The financial services sector is reaching an important milestone with the use of artificial intelligence, as organizations move beyond testing and experimentation to successful AI implementation, driving business outcomes. The fifth annual report State of AI in Financial Services (State of AI in Financial Services), conducted by NVIDIA, shows how financial institutions have consolidated their AI efforts to focus on core applications, signaling a significant increase in AI capability and proficiency.
The report indicates that companies investing in AI are reaping 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, over 60% of respondents state that 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 various markets, and the financial sector is no exception, being one of the industries that seems to benefit the most from this revolution. That’s why investment in AI has ceased to be a differentiation option and has become a competitive demand,” comments Marcio Aguiar, director of NVIDIA’s Enterprise division for Latin America.
The primary use cases for generative AI, in terms of return on investment (ROI), are trading and portfolio optimization, accounting for 25% of responses, followed by customer experience and engagement at 21%. These numbers highlight the practical and measurable benefits of AI as it transforms key business areas and generates financial gains.
The report also notes that half of the surveyed managers stated they have already implemented their first generative AI service or application, and an additional 28% plan to do so within the next six months. Furthermore, there was a 50% decline in the number of respondents who reported a lack of budget for AI, suggesting growing dedication to AI development and resource allocation.
The challenges associated with early AI exploration are also diminishing. The survey revealed fewer companies reporting data issues and privacy concerns, as well as reduced concern about insufficient data for AI model training. These improvements reflect growing knowledge and better data management practices in the industry.
As financial services companies allocate budgets and become more experienced in data management, they can better position themselves to leverage AI for improving operational efficiency, security, and innovation across all business functions.
Generative AI powers more use cases
After data analysis, generative AI has emerged as the second most used AI workload in the financial services sector. Applications of the technology 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, more than doubled, rising from 25% to 60%. This increase is driven by the growing availability, cost efficiency, and scalability of generative AI technologies to power more sophisticated and accurate digital assistants that can enhance customer interactions.
Now, more than half of financial professionals use generative AI to increase the speed and accuracy of critical tasks, such as document processing and report generation.
Financial institutions are also poised to benefit from AI agents – systems that leverage large amounts of data from various sources and use sophisticated reasoning to autonomously solve complex, multi-step problems. Banks and asset managers can use AI agent systems to enhance risk management, automate compliance processes, optimize investment strategies, and personalize customer service.
Advanced AI drives innovation
Recognizing AI’s transformative potential, companies are taking proactive steps to build AI factories – specially constructed accelerated computing platforms equipped with full-stack AI software – through cloud providers or on-premises. This strategic focus on deploying high-value AI use cases is crucial for improving customer service, increasing revenue, and reducing costs.
By leveraging advanced infrastructure and software, companies can streamline the development and deployment of AI models and position themselves to harness the power of agent AI.
With industry leaders forecasting at least double the 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 services and business operations.
