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Robots—both physical and virtual—have become common elements of everyday life. They are also appearing in a growing number of industries, helping improve their efficiency. Banking is one such industry. How are robots changing banks, and what is the future of financial-process automation?
Banking robotization—what should you know?
Banking robotization simply means automating tasks and introducing robots into the banking environment. It may apply to customer service, data verification, document workflows or risk management. With RPA (Robotic Process Automation), robots can perform repetitive tasks, allowing employees to focus on more creative and demanding responsibilities. This can improve overall efficiency, reduce costs and lower the risk of errors. Interest in banking robotization is growing worldwide. This is consistent with the spirit of hyperautomation—the automation of processes using artificial intelligence, various forms of machine learning, and robots such as chatbots and voicebots. These technologies make it possible to manage more complex datasets and increase integration between different banking systems. Contrary to appearances, robotization does not pose a threat of job losses. Not every process can be automated, particularly in an industry as complex as banking. Even with extensive robotization, people are still required to operate and supervise robots.
Which banking activities can be robotized?
Robotization in banking can automate many activities previously performed by employees. These may be very simple duties or complex processes comprising numerous smaller tasks. The complexity of a process determines the technologies and tools required to automate it. Recognizing this helps avoid RPA-related mistakes. The processes most frequently robotized include:
- Identity verification—automatically checking a PESEL number, identity document or other documentation such as invoices and account statements can accelerate customer verification.
- Customer service—this includes chatbots and voicebots that can answer customer questions and requests regardless of the day or time. Customer-service automation often involves sending prepared responses to particular enquiries. It also works well in complaints handling, where standard cases can safely be assigned to robots. Robotization combined with machine learning supports greater personalization of customer service.
- Document management and workflows—processing, categorizing and archiving documents are among the business processes most frequently automated, so it is unsurprising that this also happens in banking, which handles large volumes of documentation. The receipt and dispatch of documents to customers or other banks can also be robotized. Various text-recognition and processing methods are frequently used for this purpose.
- Payment processing—assigning card and bank-transfer execution and posting to robots enables payments to be completed faster.
- Risk management—robots can support credit-risk assessment, monitoring of suspicious activity and fraud detection. They do not replace financial analysts, however, but can increase their efficiency. Data quality is another essential consideration. If data is poor-quality or biased, the robots’ results will also be poor and incorrect.
- Data analysis—robots can rapidly analyze different types of data and financial indicators, supporting better business decisions. Data analysis is also crucial to becoming a data-driven organization. Based on customer data and other factors, robots can automatically make decisions about matters such as loans, but they should be supervised: robots can also be wrong because they depend on the quantity and quality of available data.
How does robotization improve banking operations?
Automating payment processing, document management and data analysis can improve efficiency while reducing operating costs and the likelihood of errors. Robots also support customer service and help optimize numerous processes. Robotization allows banks to serve more customers and deliver services faster while improving accuracy and reducing risk. Robots are also invaluable in integrating different systems and improving communication between them. Robotization affects bank employees too. Above all, it relieves them of routine work so that they can focus on more complex and valuable tasks. This increases productivity and allows saved time to be used to develop the skills and qualifications of people working in banks.
How should robotization be implemented in banks?
Implementing robotization in banking usually requires a multidisciplinary team that includes developers, analysts, business-process experts and security specialists. As with other implementations, work begins by defining objectives and selecting areas and processes for robotization. Appropriate software must then be selected or designed. This depends on the particular bank’s requirements and should not take place without a prior business-process analysis. Once robots have been selected or created, they must be tested before deployment to avoid errors. Testing during and after implementation must not be overlooked either. Some defects are not immediately apparent, so robots should be monitored continuously to eliminate problems as quickly as possible. Staff should be trained before or alongside implementation. Employees must not only know how to use new tools and processes, but also understand their purpose and why they are being introduced. Alongside technical training, it is worth investing in courses showing how robots in the workplace will make life easier for banking employees.
Summary—what banking robotization delivers
Banking robotization offers numerous benefits to banks, customers and employees. It enables repetitive and routine work to be automated, improving overall efficiency and customer satisfaction. Robots also reduce operating costs and provide a competitive advantage. Importantly, robotization makes banks more flexible, allowing them to respond faster and more effectively to changing market and customer requirements.
