7 Ways AI in Fintech Is Transforming the Industry

The disruptive power of fintech to revolutionize traditional banks and shape the future of financial institutions is expanding rapidly due to the latest innovations in Artificial Intelligence (AI). The 7 ways AI in fintech is driving this change include enhancing security, preventing fraud, conducting advanced data analysis, utilizing predictive machine learning, automating processes, and offering financial advice.

What Is Fintech?

Fintech, or ‘financial technology,’ refers to how new technological innovations replace traditional, human-led processes in banks and financial systems. A key aspect of this transformation is AI in fintech, which plays a crucial role in advancing these innovations. Examples of fintech include online banks like Ally, digital payment methods like PayPal, and cryptocurrencies like Bitcoin, powered by blockchain technology.

What Is AI?

AI stands for Artificial Intelligence, and it means the way that computers and other machines are able to ‘think’ intelligently like humans. AI is generally used to solve problems faster and more efficiently than humans can by using more powerful processing units and smart programming.

One way of programming machines to be intelligent is by letting them learn for themselves, either as humans do or with a different learning technique that codes the limits of what the machine can’t do instead of what it must do.

This is known as Machine Learning (ML), a subset of AI. While AI and ML are related, they are not the same; ML is a specific type of AI that is increasingly influencing fintech. The growing popularity of the Deep Learning technique within ML is further driving the impact of AI in fintech.

Watch more: How To Be Successful With Fintech Solutions For Enterprise?

7 Ways AI Is Used in Fintech

“In 2021, we anticipate AI in fintech to advance further, with smarter chatbots and enhanced functionalities—such as switching utility and credit providers—and fraud prevention becoming standard practices. These advancements will lead to more accurate and personalized financial services, enabling individuals to better access personal finance products. Ultimately, this will improve financial well-being and support those who strive to stay on top of their finances during these uncertain times.”

-Lubaina Manji, Senior Programme Manager of Open Up Challenge 2020, Nesta Challenges

1. Identity Confirmation and KYC

AI in fintech plays a crucial role in helping banking apps and other online financial services automatically and securely verify customers’ identities. This process, known as ‘Know Your Customer’ or KYC, often involves asking users to take a selfie and a photo of their ID document. The AI technology Optical Character Recognition (OCR) then scans the photos to ensure they match, eliminating the need for manual verification by a human.

As voice recognition software improves, too, the expectation is that computers will be drafted in to add this extra layer of security to eKYC processes.

Be sure to visit our SmartOSC Fintech website to see all the fintech solutions we’re developing

2. Reading Documents

OCR tech is also increasingly used to enable computers to read contracts and other documents. By scanning the image and converting the text into a format the computer can work with, the machines are able to process thousands of times more documents than a human surveyor or accountant can.

This is then combined with the additional AI technology of Natural Language Processing (NLP), which is designed to teach machines to recognize human speech and writing patterns—a feature many people are familiar with through their smart voice assistants. In the context of AI in fintech, NLP allows computers to detect inconsistencies in labor and service contracts or identify whether a document might be fraudulent, enhancing efforts to prevent fraud.

3. Financial Health Advice

In banking apps like Revolut, AI is used to analyze users’ finances and compare their personal expenditures with their income, savings goals and monthly bills. This is then broken down and presented to the user in a way that’s easy to understand for people who aren’t experts in financial planning.

The fastest-growing fintech app of all time, Cleo, takes AI in fintech a step further by delivering financial insights to users via chat. Cleo taps into the trend of commerce and services being available through chat platforms, similar to how we communicate with friends on WhatsApp and Facebook Messenger. Acting as a digital financial advisor, Cleo’s chatbot is powered by NLP technology, enabling it to interact with users in a friendly, relatable manner about their personal finances, much like human financial advisors did in the past.

Chatbots enhanced with Natural Language Processing, like Cleo, are used as virtual financial advisors

4. Transaction Search and Data Enrichment

Another way AI is being applied to fintech solutions is by improving the search function of bank transactions. While the computer is able to search through millions of transactions using their identifying codes, this has never been easy information for people to access and understand until now.

By converting those strings of codes into clear details of who the transaction was made to, when, how and where the company is located, AI lets you search for a particular transaction as you would search for something on Google. It also helps people get a clearer idea of their spending and reduces the number of calls to customer service hotlines, which in turn saves the company money.

5. Fraud Prevention and AML

While AI in fintech has revolutionized frontend, user-facing applications, its impact on the backend is equally significant. Banks are leveraging AI to prevent fraud and money laundering, with advancements in AI enabling much higher levels of compliance with Anti-Money Laundering (AML) laws. This backend application of AI in fintech is crucial for enhancing security and regulatory adherence in the financial industry.

Criminal organizations have learned to hide the sources of their illegally gained money over many years, but now banks are fighting back thanks to the power of AI to trawl through enormous stores of data, identifying patterns and recognizing suspicious movements.

