The global Artificial Intelligence (AI) in banking market size was valued at $3.88 billion in 2020, and is projected to reach $64.03 billion by 2030, growing at a compound annual growth rate, CAGR, of 32.6% from 2021 to 2030 according to a report by Research and Markets.
Artificial Intelligence (AI) brings the advantage of digitization to banks and helps them meet the competition posed by FinTech players. For instance, according to joint research conducted by the National Business Research Institute and Narrative Science in 2020, about 32% of banks are already using AI technologies such as predictive analytics, voice recognition, and various others, to have a competitive advantage in the market.
Furthermore, AI also enables banks to manage huge volumes of data at record speed to derive valuable insights and develops a better understanding of customers and their behavior. This enables banks to customize financial products and services by adding personalized features and intuitive interactions to deliver meaningful customer engagement and build strong relationships with their customers.
Improvement in data collection technology among the banks and financial institutions positively impacts the AI in banking market growth. In addition, an increase in investment by banks in AI and a 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 advance machine learning and lack of skilled labor are limiting market growth. On the contrary, the surge in the adoption of modern applications in banks is expected to offer remunerative opportunities for the expansion of AI in the banking market during the forecast period.
By component, the solution segment is expected to garner a significant AI in banking market share during the forecast period owing to managing the massive volume of data being generated for meaningful insights and better-informed decisions. Moreover, companies majorly focus on creating novel opportunities for growth and revenue generation, thereby increasing the preference for AI and advance machine learning algorithms across industries. However, the service segment is expected to witness growth at the highest rate during the forecast period, owing to a surge in demand for cloud-based AI services among end users.
Region wise, the AI in banking market share was dominated by North America in 2020 owing to an increase in demand for modernizing banks and legacy business systems across the region. In addition, the surge in demand for conducting hassle-and risk-free digital transformation among financial institutes is anticipated to boost the growth of the market. However, Asia-Pacific is expected to witness significant growth during the forecast period, owing to a surge in the need to monitor the growing number of financial violations and offences.
The report focuses on growth prospects, restraints, and trends of AI in banking market analysis. The study provides – Porter’s five forces analysis to understand the impact of various factors, such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers, on the AI in banking market share.
The global AI in banking market share is segmented on the basis of component, enterprise size, application, technology and region. Depending on the component, the market is segregated into solution and service.
Depending on enterprise size, it is fragmented into large enterprises and SMEs. Based on application, the market is divided into risk management compliance & security, customer service, back office/operations, financial advisory and others. On the basis of technology, it is categorized into machine learning & deep learning, natural language processing (NLP), computer vision and others. Region wise, the market is studied across North America, Europe, Asia-Pacific, and LAMEA.
COVID-19 impact analysis
The COVID-19 outbreak has had a significant impact on the growth of AI in the banking market, mainly owing to the rise in digitization among both the financial institutes and end users, the demand for advanced AI technology increased to reduce the load on the banking servers and reduce transaction delay with rising digital transaction during the pandemic. For instance, according to the survey of Prudential Regulation Authority (PRA) by Bank of England in August 2020, around 40% of respondents reported an increase in the importance of AI and data science for critical financial operation. Furthermore, around 35% of banks reported that AI and data science had a positive impact on technologies that support remote working among employees and on their overall security provided for AI projects. In addition, the pandemic has accelerated the use of AI-powered tools to manage a sudden increase in customer enquiries. Thus, the number of such developments across the globe are anticipated to provide lucrative opportunities for the expansion of the market.