the review and approval process for loan applications, reducing turnaround times.
RPA: Automation for Financial Services
The adoption of RPA in the banking and finance industry is not just a trend but a necessity. By automating financial operations, banks can significantly enhance their efficiency, reduce costs and minimise errors.
As technology continues to evolve, the potential for further innovation and improvement in banking operations is immense. Embracing RPA today will ensure that financial institutions remain competitive and capable of meeting the demands of the modern world.
OFS can help guide you in finding the right talent to evolve along with your technology. For more information, get in touch with the team.
