Artificial intelligence (AI) is revolutionizing the banking industry, changing the way businesses operate and providing a range of benefits to customers. The use of AI technology has transformed various aspects of banking, including mobile banking and personalized customer service. Long gone are the days of standing in queues for hours to access banking services. Consumers now have the desire to conveniently reach these services from the comfort of their own homes, leading to a significant increase in demand for mobile banking. A recent study conducted by Insider Intelligence found that more than 45 percent of respondents considered mobile banking as one of the top three features influencing their choice of financial institutions.
Prominent figures in the tech industry, such as Mark Zuckerberg, Elon Musk, and Bill Gates, have been instrumental in driving the adoption of AI. They have utilized AI tools and applications to understand consumer preferences and are now influencing other businesses to embrace AI-based technologies. Consequently, banks are making substantial investments in AI and predictive analytics to make better decisions and provide customized services.
Even banks that were initially hesitant to embrace AI technology have started using AI chatbots to handle customer queries. As Elon Musk predicted, there will be job disruptions as robots become capable of outperforming humans in various tasks.
Risk management is a critical area where AI is making a significant impact. Money laundering has become an emerging issue for banks, as they often unintentionally facilitate such processes. The Financial Action Task Force (FATF) recognizes money laundering as an international problem and emphasizes the importance of global cooperation. A study conducted by the United Nations Office on Drugs and Crime (UNODC) revealed that approximately 3.6 percent of global GDP, equivalent to $1.6 trillion, is being laundered each year. In the United States alone, the annual money laundering value amounts to $300 billion, as reported by Zippia. These figures are alarming for banks, especially as global economies face recessionary pressures reminiscent of those experienced in 2008.
Leading banks are leveraging real-time AI risk management technologies to identify customer behaviors and transaction patterns, enabling them to combat terrorist financing and money laundering effectively. Through continuous monitoring, high-risk accounts can be flagged by comparing a customer’s expected monthly turnover with their actual monthly transactions. This allows banks to implement controls that safeguard against losses and fraud, ultimately enhancing ROI for their consumers.
It is worth noting that implementing AI technologies is just the beginning of the journey. AI processes require optimized frameworks and hardware accelerators to efficiently manage assignments. Additionally, financial institutions need to establish streamlined processes and effectively communicate them with their staff to rapidly achieve their AI goals. As Simon Carter, Head of Deutsche Bank’s Data Innovation Group, emphasizes, “Artificial Intelligence technology invariably needs human beings.”
According to a survey by Deloitte, organizations that can effectively communicate a bold vision with an AI strategy are approximately 1.7 times more likely to achieve high outcomes compared to those that do not. By leveraging big and complex datasets, banks can create risk frameworks that provide precise and timely analysis.
AI also plays a crucial role in understanding consumer behavior. Banks use AI-integrated services and products to cater to customers based on their preferences and search patterns. One of the key advantages of AI in banks is its ability to learn and improve over time. For example, Standard Chartered utilizes machine learning to decode complex data compilations and extract relevant information, aiding in the development of targeted marketing strategies. Vishu Ramachandran, Head of Standard Chartered’s Retail Banking Group, emphasizes the importance of transparency and explainability in AI-based decision-making, highlighting that it not only provides a competitive advantage but also serves the best interests of clients. This approach has helped decrease costs and increase productivity.
However, data breaches remain a concern for banks using AI technology. Given the large number of daily transactions recorded by banks, the continuous collection of data raises significant security issues. A recent data breach at Flagstar Bank, one of the largest banks in the US, put its 1.5 million customers at risk.
While data protection remains a challenge, banks cannot ignore the significance of AI in modern banking. Implementing robust data protection protocols is crucial to counter such threats. Additionally, banking institutions need to lay the groundwork to support AI teams that can deliver efficiency, consumer satisfaction, and improved ROI.
AI presents exciting opportunities, and modern banking must include accessible, secure, and consumer-driven data centers to accelerate data collection and analytics.