When ChatGPT started building buzz in early 2022, generative AI in fintech may have seemed a distant light on the horizon to many in the financial industry.
Now, though, GenAI use cases are a beacon of innovation, one that’s burning too brightly for many fintech leaders who may be:
- Struggling to keep up with the latest advancements in generative AI in fintech
- Not sure how they can work AI use cases into their businesses
- Uncertain they can turn GenAI into a competitive advantage.
However, those who can integrate this type of artificial intelligence into their operations can start to reap the rewards of its numerous powerful features.
This article explores the seven top use cases of generative AI in the fintech market and how they’re changing the financial sector as we know it.
Why Generative AI is important for fintechs right now
Described as the biggest tech revolution since the internet (and embraced quicker by the general public, according to Harvard), Generative AI has taken a foothold in almost every industry you can imagine.
In the financial world, large language models are helping fintechs meet various needs including:
- Building customer and competitor understanding via natural language processing that analyzes vast amounts of online content
- Identifying niche opportunities and expanding their products and services
- Streamlining and upgrading their risk management
- Improving content production that results in better fintech lead generation and conversions.
As a result, the demand for generative AI software and services is expected to skyrocket, with a recent report forecasting growth from $1.4 billion in 2024 to $16.4 billion by 2033—an almost 12-fold increase.
Source: Market.Us
Companies in the fintech industry that know how to harness the power of AI technology are quickly setting themselves apart from rivals.
Want to see how generative AI expertise can get you better marketing returns? Book a no-cost consultation with the Mint Position team and we’ll show how you can find your target customers and increase sales.
Reshaping finance: Top 7 generative AI use cases in fintech right now
Generative AI in fintech is coming to the fore via a wealth of real-world use cases that go beyond just market trends.
Read on to discover seven applications of generative AI that experts believe will make a positive impact on businesses in the world of financial technology.
1. GenAI-produced customer (and employee) videos for better engagement
Financial products are notoriously difficult for customers to understand, in both the B2B and B2C sectors, where the target audience is often less familiar with how to apply the new technology that defines fintech.
Generative AI is helping fintech companies deal with this barrier in novel ways. Sebastian J. Burtone, Co-Founder/COO of B Squared Partners, a leading financial services provider, is seeing this first-hand.
“You can now create different modes of communication with GenAI tools, especially video to help in communicating with clients,” he says.
AI-generated video tutorials, for example, help demystify complex financial concepts for customers, breaking them down into bite-sized, visually appealing segments.
New tools like Synthesia AI make this very simple: all the user needs to do is enter a script, choose an avatar to deliver it, and the platform will create a fully formed video ready to share with the customer base.
Colyssan, a workplace training platform has extended this idea to employees, creating workplace learning videos featuring virtual avatars.
Recently raising $22 million to expand its operations, it makes training more interactive and enjoyable, a welcome boon to companies after a recent poll revealed 75% of workers skip through training videos.
Video messages might even be created for niche customer groups as marketing becomes hyper-personalized. Think product explainers for the elderly or quick tutorials for busy city workers.
Generative AI has also started to automate webinars and live Q&A sessions, where customers can get questions answered live and quickly learn about new products and services.
Tailored content like this scratches a particular itch that fintech customers have: namely, a need for insightful information about the product they’re looking to buy. If a company can provide this to them, and sound like they’re speaking directly to them at the same time, then they’re much more likely to win their custom.
As Burtone emphasizes, “By implementing this type of communication, fintechs and their users can exponentially expand their client base.”
The stats back this up. Customer data from explainer video start-up WyzeOwl found that 89% of people want to see more online videos from brands: generative AI is a way for them to do this quicker and cheaper than ever before.
The high popularity of online videos among customers (2018-2024)
Source: Wyzeowl
2. Chatbots offering more personalized customer service
Generative AI-powered chatbots and virtual assistants are quickly gaining traction in the fintech world because customers value quick and accurate product information above anything else.
Klarna, one of the biggest fintechs on the planet, recently announced that one can do the work of 700 employees. Microsoft has said it plans to use them in its call centers. Forbes has called them a “fintech game-changer” that drives up customer satisfaction.
82% of customers would prefer an immediate chatbot response over waiting 15 minutes for a human agent, according to recent market data from customer service platform Tidio.
Customers prefer chatbots over waiting for human advisors (2024)
Source: Tidio
Business-side, GenAI chatbots help fintechs free up agents to handle more high-priority issues like complex financial consultations and resolving escalated cases.
Yet, fintechs may not be using customer-facing generative AI to its full potential, focusing on cutting costs rather than the technology’s ability to help customers.
Christie H. Kristensen, Growth Advisor & Founder of Growth Advisor & Founder of fintech leader network Pantrium explains how this may be a mistake.
