Fintech + AI: real-examples of how companies are using it

Lucia Sanchez LeonFeb 3, 2025

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Artificial intelligence (AI) in Fintech is more than a buzzword; it’s a tool companies are using to redefine the way financial services operate. But let’s face it: when people hear 'AI in fintech', their eyes might glaze over, expecting the same generic pitch. Not here. In this post, I want to dive into specific Fintech and Payment companies using AI, what they’re using it for, and how these applications are transforming the industry. Let’s get to it!

1. Fraud Detection and Prevention

One of the most prevalent use cases of AI in fintech is fraud detection. With the growth of digital transactions, the need for real-time fraud prevention has intensified. It’s like trying to catch a criminal before they even know they’re committing the crime.

Paypal: PayPal uses AI-powered fraud detection systems to analyze millions of transactions in real time. Their AI models can identify suspicious patterns, flag unusual transactions, and prevent fraud before it happens. Their deep learning models get better with every transaction, which means their fraud-fighting abilities keep leveling up.
Stripe Radar: Similarly, they use machine learning to stay ahead of evolving fraud tactics. Stripe collects vast amounts of data on millions of businesses globally. By analyzing this data, they identify potential fraudulent behavior. Stripe’s AI models adjust dynamically based on evolving fraud tactics, providing businesses with tailored protection without disrupting their payment flows.

2. Personalized Financial Services

Forget generic advice—AI is all about hyper-personalized financial recommendations these days. No more one-size-fits-all. It goes beyond basic recommendation engines and includes individualized financial advice, investment recommendations, and spending analysis.

Betterment: They are like having a financial advisor that never sleeps or takes vacations. In the investment sector, Betterment uses AI to provide automated portfolio management. Their AI system rebalances portfolios and maximizes tax efficiency automatically. It also helps in tax-loss harvesting, maximizing tax efficiency without human intervention.
Cleo: This is an example on the consumer side—an AI-driven financial assistant Cleo uses natural language processing (NLP) to help users track their spending, save money, and stay on top of their financial goals. It not only helps you budget but will also tell you when you’re being too reckless with your spending. It’s tough love, but sometimes we need it, right?

3. Credit Scoring and Lending

Traditional credit scoring models have often been criticized for their lack of inclusivity. AI is rewriting the rules by using more diverse data points, providing financial access to underbanked populations.

Zest AI: They are bringing a fresh perspective to credit scoring by going beyond traditional FICO scores. Instead of relying on narrow data sets, they use thousands of data points to assess creditworthiness, offering more inclusive lending opportunities. Major players like Freddie Mac and Citi are already tapping into it to approve loans for a broader audience.
Upstart: Upstart takes it a step further by evaluating factors like education and job history to approve loans. They claim its AI-driven approach has allowed them to approve 27% more borrowers while cutting down losses by 75%. It’s like getting a second chance when the system would otherwise say "no thanks."

4. Customer Support and Automation

Anyone else slightly terrified when customer support AI gets too good?

Chatbots and AI-driven virtual assistants are widely used to enhance customer service in fintech. They help companies scale customer interactions, reduce response times, and provide accurate information without human intervention.

Klarna: Take Klarna. Their AI-driven chatbot can handle returns, answer your questions, and even suggest products based on user behavior. They are a major player in the buy-now-pay-later (BNPL) space, and use AI to enhance customer support.
Kabbage:They say time is money, and Kabbage is clearly in the business ofsaving both. Instead of relying on manual checks, their AI systems review and approve loan applications based on real-time financial data from bank accounts, reducing approval times from weeks to just minutes.

5. Optimizing Payment Processes

AI it’s also about making payments faster and smoother—because no one likes a declined transaction at checkout. Payment companies are leveraging AI to optimize and secure the payment experience, not just for fraud detection, but also for improving the entire transaction lifecycle.

Mastercard: They use AI in its decision intelligence technology to reduce false declines while improving security. ThisAI model analyzes billions of data points to determine the likelihood of a transaction being fraudulent. It’s like they’ve got eyes everywhere, ensuring more legitimate payments go through without a hitch.
Adyen: Over at Adyen, AI is optimizing payment routing. By using machine learning, their AI automatically chooses the most efficient and cost-effective route for transactions, reducing payment failures and maximizing conversion rates for merchants. It’s like GPS for your money—always finding the best route.

6. Risk Management and Compliance

AI in risk management sounds like the least fun party trick, but it’s a game-changer in Fintech. It’s proving to be an invaluable asset for managing risk and ensuring compliance.

HSBC: HSBC uses AI to improve its anti-money laundering (AML) systems. By deploying AI models that monitor transaction activity, they can identify potential cases of money laundering faster and with more accuracy than traditional methods. Their AI models scan transactions faster than a human could ever dream of, catching suspicious activity before it escalates. (It’s not glamorous work, but it sure is important.)
ING: ING uses AI to predict market risks, making sure they’re always one step ahead. Their AI systems analyze vast amounts of financial data to provide predictive insights into potential market risks, helping them mitigate exposure and optimize investment strategies.

Key takeaways: AI’s tangible impact on Fintech

"The market size of artificial intelligence (AI) in fintech was estimated at 42.83 billion U.S. dollars in 2023, which grew to 44.08 billion U.S. dollars in 2024." — Statista

So, what’s the big picture here? AI isn’t just about flashy algorithms or futuristic buzzwords. It’s about results. Whether it’s keeping your transactions secure, offering personalized services, or optimizing payments, these Fintech and Payment companies are leading the charge, showing us what’s possible when AI is used thoughtfully.

Truth is the companies using AI today are setting the standard for the future of finance. By curating the right tools and technologies, Fintechs and Payment companies are positioning themselves to lead in a rapidly evolving market.

As you can see, there’s no filler here—just real companies doing real things with AI. Which is what we came for. The future of fintech and payments is being built today, one AI-driven innovation at a time—and those who adapt will lead the way.