Banking is one of the industries which has undergone a massive technological shift. The digital era of banking has come, and the customers are expecting a consistent service experience- be it online, mobile, kiosks or the bank branch. This digitization has improved business efficiency, enabled cost saving, a faster internal and external process, and accurate and reliable performance.
Artificial intelligence, robotics, and data analytics are often talked in connection with the banking sector. Banks are taking advantage of these complementary and overlapping technologies. Accuracy, predictability and human-induced error-free are primary goals of introducing technology into the banking industry.
The rise of robotic process automation (RPA) provided banks a way to automate repetitive clerical tasks. For example, requests for replacement of credit cards or loan applications. After training these systems can perform tasks in a shorter time with greater accuracy and at a lower cost compared to human labor. Also, chatbots are already established as ways to handle phone/website queries and service issues.
Financial institutions are using machine learning for analyzing mainframe operations to save the time taken to transactions. Banks can also improve the customer relationship using insights offered by AI and data analytics. They use analytics-based customer relationship management software to deliver real-time recommendations to help individual customers.
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Using technology better is the key to success for banking today. And in the next few years, more investment in automation and AI applications will happen. This effort is motivated by cost reduction and improved performability. The coming generations will prefer to interact with technology for their convenience. Currently, applications are more about automating repetitive tasks, but in future AI will become more autonomous for focusing on core issues, for example, the development of a new product based on customer demand.