6. Data Analysis for Predictive Models

One of the most valuable advantages of AI in fintech for marketers, salespeople, and insurance underwriters is the ability to leverage big data and machine learning to create predictive models of customer behavior. Propensity models analyze vast amounts of behavioral data from past consumer actions using cognitive processing to forecast future behavior. This application of AI in fintech enables more informed decision-making in business, helping companies anticipate customer needs and optimize their strategies accordingly.

This kind of work was previously done by human data analysts, but they are obviously not able to process as much data as a computer can. For insurance companies, this technology is used to create more accurate predictions of applicants’ future behavior, and they can adjust their insurance policies and premiums accordingly.

For lenders, ML-powered data analysis is better and faster at predicting and assessing loan risks and in corporate finance it provides an additional tool in risk assessment for mergers and acquisitions. For sales and marketing in the banking sector, these predictions help to create product propensity models for better-targeted campaigns and product development.

7. Process Automation

“Process automation is one of the major drivers of artificial intelligence in financial organizations. However, it is further evolving into cognitive process automation, where AI systems can perform even more complex automation processes.”

-AI in Fintech Market – Growth, Trends, Forecasts (2020 – 2025), Research and Markets

Finally, and perhaps most importantly, AI in fintech can automate repetitive tasks, allowing employees in the financial industry to focus on more productive work. For example, wealth managers are using AI to expedite the creation of status reports for clients, while banks are relying on AI-driven systems to make decisions on mortgage approvals. This automation speeds up the process for both bankers and loan applicants, but it also has the potential downside of removing the element of human empathy and trust from the loan process, if it was ever present in the first place.

IBM has a cloud-based AI tool called Watson, meanwhile, that has been trained to understand complex banking regulations so it can provide financial information to those who need it in a matter of seconds rather than days. AI automation of workflows in the financial sector is complementing the human factor to positively impact the working practices of the business world, and this trend is set to continue in the future.

Read more: Top 10 Fintech Applications You Should Use In

Challenges and Ethical Considerations of AI in Fintech

While AI in fintech offers transformative benefits, it also brings significant challenges and ethical questions that businesses must address to operate responsibly and sustainably.

• Data Privacy Concerns and Regulatory Compliance: Fintech companies handle vast amounts of sensitive customer information, making data protection a top priority. Adhering to data privacy laws like GDPR, CCPA, and Australia’s Privacy Act is crucial. Missteps in how AI models collect, store, or use customer data can lead to regulatory penalties and reputational damage.
• Algorithmic Bias and Fairness Issues in Lending and Credit Scoring: AI algorithms can unintentionally perpetuate bias if they are trained on historical or incomplete data. In areas like credit scoring and loan approvals, biased algorithms may discriminate against certain demographics, leading to fairness concerns and social inequities. Ensuring AI models are built, tested, and monitored with bias mitigation in mind is critical for ethical fintech operations.
• The Need for Explainable AI to Maintain Trust and Transparency: As AI increasingly influences high-stakes financial decisions, customers and regulators demand transparency into how these decisions are made. Explainable AI (XAI) techniques help businesses make AI-driven processes understandable to both users and compliance bodies, building trust and ensuring accountability in financial services.

Addressing these challenges is essential for fintech companies aiming to leverage AI while maintaining customer confidence, regulatory compliance, and ethical leadership in the industry.

SmartOSC: A Proven Digital Partner for Fintech Growth

As the fintech industry rapidly evolves with the integration of AI, data, and cloud-native technologies, businesses need a partner that understands both the innovation and the regulatory rigor behind financial services. SmartOSC is that partner—bringing a proven track record of delivering AI-driven fintech solutions that are scalable, secure, and tailored to customer expectations.

With extensive experience across platform development, data architecture, API integration, and compliance support, SmartOSC helps fintech companies build robust digital ecosystems that support real-time transactions, intelligent automation, and personalized user experiences. Their development approach combines deep technical expertise with financial industry insight to ensure all solutions meet high performance, scalability, and security standards.

SmartOSC also prioritizes regulatory compliance and customer trust, supporting clients with tools and frameworks that align with data privacy laws, Know Your Customer (KYC), and Anti-Money Laundering (AML) requirements. Whether launching a neobank, upgrading a payments platform, or deploying AI for fraud detection, SmartOSC empowers fintech firms to move fast—without compromising on control, compliance, or user experience.

For fintech innovators seeking a long-term digital strategy partner, SmartOSC delivers the technology foundation and strategic guidance needed to succeed in a competitive, AI-driven financial landscape.

Conclusion

AI in fintech is transforming the financial industry by driving smarter decision-making, improving customer experiences, and streamlining operations. As AI continues to reshape the future of financial services, businesses that invest early will gain a strong competitive edge. If you’re ready to explore how AI can accelerate your fintech growth, contact us at SmartOSC to start building intelligent, future-ready solutions.