AI and fintech: What are the most impactful use cases driving innovation?

If you’ve been following the financial technology ecosystem in recent years, you’ll have noticed that the biggest development in the industry is artificial intelligence (AI). While the likes of ChatGPT have brought the technology to mainstream use only recently, similar tools have already been delivering significant benefits for financial services organisations. 

In this article, I want to give you an overview of some of the key developments, success stories, and potential future use cases of AI in fintech. 

To help to do this, I spoke to the founders and leaders of two AI fintechs in the Tenity ecosystem: Manuel Grenacher from Unique, a startup offering a FinanceGPT, to boost productivity among financial services organisations; and Paul Teather, CEO of Amplyfi, a fintech company that aims to democratise intelligence using AI.

I cover:

• Why are financial services ripe for transformation by AI?
• What are some use cases for AI in fintech?
• How is Unique helping financial services firms with its FinanceGPT AI tool?
• How is Amplyfi democratising intelligence for financial services teams?
• What’s the future of AI in fintech?

Why are financial services ripe for transformation by AI?

If we’re totally honest, the hype around AI technology hasn’t always been deserved. But in the financial services industry, this technology’s potential to bring transformation can’t be exaggerated. 

Why? Here are some reasons why AI can have such an impact. 

1. AI can enable financial services to remove a lot of their manual work

As a financial services organisation, you’re likely under a lot of pressure to minimise operational costs and make your processes more efficient. 

For instance, your teams will likely be dealing with large amounts of customer data and documents. This requires a lot of time and energy—aside from being quite tedious—as people need to trawl through documents for the information they need.

AI has the potential to speed up this entire process, by digesting and summarising all these data points and then sharing the insights that colleagues are looking for. 

“AI—and generative AI in particular—can handle this massive amount of unstructured information,” says Unique’s Manuel.

“Scouring this information—such as reading contracts and comparing them to rules—is something that humans have to do a lot in finance. So, generally, it’s an industry where AI is a good fit.”

In fact, anywhere that there’s a lot of data, AI can step in to make extracting insights easier. Another example is change management, where data analysis needs to inform any transformation, says Paul from Amplyfi.

“Something like 75% of digital transformation change programmes globally fail because they don’t have enough evidence to support the change direction,” he says.

“Instead, you need a data-driven approach that builds and maintains the case for change throughout the journey. We can use AI to digest all the knowledge that’s out there to inform the process of change.”

2. An AI workforce can help scale finance brands when human talent is scarce

One pressure that financial services incumbents and fintech startups both face is the need for growth. Yet talent to support that growth can be scarce, particularly in geographies with ageing populations. 

Instead of working hard to source human talent that’s ever more in demand, financial services teams could instead turn to what Manuel from Unique calls an “AI workforce”.

“Growth is obviously a mandatory step for any financial services institution,” he says.

“But if talent is scarce, that growth can’t be guaranteed. An AI workforce can provide a much more reliable basis for growth, particularly in places like Europe.”

Yet, at the same time, one of the big scare stories around AI is that it may cause many people to lose their jobs. For example, it’s already doing tasks that only humans could do, such as writing content or analysing financial data. And the prospect of an AI-driven workforce implies that it will replace other tasks too. 

However, according to Manuel, AI is likely to only support humans rather than replace them for a long time to come yet. 

“We shouldn’t see AI simply as ‘bad’. Instead, it’s a real opportunity for financial companies. However, in whatever we do, we need to keep an eye on the human element.”

3. In future, AI could make decisions in financial services, not just summarise information

So far, the frontier of AI has been generative AI, with the likes of ChatGPT exciting organisations and users across the world. But both Manuel and Paul see a new AI technology on the horizon: agentic AI.

“Where genAI is based on a linear logic, agentic AI is expected to be able to solve more complex problems based on asynchronous processes. As a result, it will be able to creatively make decisions, not just digest data and support analytics processes,” Paul says. 

In financial services, an industry where trust and compliance are critical considerations, such a technology will need to be handled carefully. With genAI, there are already concerns about hallucinations and inaccurate information. But if agentic AI is to engage in data-driven decision-making, any errors would pose serious problems. 

Yet companies are already using AI models for decisioning and process automation in insurance claims. For instance, in health insurance claims, AI algorithms can extract information from handwritten and digital documents, and machine learning can understand whether a claim is covered. 

Yet there’s potential for much more complex decisions, such as in approving home insurance claims that involve more variables or writing entire reports. As organisations gain more trust in the technology, the potential uses are endless.

What are some use cases for AI in fintech?

The potential uses of AI in fintech are limited only by our imaginations. But how is the technology being used right now?

Here, I want to share some of the most compelling use cases of AI in the fintech sector, including some offered by Unique and Amplyfi:

Searching and serving internal company knowledge. Most financial institutions have thousands of internal documents that outline processes and best practices for everything from onboarding to HR. However, just to understand how their own company runs and find the right way to do things, employees often need to navigate through all this information themselves. 

AI-based tools such as Unique can make sifting through this information easier, as people can ask the tool to extract key insights from their company documentation. 

“Using Unique, a colleague could ask, in natural language, something like ‘how do I onboard a new US client?’ and the AI would serve them the right information,” says Manuel.

