Whether you agree or not Artificial intelligence is one of the most game-changing factors around several sectors of the economy. Additionally, the contribution of artificial intelligence in banking is quite remarkable around the globe.
The technology of artificial intelligence and machine learning has become a major reason for the development of manufacturing and boosting the economy to a greater extent. Whereas experts say there is a huge potential in the IT tools such as machine learning and artificial intelligence for developing the banking sector to its epitome globally. Even the lowest member of the social pyramid can get the banking services with the inclusion of AI and Hitech software development features. It is due to the inclusion of highly innovative tools such as AI that we can create a society with more equality and prosperity.
According to a reputed report from the economic experts, there will be a market of fintech technologies of about 6.67 billion U.S dollars in 2019. Additionally, experts also predicted that this value will rise and reach up to 22.65 billion U.S dollars by 2025. Therefore we can say that the contribution of artificial intelligence and machine learning is crucial for economic development and offering its services to a wider range of customers.
The impact of artificial intelligence in the banking sector can be understood through the following points :
Table of Contents
Cost of operations
The primary objective of the banks or banking sector is to reduce the cost of banking operations as much as possible. In doing so several steps are taken from time to time by banking and fintech organizations. One of the expenses of the banking sector is the use of paper in banking operations. The use of banking operations doesn’t only create a burden on increasing cost but also use of paper is not environment friendly. Using innovative tech like AI we can keep the majority of human errors very low. Additionally, it also reduces the time-consuming lengthy process in performing banking operations click for more info. With the inclusion of AI and machine learning tools, the banking ecosystem is also getting digital. This means that the conversion of paperwork into digital format. Therefore this digitalization not only reduces the cost of paper but also reduces the time taken to execute an operation in this sector.
Better customer support
In traditional times when most of the work was executed manually then the care for customers was not the key service that is offered by the major banks. The increasing number of customers and services added more burden on the staff with time. And due to which the customers support by the banking system suffered. But it is not the case in current times. Now with the inclusion of revolutionary tech such as artificial intelligence we can experience one of the best customer support by the banks. Chatbots and personal assistants have made it so easy for solutions of any grievances thrown at by the customer. They give replies and add support for the major the most repetitive questions or help asked by the customer. This highly increased the level of customer satisfaction by the banks. Additionally, several other opinions are there for customer support such as email, multiple contact numbers, dedicated social media support team, etc. features available for the customer.
Security
Security is one of eh major pillars of the banking sector that they put the most focus on. Even the eminent institution like the world bank acknowledges the threat of cyber attacks on banks around the world. It is for the cybersecurity world banks has special fund program for funding poor countries that cannot afford cyber security cost. Therefore in the nonending war for fighting cybercrime Artificial intelligence helps by creating several layers around the banking digital ecosystem. Adding multiple security layers with innovative tech checks the cybercriminals to breach the security of the system as well as plunder the money.
Regulatory compliance
We always ignore the number of compliances banking organizations have to follow for getting the working authority. Usually, we underestimated the regulator’s compliance policies that are strictly followed by the banks. With the inclusion of machine learning guidelines, protocols, laws, and regulations are followed correctly. With the utilization of AI and machine learning the human errors and irregularities are detected regularly without failing any regulatory compliance of the banking services.
