The financial services sector is reaching an important milestone with the use of artificial intelligence, as organizations go beyond testing and experimentation for a successful implementation of AI, driving business results. The fifth annual reportState of AI in Financial Services(State of AI in Financial Services), carried out by NVIDIA, shows how financial institutions consolidated their AI efforts to focus on essential applications, signaling a significant increase in the capacity and proficiency of AI
The report indicates that companies investing in AI are achieving tangible benefits, including increased revenues and cost savings. Almost 70% of respondents report that AI generated a revenue increase of 5% or more, with some reporting a revenue increase of 10 to 20%. Furthermore, more than 60% of respondents claim that AI helped reduce annual costs by 5% or more. Almost a quarter of respondents plan to use AI to create new business opportunities and revenue streams
"AI technology carries the potential to drastically transform various markets", and with the financial sector it is no different, being one of those who seems to be benefiting the most from this revolution. That is why investment in AI is no longer an option for differentiation, to become a competitive demand, comment Marcio Aguiar, director of the Enterprise division of NVIDIA for Latin America.
The main use cases ofGenerative AI, in terms of return on investment (ROI), are negotiation and portfolio optimization, that account for 25% of the responses, followed by customer experience and engagement at 21%. These numbers highlight the practical and measurable benefits of AI, as she transforms the main business areas and generates financial gains
The report also indicates that half of the interviewed managers stated they have already implemented their first generative AI service or application, and additionally 28% of them still plan to do so in the next six months. Furthermore, there was a 50% decline in the number of respondents who reported a lack of budget for AI, what suggests an increasing dedication to the development of AI and the allocation of resources
The challenges associated with the initial exploration of AI are also decreasing. The research revealed fewer companies reporting data issues and privacy concerns, as well as reducing concerns about insufficient data for training AI models. These improvements reflect the growing knowledge and better data management practices in the sector
As financial services companies allocate budget and become more experienced in data management, they can position themselves better to leverage AI to improve operational efficiency, security and innovation in all business functions
Generative AI powers more use cases
After the data analysis, generative AI has emerged as the second most used AI workload in the financial services sector. The applications of 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, going 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 fromAI 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 the transformative potential of AI, companies are taking proactive measures to build AI factories – accelerated computing platforms specially built and equipped with full-stack AI software – through cloud providers or on-premises. This strategic focus on implementing high-value AI use cases is crucial for improving customer service, increase revenues and reduce 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 agency AI.
With industry leaders expecting at least double the ROI on investments in AI, financial institutions remain highly motivated to implement their highest value AI use cases to drive efficiency and innovation.
Download thefull reportto learn more about how financial services companies are using accelerated computing and AI to transform services and business operations
