Global GenAI in Banking Market to Reach $14bn

As more banks leverage generative AI (GenAI), the global GenAI in banking market is expected to increase from $818 million in 2023 to $14 billion in 2033, according to a Market.US report.

The new report found that North America currently dominates the GenAI in banking and finance market, with a market share of 39.2%. According to the report, this can be attributed to the region’s advanced technological infrastructure and high investment in AI research.

Capital One, JPMorgan Chase and the Royal Bank of Canada all ranked as leaders in AI adoption among the largest banks in the Americas and Europe.

The rise in the use of GenAI can be attributed to boosts in productivity as the top 14 global investment banks could experience productivity increases ranging from 27% to 35% by 2026.

This could potentially translate into an additional $3.5 million in revenue per front-office worker.

The report also provided case studies that demonstrated the value of GenAI for banks. For example, OCBC Bank reported a 50% improvement in task completion speeds among employees following the deployment of GenAI in chatbots.

In addition, the Commonwealth Bank of Australia leverages AI to monitor and block transactions that include abusive language in payment descriptions. Since 2020, around one million transactions have been blocked due to GenAI.

The report also revealed deep learning accounted for 24.6% of GenAI applications in the technology sector due to its proficiency in handling vast amounts of unstructured data, which enables more accurate predictions and smarter decision-making.

According to the report, more banks are using deep learning in areas such as credit scoring, where it is used to analyze consumer behavior to predict loan repayment probabilities. It is also used in fraud detection to identify unusual patterns that may indicate fraudulent activities.

Risks assessment emerges as the most used application of GenAI in banking, with a 27.8% share largely due to the increasing complexity and volume of financial transactions, which necessitate sophisticated tools to manage and mitigate risks effectively.

This type of GenAI can identify patterns and anomalies that may signify risk, enabling banks to take preemptive measures.