The financial services industry is reaching a major milestone in its use of artificial intelligence, as organizations move beyond testing and experimentation to successfully implementing AI to drive business outcomes. The fifth annual report State of AI in Financial Services NVIDIA’s State of AI in Financial Services showcases how financial institutions have consolidated their AI efforts to focus on core applications, signaling a significant increase in AI capability and proficiency.
The report finds that companies that invest in AI are seeing tangible benefits, including increased revenue and cost savings. Nearly 70% of respondents report that AI has generated a revenue increase of 5% or more, with some reporting a revenue increase of 10 to 20%. Additionally, more than 60% of respondents say AI has helped reduce annual costs by 5% or more. Nearly a quarter of respondents plan to use AI to create new business opportunities and revenue streams.
“AI technology has the potential to drastically transform several markets, and the financial sector is no different, as it is one of the sectors that seems to be benefiting the most from this revolution. That is why investment in AI has ceased to be a differentiation option and has become a competitive demand,” says Marcio Aguiar, director of NVIDIA’s Enterprise division for Latin America.
The main use cases of Generative AI, in terms of return on investment (ROI), are trading and portfolio optimization, which account for 25% of responses, followed by customer experience and engagement at 21%. These figures highlight the practical and measurable benefits of AI as it transforms key areas of business and drives financial gains.
The report also found that half of the managers surveyed said they had already implemented their first generative AI service or application, and an additional 28% of them plan to do so in the next six months. Additionally, there was a 50% decline in the number of respondents reporting a lack of budget for AI, suggesting a growing focus on AI development and resource allocation.
The challenges associated with early AI exploration are also decreasing. The survey revealed fewer companies reporting data issues and privacy concerns, as well as reduced concerns about insufficient data for training AI models. These improvements reflect growing knowledge and better data management practices in the industry.
As financial services firms allocate budget and become more savvy in data management, they can better position themselves to leverage AI to improve operational efficiency, security, and innovation across business functions.
Generative AI powers more use cases
After data analytics, generative AI has emerged as the second most widely used AI workload in the financial services industry. The technology’s applications have expanded significantly, from improving customer experience to optimizing trading and portfolio management.
Notably, the use of generative AI for customer experience, especially through chatbots and virtual assistants, has more than doubled, from 25% to 60%. This increase is driven by the increasing availability, cost-efficiency and scalability of generative AI technologies to power more sophisticated and accurate digital assistants that can improve customer interactions.
More than half of finance professionals now use generative AI to increase the speed and accuracy of critical tasks like document processing and reporting.
Financial institutions are also poised to benefit from AI agents – systems that leverage large amounts of data from multiple sources and use sophisticated reasoning to autonomously solve complex, multi-step problems. Banks and asset managers can use AI agent systems to improve risk management, automate compliance processes, optimize investment strategies, and personalize customer service.
Advanced AI drives innovation
Recognizing the transformative potential of AI, companies are taking proactive steps to build AI factories—purpose-built accelerated computing platforms equipped with full-stack AI software—through cloud providers or on-premises. This strategic focus on implementing high-value AI use cases is crucial to improving customer service, increasing revenue, and reducing costs.
By leveraging advanced infrastructure and software, companies can accelerate the development and deployment of AI models and position themselves to harness the power of agency AI.
With industry leaders predicting at least a doubling of ROI on AI investments, financial institutions remain highly motivated to implement their highest-value AI use cases to drive efficiency and innovation.
Download the full report to learn more about how financial services companies are using accelerated computing and AI to transform business services and operations.