“Until now, the focus has largely been on how GenAI can enhance internal processes and reduce costs, primarily by cutting down task time,” she says. “However, we need to shift our focus towards the customer and explore how GenAI can better serve their needs. We’re beginning to see some interesting use cases in personalized assistance and voice support.”
For example, some fintechs are starting to integrate generative AI-driven voice support to guide customers through complex financial processes, such as loan applications or investment portfolio management, using natural, conversational interactions. This is similar to the Connect and Lex tools that Amazon Web Services has integrated into its systems.
These tools can provide instant, context-aware responses, making customer experiences smoother and more intuitive.
“Once we unlock simpler and more personalized services for our customers through GenAI, we’ll see its true value,” says Kristensen.
3. Smarter investment analysis and predictions
A common problem for investment fintechs is the struggle to break the image of trading as the reserve of suited Wall Street elites.
Generative AI models are helping to reshape this perception by bringing hyper-personalized financial advice to the table.
Chatbots now provide everything from budgeting tips to complex investment strategies. They can even learn from previous interactions, becoming smarter and more helpful over time.
When done well, this leads to better risk assessment, smarter decision-making, and higher returns.
Fintechs can offer advanced portfolio management too, where AI analyzes vast financial data sets, identifies hidden patterns, and predicts market movements with uncanny accuracy.
Some include algorithmic trading models which automate decisions based on data analysis.
This doesn’t mean that human advisors are not needed, however. Instead, AI becomes the ultimate digital assistant that lets human experts focus on the strategic element of asset management, like building a strategy around the client’s goals. AI also frees up time for advisors to build deeper relationships with clients and offer more personalized, empathetic guidance.
Financial institutions like Morgan Stanley and JPMorgan Chase are using GenAI to help assist advisors and select investments.
George Lee, co-head of Goldman’s Office of Applied Innovation stressed the importance of maintaining a “human in the loop” of these tools, especially when it comes to context-sensitive tasks like personalized planning.
4. Better compliance with tax laws and financial regulations
Meeting tough compliance laws is an ongoing headache for fintechs, which must devote time and money to adapt to ever-changing regulations – without affecting customer experience.
A key compliance area that many fintechs must know well is ‘Know Your Customer’ (KYC), yet this often presents problems in safely verifying the identity of new customers, not to mention the hassle of dealing with potentially costly errors.
One recent report by Encompass, a digital identity platform pointed out the deceptively high cost of KYC inefficiencies, with large fintechs paying up to $500 million annually to rectify them.
Jackee Wong, Global Marketing Director of RedotPay, a leading cryptocurrency payment provider, is clear on how much of a headache human errors in regulatory compliance are for fintechs. “Mistakes, such as false positives in KYC and AML processes, can lead to legitimate customers being flagged incorrectly, which damages a firm’s reputation and their customer relationships.”
AI-powered tech is helping to improve these KYC issues. Template Search, for example, is a KYC tool run through ID verification platform Sumsub.
Wong has first-hand experience of just how this tool uses fast and accurate customer screening. “One of the most impactful uses of generative AI in fintech today is in Template Search”, he says. “This tool analyzes images for similar features to help prevent repeated fraudulent activity.”
Template Search checks for the telltale background or layout discrepancies that characterize ID fraud in a matter of seconds. If used successfully on a wider scale, it has the potential to transform KYC processes.
Wong has also witnessed how this tech can handle one of the biggest threats to KYC authenticity in the AI era: the dreaded deepfake, which malicious applicants can use to generate fraudulent videos of themselves.
“A surprising application has been the use of the Liveness Template search, which detects deepfakes and ensures document authenticity”, he continues.
While Template Search deals with images, Liveness Template Search, also a tool provided by Sumsub, digs deep into video submissions to analyze facial characteristics in real time, identifying indicators like masks or synthetic manipulations to verify if a user is physically present.
Such techniques promise to be just the start in this new era of advanced fraud detection. Other behavioral analytics tools, like user interaction profiling and biometric authentication, are also improving rapidly.
“In the coming years, I anticipate a rise in behavioral analytics tools that analyze user behavior during KYC checks, enhancing security”, says Wong.
Sebastian Burtone agrees, pointing out the ability of a Language Learning Model LLM (a subset of Gen AI) to form a fully rounded picture of new clients. “I have been surprised by the ability to use LLM to create client portfolios with little to no human intervention. There is no limit to how impactful generative AI can be for fintechs.”
5. Improving cash flow and cutting costs
Cash flow management is a major obstacle to success for many small fintechs, with high operational costs and unpredictable revenue streams often leading to financial strain.
