AI in Banking Market Expected to Reach $64.03 Billion by 2030

According to a recent report published by Allied Market Research, titled, “AI in Banking Market by Component, Enterprise Size, Application and Technology: Global Opportunity Analysis and Industry Forecast, 2021–2030,” global AI in banking industry size was valued at $3.88 billion in 2020, and is projected to reach $64.03 billion by 2030, growing at a CAGR of 32.6% from 2021 to 2030.

Artificial intelligence in banks is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management. In addition, it provides solutions to process automation to replace routine manual work in most cases. Furthermore, the key factor that drives the market includes improvement in data collection technology among the banks and financial institutions positively impacts the AI in banking market growth. In addition, increase in investment by banks in AI and rise in customer preferences for personalized financial services boost the growth of the market across the globe. However, factors such as higher deployment cost of AI and lack of skilled labor are limiting the growth of the market. On the contrary, surge in adoption of modern applications in banks is expected to offer remunerative opportunities for the expansion of the market during the forecast period.

Region wise, the AI in banking market share was dominated by North America in 2020, and is expected to retain its position during the forecast period. This is attributed to number of factors such as penetration of new industries and improvement in economy. In addition, presence of growing number of cloud AI in banking solution vendors across the U.S. and Canada is expected to provide lucrative opportunities for the AI in banking market. However, Asia-Pacific is expected to witness significant growth during the forecast period, owing to wide presence of small-and medium-scale enterprises, which are turning toward hosted AI in banking solutions to efficiently manage their business processes, particularly in developing countries such as China, India, and Singapore.

The outbreak of COVID-19 is anticipated to have a positive impact on growth of AI in banking market. This is attributed to rise in demand for anti-money laundering (AML), fraud detection solutions, and various other solutions during the pandemic situation. Moreover, with rise in digitization among both the financial institutes and end users, the demand for AI technology increased to reduce the load on the banking servers and reduce transaction delay with rising digital transaction during the pandemic. In addition, this was due to surge in need for analyzing large data sets of genuine claims and to reduce risks and costs related to frauds and achieve superior results. For instance, according to survey of Prudential Regulation Authority (PRA) by Bank of England in August 2020, 16% of banks reported an increase in funding for advanced technologies such as AI and ML to increase efficiency and improve digital customer channels, as they manage the cost and revenue impact of COVID-19. Furthermore, with the rapid spread of COVID-19, majority of people faced sudden surges in demand for financial resources, owing to sudden increase in panic among public, which, in turn, increased the number of transactions performed at a time. Furthermore, various financial institutes are collaborating with Fintech institutes to improve the AI capabilities.

Key Findings Of The Study

• By component, the solution segment accounted for the largest AI in banking market share in 2020.
• Region wise, North America generated highest revenue in 2020.

The key players profiled in the AI in banking market analysis are Amazon Web Services Inc., BigML, Inc, Cisco Systems, Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, International Business Machines Corporation, Microsoft Corporation, RapidMiner, Inc., SAP SE and SAS Institute Inc. These players have adopted various strategies to increase their market penetration and strengthen their position in the AI in banking industry.