Improving Customer Service with AI: Potential and Risks in Banking

Recently, Artificial Intelligence (AI) in the banking industry has become quite a hot topic of conversation. This technology, which is able to increase operational efficiency, provide more personalized services to customers, and improve data security are able to minimize the potential and risks in banking activities. 

Benefits of AI in Banking

It can also be said that AI has made a huge impact in various industries in the world, and banking is no exception.This technology is able to increase efficiency, improve security and provide a better customer experience. 

Minimizing the risk of fraud, analyzing customer needs, determining potential stocks, applying biometrics, and presenting internet banking services are the benefits of AI in the banking industry. The use of chatboxes in internet banking to provide information to customers about banking products can be an example of effective implementation of this technology. 

• Improved Efficiency and Innovation
  AI can improve operational efficiency and innovation in banking services. For example, AI can be used to develop faster and more accurate payment systems, such as QRIS in Indonesia. 
• Risk Management 
  AI can assist in risk management, such as the use of more dynamic stress testing models to identify complex risks. AI can also help in fraud detection and more accurate credit management. 
• Technology Development 
  It is important to note that AI enables the development of more advanced technologies, such as the use of Generative AI (Gen AI) to improve data analysis and decision-making capabilities. Gen AI can also be used to improve communication capabilities with customers through smarter chat boxes. 

Challenges of AI Technology Implementation 

In addition to bringing convenience in banking activities, AI technology also has several challenges to be faced such as data privacy security, customer data access, procurement & development costs, algorithm bias, understanding and communication. Therefore, banks are expected to always pay close attention to the interests of customers or consumers. 

• Security and Privacy Risks
  AI integration in banking increases security and privacy risks. AI can be a target for cybercriminals and mismanagement of data can lead to huge losses. 
• Difficult to Understand 
  AI often has a complex “black-box”, making it difficult to understand the decision-making process. This can interfere with efforts to identify and correct security errors. 
• Dependence on Data 
  It is important to note that AI relies heavily on the quality of data used for model training. This dependency can increase the risk of bias in decision-making and errors in predictions. 

Risk Mitigation for AI Technology in Banking 

Of course, knowing the steps to mitigate the risks and challenges of AI technology in the banking industry can be a way to still be able to carry out banking activities with the help of this latest technology. What is the right mitigation? 

• Good Data Management
  Good data management can be done by investing in quality data collection and preparation to reduce bias in AI models. 
  Human Oversight
  Using human oversight to ensure responsible and reliable use of AI. 
  Sustainability Framework Development
  Develop a sustainability framework covering ethics, security, and transparency to manage AI risks in banking. 

AI technology is indeed on the rise in various industries, and banking is not left out of the benefits it offers. In implementing it in banking activities, AI also needs to be monitored in terms of its potential and risks so that it can become a technology that can help run daily activities in the banking industry.