The impact of artificial intelligence (AI) and generative artificial intelligence (GenAI) in the fintech and banking sectors can not be undone. Everywhere you look, the technology is being used in some way to help. However, when looking to find out specifically how AI and GenAI were being used, 50 per cent of banks said it was a tool for improving productivity and efficiency while 49 per cent said it could reduce operational IT spend.
The research was published by the global digital business and IT services firm, NTT DATA in its Intelligent banking in the Age of AI report. Overall, over half (58 per cent) of surveyed firms said they were already embracing GenAI – this was an increase from 2023 when only 45 per cent of organisations said the same thing.
All banks and fintechs are gradually adopting AI tech due to its transformative ability to embed intelligence at every layer of the banking ecosystem. It is less a question of if, but when banks embrace this technology.
“Generative AI represents a pivotal moment for the banking industry,” said Robb Rasmussen, head of global marketing and communications, NTT DATA. “While the potential benefits are enormous, the challenges of implementing GenAI are complex and varied, requiring careful navigation and a structured approach. Given the anticipated high spending on GenAI, achieving a return on investment is crucial.
“Many banks will be expecting GenAI to drive long-term savings by automating IT tasks, improving operational efficiency, and creating competitive advantages, but it’s important to note that achieving meaningful ROI requires a clear strategy, tailored implementation, and robust governance at the same time.”
Is GenAI the answer to productivity problems and higher ROI?
ROI has become a top priority for GenAI implementations, yet banking organisations are split in their opinions of which strategies are most important to them. Banks have long struggled with boosting productivity, and GenAI is poised to present a solution to this problem, but only half of banking leaders (50 per cent) see it as a solution to current productivity woes. Cost optimisation is another area where banks are split, with just under half (49 per cent) are looking to reduce IT budgets accordingly.
This disparity is highlighted on a global scale too – for example, almost six in 10 US banks (59 per cent) are keen to reduce IT budgets and almost half (47 per cent) want to cut operations budgets, while only four in 10 banks in Europe (43 per cent) have IT budgets front of mind and just over a third (36 per cent) are concerned with operations costs. Meanwhile, productivity is the most important factor for European banks (46 per cent), yet the US and APAC are placing even more emphasis on productivity themselves in comparison.
Key performance indicators (KPIs) that financial institutions are using or planning to use to evaluate the success of its Generative AI initiatives:
| Europe | US | APAC | LatAm | Japan | |
| Improved productivity/efficiency | 46% | 52% | 58% | 43% | 35% |
| Competitive advantage | 42% | 48% | 57% | 48% | 40% |
| Cutting costs/Reducing IT budget | 43% | 59% | 51% | 44% | 48% |
| Cutting costs/ Reducing operations budget | 36% | 47% | 49% | 36% | 28% |
| Accelerate speed to innovate | 37% | 34% | 50% | 41% | 35% |
| Increased net promoter score | 29% | 25% | 31% | 26% | 40% |
Differing strategies across differing regions
Strategies for realising these benefits of GenAI differ vastly among organisations too. While around half of organisations are focusing on collaboration between humans and AI (51 per cent) or a hybrid approach with existing systems (47 per cent), over a quarter (28 per cent) of banks are hoping to fully automate tasks and remove the need for manual input entirely.
Fully automating tasks is an area which divides opinions worldwide as well, with a quarter of banks in the UK (25 per cent) and Europe (24 per cent) looking to fully automate the process, while almost a third of banks (32 per cent) in the Americas and 35% of Japanese banks are looking to do the same.
Rasmussen concluded: “It is clear that the ability to balance innovation with fiscal responsibility will define success for banks. However, many banks are lacking in maturity when it comes to this technology and are unsure where to start.
“Partnering with systems integrators can be a good starting point, allowing them to access the latest knowledge while ensuring compliance with industry regulations. By working with specialised providers, banks can ensure that GenAI implementations can deliver the desired ROI, while maintaining robust data protection measures and meeting both internal security standards and regulatory requirements.”
