According to an NVIDIA report, 78% of financial services professionals claim their companies use accelerated computing to deliver AI-enabled applications through ML, deep learning or high-performance computing.
NVIDIA’s “State of AI in Financial Services” report is based on responses from over 500 C-suite executives, developers, data scientists, engineers and IT teams working in financial services.
Fraud detection involving payments and transactions was the top AI use case at 31%, followed by conversational AI at 28%, and algorithmic trading at 27%. The number of financial institutions investing in AI have also gone up exponentially. AI for underwriting increased fourfold, from 3% penetration in 2021 to 12% this year. Conversational AI jumped from 8% to 28% year over year.
AI-enabled applications for fraud detection, know your customer (KYC) and anti-money laundering (AML) saw growth of at least 300 percent.
Top current AI use cases in financial services
Almost half of the respondents (47%) said AI enabled more accurate models for applications such as fraud detection, risk calculation and product recommendations. Only 16% of survey respondents agreed their companies are spending the right amount of money on AI, and 37% believe “lack of budget” is the primary challenge in achieving AI goals. Less availability of data scientists, lack of data, and explainability, were the other major challenges listed.
Over half of C-suite respondents said AI is important to their companies’ future success. To the question “How does your company plan to invest in AI technologies in the future?” the top responses included: stepping up hiring of AI experts (43%), identifying additional AI use cases (36%) and engaging third-party partners to accelerate AI adoption (36%). However, only 23 percent believe their companies have the capability and knowledge to move an AI project from research to production.