“But with genAI they can also ask follow-up questions too, so they can access exactly the information they need.”

Generating reports on investment portfolios, ESG, and other topics. Every quarter, millions of companies draw up reports on their investment performance, whether an ESG report or a fund commentary. Of course, you could use a generic report from the likes of Moody, but you may want to see particular risk factors and market trends that are more aligned with your needs. 

While collecting this information on every investment manually can be time-consuming, AI can make this easy. Whether this information is in your company docs or from across the market, AI tools can find and serve relevant. It’s something that both Unique and Amplyfi can assist with. 

Transcribing and extracting insights from live calls. In financial services, it’s often mandatory to record internal calls. But apart from being a legal requirement, these recordings can contain extremely valuable information—you just have to listen to them (or read a transcript) to find those insights. 

Unique’s AI was designed for precisely this use case. The tool can transcribe the call and pluck out key insights across many recordings at scale. Then it can input the information into your company’s CRM, so that everyone across the business can have that data at their fingertips. 

Digitising contextual information about the industry. It takes a lot of time to keep up to date with developments and trends in your industry—whether that’s regulation, emerging technology, competitor growth, or something else entirely. But overlooking these developments can seriously hold back your business.

AI tools such as Amplyfi can digest huge amounts of datasets and industry information and share insights that are tailored to your specific business needs. Again, you can ask Amplyfi questions in natural language and get a response informed by the world’s intelligence. 

Unique has a handy “Use case factory” page where you can browse all the use cases Unique is currently working on in financial services. Find it here.

How Unique is helping financial services firms with its FinanceGPT AI tool

As you’ve seen already, Unique is a Switzerland-based fintech that’s using AI to automate the manual workloads of financial services organisations. Using generative AI, it provides a tailored solution specifically for the financial sector. 

“During COVID-19, we were using a genAI model to summarise our meetings, reports, and documents,” Manuel says.

“Growing up in Switzerland, financial services were our home turf, so we decided to specialise early on in use cases for the financial industry. Now, four years later, we’re growing abroad in New York, London, Singapore, and more.” 

A company that has benefited from Unique’s services is LGT.

LGT is a private banking and asset management company. With Unique, they launched Lumen, a chat platform for internal use, which connects internal  knowledge sources, including market reports, industry news, and directives. 

One feature they like is “Upload and Ask”, which allows users to securely upload documents and directly inquire about their content. Another is the Investment Research Assistant, which streamlines the process of preparing detailed investment recommendations. 

Read more about the collaboration between Unique and Pictet here.

How Amplyfi is democratising intelligence for financial services teams

Amplyfi uses AI to enable faster access to tailored market insights, to enable financial institutions to make better informed decisions. 

“Amplyfi is a machine that’s designed to organise the world’s unstructured information around the needs of the individual,” Paul says. 

“There’s vast amounts of data in the world, 90% of it has been created in the last 3 years and IDC estimates suggest it’s going to double every 18 months. As an enterprise, you’re making decisions based on a tiny fraction of the available information.”

Amplyfi helps financial services teams by searching that information, machine reading it, then providing structured banks of data that’s relevant to them. The client receives a stream of intelligence that’s sourced, fact-checked, and updated in real time. 

One company that uses Amplyfi is Deloitte. Obviously, quality research is a cornerstone of quality consulting, but Deloitte was struggling to manage the thousands of requests for insights it received each year. They used Amplyfi to:

• Harvest hundreds of thousands of documents
• Generate thousands of unique signals from the content
• Summarise this information into hundreds of automated insights and reports. 

“The integration of Amplyfi’s AI-powered market intelligence platform has supercharged our team’s workstreams, enhancing the quality of our outputs in shorter timeframes,” says Vikas Maturi, Team Lead of Research & Insights at Deloitte. 

Read more about the collaboration between Amplyfi and Deloitte here. 

What’s the future of AI in fintech?

At the end of each conversation, we asked the two founders what they thought we should expect from AI in fintech in the future. 

“I don’t think that AI is going to replace people like bankers or asset managers. People will always want that personal, human touch for certain needs like financial advice,” Manuel says. 

“But AI workforces will continue to grow, to fully complement human teams. So, while you won’t replace your employees with AI, you might hire less in future.”

For Paul, on the other hand, one of the biggest issues that industry needs to resolve is trust. 

“I think we’ll see people gain more trust in AI, as we reduce hallucinations and other errors and ensure that the technology is compliant. But for this, generative models will need to become more evidential and controlled,” he says. 

“After that, the biggest development in the finance industry will be the emergence of agentic AI. This will allow us to benefit from AI systems across asynchronous processes — improving decision support and ultimately moving us closer to AI decisioning.”

Yet there’s one thing that they’re both agreed on: AI is here to stay—and it will be transformative for fintech and financial services companies alike. 

The future of AI is in startups

In this article, I’ve shared some of the most exciting opportunities and applications of AI can offer the fintech industry, right now and into the future. 

While we’re yet to see the full impact of genAI in fintech, another technology is soon to make itself felt: agentic AI. We’re excited to see how its capacity to solve even more complex problems. 

At Tenity, we help financial corporates keep a finger on the pulse of fintech innovation. Want to know more about what’s new in fintech? Reach out to us.