The financial services industry is undergoing a significant transformation with the adoption of AI technologies. NVIDIA’s fourth annual State of AI in Financial Services Report provides insights into the current landscape and emerging trends for 2024.
The report reveals that an overwhelming 91% of financial services companies are either assessing AI or already using it in production. These firms are using AI to drive innovation, improve operational efficiency and enhance customer experiences.
Portfolio optimization, fraud detection and risk management remain top AI use cases, while generative AI is quickly gaining popularity with organizations keen to uncover new efficiencies.
Below are the report’s key findings, which show how the financial services industry is evolving as advanced AI becomes more accessible.
Generative AI and Large Language Models Are on the Rise
Reflecting a macro-trend seen across industries, large language models (LLMs) and generative AI have emerged as significant areas of interest for financial services companies. Fifty-five percent of survey respondents reported that they were actively seeking generative AI workflows for their companies.
Organizations are exploring generative AI and LLMs for an array of applications ranging from marketing and sales — ad copy, email copy and content production — to synthetic data generation. Of these use cases, 37% of respondents showed interest in report generation, synthesis and investment research to cut down on repetitive manual work.
Customer experience and engagement was another sought-out use case, with a 34% response rate. This suggests that financial services institutions are exploring chatbots, virtual assistants and recommendation systems to enhance the customer experience.
AI Is Having an Impact Across Departments and Disciplines
With 75% of survey respondents considering their organization’s AI capabilities to be industry leading or middle of the pack, financial services organizations are becoming more confident in their ability to build, deploy and extract value from AI implementations.
The most popular uses for AI were in operations, risk and compliance, and marketing. To improve operational efficiency, financial organizations are using AI to automate manual processes, enhance data analysis and inform investment decisions.
To enhance risk and compliance, they’re deploying AI to analyze vast amounts of data to identify suspicious activities and anomalous transaction patterns. They’re also using AI to analyze customer data to predict preferences and deliver personalized marketing campaigns, educational content and targeted promotions.
Companies are already seeing results. Forty-three percent of financial services professionals indicated that AI had improved their operational efficiency, while 42% felt it had helped their business build a competitive advantage.
A Shift in the Headwinds
In previous years, the number one challenge respondents reported was recruiting AI experts and data scientists. A 30% increase this year in survey participants resoundingly responded that data-related challenges were the primary concern. This includes data privacy challenges, data sovereignty and data scattered around the globe governed by different oversight regulations.
The growing attention to these issues reflects the advancing power and complexity of AI models, which require huge, diverse datasets to train, as well as increasing regulatory scrutiny and emphasis on responsible AI.
Recruiting and retaining AI experts remains a challenge, as do budget concerns. But more than 60% of respondents are still planning to increase investment in computing infrastructure or optimizing AI workflows, underscoring the importance of these tools in quickly building and deploying trustworthy AI to overcome these barriers.
Paving the Way for Future Investments
By and large, the survey results paint a positive picture of AI bringing greater efficiency to operations, personalization to customer engagements, and precision to investment decisions.
Finance professionals agree. Eighty-six percent of respondents reported a positive impact on revenue, while 82% noted a reduction in costs. Fifty-one percent strongly agreed that AI would be important to their company’s future success, a 76% increase from last year.
With this positive outlook, 97% of companies plan to invest more in AI technologies in the near future. Focus areas for future investments include identifying additional AI use cases, optimizing AI workflows and increasing infrastructure spending.
To build and scale impactful AI across the enterprise, financial services organizations need a comprehensive AI platform that empowers data scientists, quants and developers to seamlessly collaborate while minimizing obstacles. To that end, executives are investing more in AI infrastructure and prioritizing high-yield AI use cases to improve employee productivity while delivering superior customer experiences and investment results.
Download the “State of AI in Financial Services: 2024 Trends” report for in-depth results and insights.
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