Financial Services Embrace AI: Transformative Impact and Unprecedented Growth Revealed in Latest Industry Report
By Kevin Levitt, Global Industry Business Development for Financial Services at NVIDIA
Since AI took center stage in the technology sector just over a year ago, there’s been abundant speculation about how it will change our lives. Just earlier this month, a Communications and Digital Committee report asserted that AI will produce epoch-defining changes comparable to the invention of the Internet. But in financial services, the impact is already being felt today, spurring a significant shift in how the industry works and how organizations plan for the future.
At NVIDIA, we’ve been monitoring financial services’ use of AI for several years, and the results of our fourth annual State of AI in Financial Services report shed light on the most significant ways the industry is responding to the arrival of generative AI.
AI rollout across core business areas
Overall, the financial services sector is markedly bullish on AI, with more than 80% of respondents reporting that AI is increasing revenue and decreasing annual costs. Digging into the results, it’s clear that leaders are deploying AI across various use cases and are confident in their ability to do so. A significant 75% of those we surveyed consider their AI capabilities as either middle-of-the-pack or industry-leading.
Improving operations is among the most popular areas where financial services firms deploy AI solutions (48% of respondents). Here, AI can be used to automate manual processes, optimize resource allocation, and enhance efficiency. Consumers are already likely to have noticed AI-powered features being rolled out to accomplish this – for example, chatbots to handle customer queries and more targeted and personalized product offers.
Improving risk management and compliance is another key area being improved through AI. Financial services organizations have a significant regulatory burden placed on them by the countries in which they operate, and 45% of respondents reported using AI to help lighten the load when it comes to compliance. For example, anti-money laundering checks can be substantially sped up using AI, because of its ability to process vast amounts of data in record time.
Processing and understanding data is one of the most valuable tasks that financial services firms are leaning on AI to perform, with 69% and 57% reporting using it for data analytics and processing, respectively. Banks and asset managers can identify market trends more quickly through the enhanced speed of processing this data, enabling them to respond to changes in a more agile way. This, in turn, enables firms to identify operational efficiencies (43%) and areas for competitive advantage and differentiation (42%) more effectively than human work alone.
The key challenges that remain
Regulatory issues are one of the most significant roadblocks preventing AI from being deployed even more widely in financial services. Strict new regulations, such as the EU’s AI Act, mean compliance is increasingly challenging, especially when ensuring the organization is aligned with different regulatory environments across borders. 38% of respondents said this was their biggest obstacle to achieving their organization’s AI goals, making it the most significant uncovered by the research.
Lack of available talent is another key challenge (32%). Given the meteoric rise in popularity of AI tools in business, it’s no surprise that demand for AI skills will outstrip supply for some time, as workers with the relevant skill set will quickly get offers from the highest bidder. To address this, financial services firms need to work with the tech sector and education providers to first understand what the skills needs are for the sector. They can then work to implement changes to existing education programs to ensure that those skills are being taught in higher education as well as through lifelong learning programs.
Implementing a successful enterprise AI strategy requires investment in the right AI platform – from the hardware layer to the ML Ops software layer and beyond – but 28% of respondents cited the lack of available budget as another key hindrance to the uptake of AI tools. To realize the benefits of AI in improving business efficiency, organizations must allocate the appropriate budgets.
AI is entering 2024 with a spring in its step
Despite these headwinds, a remarkable 97% of financial services firms surveyed plan to invest more in AI technologies in the near future, focusing on identifying additional use cases, optimizing AI workflows, and increasing infrastructure spending.
Decision-makers are especially cognizant of the need to govern AI’s rollout, with 84% planning to implement a framework for how the technology will be built, trained, and used to adhere to business principles and relevant regulations. This concern was echoed by a speech made by the Financial Conduct Authority’s CIO in October last year, where she highlighted that getting AI integration right will involve more than just good technology implementation – digital infrastructure, resilience and consumer safety all need to be considered.
The importance of this cannot be understated – AI is a tool that is at its best when co-piloted with human supervision. The technology is not yet ready to make significant decisions on its own, and the right governance structures need to be implemented to ensure that mistakes are not introduced.
Fraud detection is another area that banks are increasingly looking to AI to assist with. Recently, the UK’s National Cybersecurity Centre (NCSC) warned that AI will make scam emails increasingly difficult to spot, fuelling a dramatic rise in phishing, from an already high base currently.
The good news is that, when deployed correctly, AI can be used to spot fraud much more effectively than with humans alone. 51% of respondents rated fraud detection as their highest priority cybersecurity challenge they are looking to address with AI. By analyzing large volumes of data at scale, including user behavior, device information, and other contextual data, AI can flag suspicious activity, alerting organizations to take proactive mitigation measures.
2023 has been the year where AI hit the mainstream. In 2022, just 29% of respondents strongly agreed that AI would be important to their company’s future success. By 2023, it has jumped to 51%. This remarkable rise signals that more and more financial services organizations are moving from the early-stage proof of concept stage and starting to see real business impact and momentum.
Looking ahead to 2024, it will be crucial to build comprehensive AI platforms, encompassing data analysis, LLMs, generative AI, data governance, privacy, and regulatory controls to ensure that data scientists and developers can collaborate to introduce new AI-powered products and services to market. Expectations from the technology are higher than they’ve ever been, and budget decision-makers will need to listen carefully to their technical leads, and provide the resources required to develop and implement these tools properly. Those who do this have substantial benefits to gain, including enhanced employee productivity, superior customer experience, and better investment results.