We live in a modern age, and therefore no global financial institution can be impeded by technology and the implementation of new operating tools. Banks and the finance industry were among the first to adopt automation, taking into account the many benefits of the application. The explanation of why bank automation took pace with IT automation is because it takes a long time and energy to work manually, and that repetitive operations are carried out by their workers time and time again—leading to a loss of productivity and a lack of resources to develop the value chain.
Automation will provide the banks and financial institutions with many other advantages. Despite some early reverses in the application of robotics and artificial intelligence (AI) in banking systems, the future is promising. The technology evolves rapidly, and market expertise among banks and suppliers are developing, many of whom have already abandoned the one-solution approach to more advanced strategies. Let's see how these methods work in business and society as a whole.
Banks answer numerous questions every day, ranging from details about their deposits to the payment status and the balance. Responding to all those queries with low turnaround time can be a massive task for the customer service staff. Robotic Process Automation ( RPA) is a process that can be of great help in this respect. These rule-based processes can be automated by RPA to respond to queries in real-time and minimize turnaround time to seconds, freeing human resources for more critical tasks. RPA can also solve questions that require logical reasoning or decision-making with the help of artificial intelligence. A chatbot can easily understand the natural language to speak to the customers and respond just like a human, with the help of NLP.
Banking system account management is a tedious but straightforward process. This includes data to be obtained, checked by the supplier, and then handled by the employee or cashier. It is an example of a program which can be implemented quickly by a professional AI system. RPA can easily overcome this issue using OCR (Optical Character Recognition) technologies. OCR can read and send information to the seller in a hard copy format. The RPA validates data and processes payments using system information. If there is a mistake, RPA can alert the resolution administrator.
KYC and AML
Money laundering is an urgent problem in any financial institution. Furthermore, financial services required that the client file the Know Your Customer form before opening or running an account. This principles, which are considered money laundering (AML), can easily be achieved by automating business processes and are recognizable to the client. AML and KYC are processes focused on data which make them suitable applicants in the field of AI and automation. Many banks worldwide work on automated systems to scan and detect suspicious transactions of AML systems. In these instances, RPA has also demonstrated better cost-effectiveness and implementation options than orthodox business management solutions. When talking about KYC, while banks want to digitize a complete process that needs changes to the systems concerned, an automated solution can be implemented that bridges the integration gap between new and previously-used systems quickly.
Banks know how to manage money, there is no doubt, and it is no surprise to hear that the banking industry is one of the first to use the latest cost and savings technologies. As mentioned above, AI automation improves performance, speeding up the invested time and reducing human error, enabling banks to make significant savings. Almost half of the banks mentioned in the Accenture Technology Vision survey have realized cost savings of 15 percent or higher from automated systems integration. Prices have been cut by 80% in some parts of financial markets and up to 90% of the hours available for operations have been reduced. These figures give you quite a good idea of how your company can benefit from business process automation.
The successful financial institutions of tomorrow will be organizations which consistently combine intelligence and artificial intelligence and use their coexistence in their products, services and business models. AI automation will continue to add value to the tasks of its employees, provide customers and less costly services, and provide a more substantial amount to shareholders' investments.