We are living in a digital age and thus, no global financial institution can be impervious from automation and the advent of digital operative means. Banks and the financial sector were among the first automation adopters taking into account a large number of advantages of adopting IT. The reason why banking automation took pace embraced IT automation is that their operations take a lot of time and effort when done in a manual way as well as making their staff do routine activities over and over again leads to loss of productivity and lacking the opportunity for advancement on the value chain.
There are several other benefits that automation can provide to the banks and financial organizations. The future is bright, despite some early setbacks in applying robotics and artificial intelligence (AI) to banking processes. The technology is evolving, and domain competence is developing among both banks and vendors, many of whom have already left the one-solution-fits-all approach towards more specialized approaches. Let’s see how adopting these techniques has worked in the industry and society.
Every day, banks handle many questions ranging from account information to application status to balancing information. It can be a huge task for the customer service staff to answer all these queries with low turnaround time. Robotic Process Automation (RPA) is a process that can be of tremendous help here. RPA can automate these rule-based processes to respond to queries in real-time and cut turnaround time to seconds, freeing human resources for more important tasks. With the aid of artificial intelligence, RPA can also solve queries that need logical reasoning or decision making. A chatbot, with the aid of NLP, can understand the natural language to talk to the customers and respond like a human.
AML and KYC
In any financial institution, money laundering is a pressing issue. Also, Before opening or operating an account, financial institutions made it mandatory for the customer to fill out the Know Your Customer form. These values called Anti-money laundering (AML) and know your customer (KYC) can meet by automating the business processes. Both AML and KYC are data-based processes that make them good AI and automation candidates. Many banks around the world are working on automated systems for reviewing AML systems and identifying suspicious transactions. RPA has also proven a better option in these instances than the orthodox business management solutions cost and implementation time. Talking about KYC, while banks like to digitize an end-to-end process, which requires changes in the involved systems, an automated solution can deploy to bridge the integration gap between the new and already used systems.
Account management in the banking system is a simple yet monotonous process. This needs information from the manufacturer to collect, check, and then payment processing by the cashier or worker. This is the example of a system that can automate and train an AI system. RPA, with the aid of optical character recognition (OCR) technology, can solve this problem. OCR can read the seller’s information in a physical copy form and provide the system with information. RPA validates the information and processes payments using the information in the system. RPA may notify the executive for resolution if there is an error.
There’s no question that banks know how to handle money, and it’s no surprise to hear that the banking industry is one of the first to use the latest technologies for cost handling and savings. As described above, AI automation increases efficiency accelerates the time spent and reduces human error, so that banks can make a huge difference in cost savings. Half of the banks stated in an Accenture Technology Vision survey have achieved 15 percent or more in cost savings from incorporating automated systems. In some areas of financial services, prices have cut down to 80% and the time required to perform activities has reduced up to 90%. These figures give a pretty good idea about how business process automation can leverage your company.
The organizations that combine human intelligence and machine intelligence and use their coexistence in their goods, services, and business models will be the effective financial institutions of tomorrow. AI automation will continue to add value to employee tasks, deliver better customer experience and cheaper services, and return stronger value to investments by shareholders.