By John Harding, Regional Director, UK & Ireland, NVIDIA

While stories about the seismic shift toward digital banking in the post-COVID era abound, another technology revolution is taking place in leading banks and fintechs: the era of AI-powered banking. Banks have realized the competitive advantage AI brings to financial services and are poised to capitalize on it as they integrate it into an enterprise-wide strategy.  According to NVIDIA’s recently released “AI in Financial Services” survey report, 83% of global financial services professionals agreed with the statement that “AI is important to my company’s future success.” 

Furthermore, the impact of AI on financial services firms across sectors from retail banking to fintech is real and measurable. Survey respondents identified four key areas where AI is impacting their company today: yielding more accurate models, creating a competitive advantage, developing new products and improving operational efficiencies. Banks can measure these impacts, build business cases around them, and utilize those insights to secure increased investment – whether it’s human or technology capital – to drive further benefits from AI.

Driving cost savings through AI

Financial institutions can reap the benefits of cost savings from AI. Asset managers, banks, and insurers are able to create efficiencies in daily operations using technologies such as conversational AI, robotic process automation, optical character recognition, and other machine learning and deep learning applications.

These AI services save time and reduce expenditures by automating insurance claims processing, augmenting call center agents via automated speech recognition for call transcription, and carrying out other manually intensive services. And those mean benefits for customers as well. Customers have come to expect a great quality service experience that’s both fast and personalized. Infrastructure investments and optimizations are key here to anticipate growing demand.

Roadblocks to Achieving AI Goals

While the benefits of leveraging AI in financial services are unmistakable, the journey from research to enterprise-scale production for AI models within banks, insurers and asset managers is marked with potential pitfalls and challenges. According to the survey, over one-third of respondents (34%) say that AI will increase their company’s revenue by 20 percent or more. So, what is holding banks and other financial institutions back from achieving their AI objectives? The biggest challenges to achieving AI goals are too few data scientists (38 percent), insufficient technology infrastructure (35 percent) and a lack of data (35 percent).

Finding and retaining top talent is a challenge for any part of an organization and that’s certainly the case in AI. However, the C-suite can overcome these by infusing AI expertise across the organization. 60 percent of C-level executives responded that their largest focus moving forward is identifying additional AI use cases. One in two respondents from the C-suite noted that their company also plans to hire more AI experts — addressing the gap of too few data scientists.

Putting it Together

As the competition for customers and their loyalty becomes fiercer, the advantages of AI will become undeniable for banks, insurers, and asset managers. Not only do they see the potential in AI, but they are also willing to invest more to deliver on its promise. That potential is actively being realized by companies who see AI generating competitive advantage, creating new products, adding significant revenues to the top line, and reducing costs to grow the bottom line.

The challenge before C-suite and IT leadership will be unifying and creating enterprise-level AI platforms to scale and deliver productivity and return on investments to support the growing AI professionals across their companies. As a starting place, financial institutions need to proactively elevate AI as a strategic imperative to the firm that needs to ultimately become a core competency. Rather than relegate AI to the “research lab,” the banks that are creating meaningful impact from AI are developing strategic plans, resourcing the teams appropriately and establishing an AI infrastructure platform upon which the bank can productively scale dozens if not hundreds of AI applications and see a significant return on investment.

The “State of AI in Financial Services” survey consisted of questions covering a range of AI topics, such as deployment models, infrastructure spending, top use cases and biggest challenges. Respondents included C-suite leaders, managers, developers and IT architects from fintechs, investment firms and retail banks.