Nick Chandi, CEO and co-founder of the real-time payments platform Forwardly, knows this well having worked with many fintechs in this situation. “82% of small businesses fail due to cash flow problems”, he says, “but generative AI is opening up incredible possibilities for them”.
Central to this breakthrough is the predictive ability of GenAI that helps SMBs spot problems on the horizon. “AI can analyze spending patterns and predict cash flow issues before they happen, giving business owners time to adjust their budgets,” says Chandi.
This potential explains why so many big names in the industry are now taking action. “Bank of America has invested $3.8 billion in generative AI and has seen impressive results—cutting credit card fraud losses by 45% and saving an estimated $500 million in 2024,” explains Chandi. “They’ve also boosted commercial banking efficiency by 30% with CashPro, alongside a 25% increase in customer acquisition.”
The ForwardAI CEO believes this type of tools will become common place within the industry. “Generative AI fuels cost savings and efficiency gains across fintech. It’s no wonder 91% of financial firms are exploring or already using AI.” he explains.
6. Smarter credit assessments
Traditional credit checks were a source of frustration for customers – but also for lenders.
Robust financial planning and a healthy bank balance may qualify the most likely applicants to repay a loan, but it also shuts out those likely to pay yet stumble on a credit check or tied-up funds.
AI-based credit scoring models help lenders scoop up this business left on the table by digging deeper into a borrower’s credentials.
They don’t just assess their credit score at the exact moment of a pull but use machine learning to assess historical information from many sources so they can make more informed decisions about how much of a potential risk they are.
This might include transaction history, spending patterns, future purchases, and even social media followings.
This brings in more reliable borrowers from the cold, and roots out applicants who may look good on paper, but are, in fact, more likely to default.
Take, for instance, a fintech AI company that develops an AI-driven lending model. This system uses algorithmic data analysis to evaluate an applicant’s creditworthiness quickly and can boast high acceptance rates (and low defaults) thanks to its accuracy. This lender then stands out from rivals who use inflexible scoring models that create friction and fail to mitigate risk.
Duckfund, an earnest money deposit lender that Mint Position has helped achieve number-one ranking for multiple keywords in the U.S., is a prime example. Thanks to their outstanding product and smart content marketing, they quadrupled their organic traffic and achieved over 70 new B2B sales within six months.
7. More personalized content marketing
The rise of OpenAI led many fintechs to fall into the trap of copying and pasting content from a ChatGPT editor into their marketing campaigns.
Big mistake.
Google’s generative AI algorithms quickly caught on to poorly written or obviously artificial content. By March 2024, a ‘helpful content’ update was rooting it out, reducing AI landfill by as much as 40%. Thousands of websites were even de-indexed as the anti-AI move really kicked in.
Out of the chaos emerged a more sensible approach. Generative AI clearly had many powerful uses that helped augment human marketing creativity rather than replace it. “The Universal Intern” was a term coined by tech journalist Kevin Kelly to describe how GenAI could do this. This includes handling subtasks that eat up a content marketer’s time, including:
- Brainstorming ideas based on certain keywords
- Creating imaginative headlines
- Forming article outlines
- Breaking articles down into social media posts (or repurposing).
This strategic use frees marketers to focus on refining content with expert insights and real-life examples that AI cannot replicate. It helps smaller teams produce high-quality content faster.
AI-powered tools, too, like Clearscope and Grammarly help support keyword research, suggest fintech SEO measures to take, and even grade content according to how well it meets ranking criteria (in the case of Clearscope).
Content experts now know that the best fintech content marketing examples achieve high rankings by balancing AI-generated efficiency with a genuine human touch. This way it’s more likely to reach the right people and answer their concerns in an intelligent, human-like manner.
How Mint Position combines Generative AI with expert writing to get fintechs on Google’s first page
When ChatGPT came out many content marketers feared that this huge AI development might steal their jobs.
Mint Position saw it differently.
We knew AI solutions were going to affect the content marketing industry, the opportunity lay in harnessing its power to create the best results possible for fintech companies.
So, how do we do this?
The first step is to use GenAI to analyze the search intent behind top keywords, and then translate it into content that’s SEO-optimized for maximum visibility and engagement.
We then weave expert-led insights, which we get from interviewing industry specialists, into our content, written with journalistic-quality standards.
Google algorithms trained to sniff out AI-pasted content love both the unique perspectives and high-quality output that this approach generates, which is why so many of our customers report higher organic traffic and new conversions within weeks of working with us.
Combining writing expertise with data-driven AI strategies, Mint Position has become a go-to partner in the fintech industry for achieving higher rankings and sustainable growth.
Ready to see how generative AI can help you land more conversions? Get in touch with us and we’ll show you how our unique approach will get you higher organic traffic and more customers.
