In today’s fast-changing financial environment, generative AI is gradually becoming an important tool for financial professionals. With the explosive growth of data volumes, traditional manual processing methods can no longer meet the demand for efficiency and accuracy in banking.
Generative AI technology can not only dramatically improve the speed and accuracy of data processing, but also create far-reaching impact in multiple areas such as customer service, risk management, and decision support. This article will explore the development trend and application value of generative AI in the global financial industry through in-depth analysis of a number of key data, and analyze how this technology can lead the banking business into a new era of intelligence.
Global banking industry, estimated spending on generative AI in 2023, and projections for 2024-2027
Spending on the application of generative AI in the global banking industry is expected to increase from $386 million in 2023 to $8.499 billion in 2030, showing a significant growth trend. This growth was mainly reflected in the improvement of the efficiency and quality of service within the bank’s business. As a huge database of banks, traditional manual processing methods are time-consuming and inefficient, but the introduction of AI technology can significantly improve the speed and accuracy of data processing, thereby supporting personalized customer service, automated business processes, and optimization of decision support. The advantage of generative AI technology is that it automatically generates text, performs data analysis, and provides accurate predictions.
Estimated global industry spending on AI systems in 2023
According to forecasts, spending on AI systems in the global financial industry will grow significantly and dominate in 2023. This trend can be attributed in part to the need for large amounts of data and reports to be processed in financial businesses, and the introduction of AI technology can significantly improve the efficiency of data processing and business operations.
It is important to note that although spending in the “other” category is particularly prominent, it is reasonable to have a higher proportion of spending because the category covers many types of businesses. At the same time, it also reflects the active investment and application of AI technology in all walks of life around the world, indicating that the use of AI will be further expanded in more fields in the future.
Estimated global spending by industry in 2023 on AI systems
Banking, retail, and professional services will account for a large share of spending on AI systems, demonstrating the urgent need for these industries to improve business efficiency and enhance competitiveness. Companies in these industries are adopting AI technology to optimize operational processes, enhance data analytics, and provide services closer to customer needs.
For example, Walmart, a leader in the retail industry, has successfully used AI technology to improve inventory management and supply chain processes, reducing operating costs and significantly improving the shopping experience for customers. Walmart uses predictive analytics and automation to more accurately forecast demand and reduce excess inventory and shortages, thereby improving the efficiency of the overall supply chain.
Global AI industry and functional adoption in 2022
In 2022, AI applications in the financial services industry were mainly focused on product and service development, accounting for 31%. This shows that AI technology plays a key role in driving financial innovation, designing personalized financial products and services, and has an important impact on improving customer experience and competitive advantage.
The high-tech/telecom industry accounted for 38% of the risk assessment sector, underscoring the need for risk control in the industry. For example, Citibank has partnered with data science leader Feedzai to use AI technology to detect and prevent fraudulent activity and protect trillions of dollars in daily transactions, greatly improving the security of customer funds.
The potential value of generative AI in the banking industry in 2023
Generative AI creates significant value in banking because of its ability to efficiently process large amounts of data, perform deep analytics, and automate decision-making. Reduce legal risks and financial losses by predicting risks and automating compliance management in the risk and legal areas. In corporate banking, AI improves the accuracy of credit assessment and risk management, shortens approval times, and reduces the risk of loan default. It can also enable AI to improve customer satisfaction and loyalty through personalized services and intelligent customer service, and promote business growth.
Percentage of financial services using AI on a daily basis, by business area, 2022
In 2022, AI technology has been widely used in the global financial services industry, especially in customer experience management, risk management, data analysis, and other fields. AI not only optimizes front-end customer service, but also penetrates into back-end financial reporting, cloud management, and risk control, providing financial institutions with powerful data support and intelligent decision-making capabilities.
For example, United States Express uses generative AI technology to optimize business travel services, enabling intelligent booking, itinerary optimization and real-time support to provide personalized and efficient travel solutions. AI analyzes large amounts of data to accurately predict customer needs and customize services.
European Financial Services Leaders’ Attitudes to Generative Artificial Intelligence (GenAI) in 2023
In Europe’s financial services industry, generative AI is gaining traction among leaders. Many companies are actively exploring how to integrate GenAI into their business operations. Leaders are generally optimistic about the development of the technology and are actively investing resources in the technology, which has great potential to improve customer experience and optimize operational efficiency.
In summary, the application of generative AI is changing the operating model of the financial industry, from risk management to customer experience, all of which reflect its powerful data processing and prediction capabilities.
As technology continues to advance, we can expect AI to be more deeply integrated into the day-to-day operations of financial institutions in the next decade, improving overall business efficiency, optimizing customer experience, and creating more business value. Early adoption and effective use of these technologies by bankers will set them apart from the competition and create new business opportunities.
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