Put AI to work across risk, fraud and customer experiences
October 08, 2025
Key takeaways
- AI use in financial services has become a necessity for competitive advantage, with applications spanning fraud prevention, predictive analytics, customer experience enhancements and more.
- High implementation costs, a lack of in-house expertise, difficulty in integrating the technology with existing systems and security concerns are the biggest hurdles for financial firms considering AI and automation.
- Machine learning appears to offer firms the greatest opportunity to transform their operations by enhancing decision-making and efficiency through more accurate credit assessments and predictions.
Let’s face facts: AI is here to stay. As the technology advances, financial services firms from investment banks to fund managers and servicers are finding more ways to harness its power and put money to work. So, what’s stopping your organization from adopting AI or using it to its very best advantage?
Believe the hype
AI is advancing fast. You’ve not only read the headlines, but also experienced it for yourself. Since ChatGPT came to market in late 2022, we’ve all become more accustomed to asking questions of a generative AI tool and receiving an articulately written answer or an immaculately designed image in seconds.
Once, the experience was mind-blowing; now, it’s almost an expectation. As AI continues to evolve, it raises the bar on what technology can achieve and how much more it can automate our domestic and working lives, our daily interactions and communications.
In business in general and financial services in particular, use of AI and machine learning is becoming nonnegotiable: a necessity for competitive advantage. Beyond the media hype, there’s a very real danger that late adopters will be left behind.
According to FIS® research, some regions are waking up to the opportunities faster than others. In our Harmony Gap survey of more than 500 C-suite executives and fintech decision-makers across the U.S., the U.K. and Singapore, we found that the U.K. leads in prioritizing the adoption of generative AI and machine learning. 1
But around the world, use cases for AI in lending, trading, investment management and fund servicing are proliferating and helping organizations make faster and better decisions, reduce risk and improve efficiency. If you’re not using AI to fuel growth and help money work harder, you can bet your competitors are.
Preempt the future
In fast-moving markets, AI plays an increasingly critical role in future-proofing operations and keeping up with new customer and regulatory demands.
AI and machine learning technologies can power predictive analytics to forecast market trends and customer behavior. They can help automate compliance processes so you can adapt to new regulations without breaking a sweat. And with a laser-like ability to spot anomalies in large volumes of data, they can help protect your business from fraud.
With so much money in motion, at rest and at work globally, the stakes are clearly higher for the financial services industry than for other sectors when it comes to fraud management . AI technologies give firms a secret weapon for identifying and preventing fraudulent transactions in real time.
No wonder that 69% of financial services firms, versus just 55% of nonfinancial companies, use AI and machine learning to improve detection of fraud. 1
But malicious activity aside, AI and machine learning are also proving their worth in the sifting, organization and evaluation of data, critical not just for regulatory reporting but also for improving treasury and financial management.
When you’re processing data in multiple disparate systems and different formats, AI can prevent you from drowning in information and help you normalize it, simplify it and cut through to the results you need to see – fast. That’s as vital for cash flow forecasting or managing commercial lending or private credit transactions as it is for compliance.
Plus, in pulling data together so effectively, AI can help deliver a more seamless customer experience with a smoother flow of information and recommendations. For operations that have long been fragmented, the time has come to invest in technology that simplifies the complex and keeps you on top of every new requirement.
Explore the possibilities
Of all the advanced technologies on the market, machine learning seems to have given firms the most opportunities to transform their operations. In the Harmony Gap survey, more than 90% of organizations say they are increasing or maintaining investment in machine learning, versus over 80% in AI over 75% in data analytics. 1
It’s easy to see why. Machine learning offers immediate tangible benefits for decision-making and efficiency, with algorithms that can be trained on historical data and continuously improved to make increasingly accurate predictions and automate more credit assessment and approval processes.
Additionally, firms are using both AI and machine learning to help minimize errors and reworks across their operations. With mountains of data to process, monitor, report and analyze, fintechs and financial services firms are more satisfied than any other sector with AI and machine learning’s abilities in predictive error detection. 1
But the real buzz right now is around generative AI and large language models. These technologies are not just enhancing existing processes; they are fundamentally reinventing how businesses operate.
Think chatbots in your private equity accounting or treasury management software that can instantly answer questions on functionality and need just a few keywords to deliver user-friendly documentation.
Think AI agents that can autonomously perform complex tasks, manage exceptions and make it easier to find, understand, use and integrate data. Or a tool that automatically documents every change you make to your risk models.
All completing actions in a fraction of the time that a human would have traditionally taken, effectively supercharging your workforce. All taking accuracy, productivity and the timely delivery of insight to entirely new heights. All in the name of efficiency, risk reduction and growth.
Defy the risks and seize the opportunities
But, of course, AI brings its own risks to organizations. Why else would you hesitate to use it?
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But there are other, less obvious barriers to adoption. Another 54% of surveyed firms cite a lack of data quality and availability, both critical to the performance of AI models.
With a lack of buy-in from the C-suite and stakeholders affecting 46% of financial services firms and employee resistance a further 43%, implementing AI and automation often also requires radical changes to workflow, processes and culture. There can be fear of job displacement or poor understanding of technology.
More practically, 29% of firms simply don’t have the scalable infrastructure they need to develop and deploy powerful AI models. The same proportion have compliance and ethical concerns, too, as regulators, auditors and analysts continue to grapple with the governance risks and potential biases inherent in AI-generated data. 1
In short, obstacles to adopting AI are significant. But they are far from insurmountable and, as the financial services industry has already shown, the opportunities can quickly outweigh the risks.
The key is to take a strategic approach. Invest in training and development to build in-house expertise. Partner with technology providers to reduce implementation costs. But don’t try to integrate with all your systems, all at once: Do it in carefully planned phases.
Cloud-based solutions can also help mitigate integration challenges and provide scalable platforms, so you can accelerate your deployment of high-performance AI applications and implement models and tools even more cost-effectively.
Above all, get your organization into an AI mindset. As you continue your digital transformation, make sure you develop data and technology frameworks with an eye on how AI could be incorporated to solve your business issues. And start with areas where you’ll make the biggest impact with the least effort.
AI isn’t going anywhere, but it could take your firm to the next level of digital maturity. Let’s seize every chance we can to live, work and grow with it.
1 FIS, The Harmony Gap: Finding the Financial Upside in Uncertainty (with Oxford Economics), May 2025
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