10 Ways AI Will Impact FinTech [2023]


by Kate Rodriguez, 14 April 2023

The integration of artificial intelligence in financial technology will continue to drive innovation and growth in the financial services industry throughout 2023 and beyond. 

According to Grandview Research, the AI FinTech global market size is expected to grow at a compound annual growth rate of 16.5% through 2030. A market valued at $9.45 billion in 2021, AI-powered solutions will continue revolutionizing all parts of the financial sector, from customer service and security to data and investment management. 

How is AI transforming the future of FinTech? AI is transforming the future of the FinTech industry through automation that improves both business operations and customer services alike. 

With AI-fueled easy access to complex data, financial services companies can make better predictions that impact the financial health of individuals and companies alike. Through the automation of banking services like financial advising and investment management, services accessible only to the rich are now available to the masses. 

In this article, we explore how AI has impacted fintech products and services thus far, plus future implications for further advancements in the financial industry. Keep reading to find 10 applications of AI in the fintech sector and our 2023 predictions.

1. Improve Security

The increase in online banking and digital transactions makes money laundering, cybersecurity, and fraud detection more vital than ever. AI enhances data security measures by protecting sensitive financial information and preventing fraudulent activities. Here’s how:

Real-time fraudulent activity prevention. If you’ve ever received a notification about suspicious activity on your bank account, you’ve witnessed real-time fraudulent activity prevention in action. Thanks to machine learningalgorithms able to detect patterns and anomalies, fraudulent behavior can be identified and prevented.

Biometric authentication. Face and voice recognition are 2 examples of biological characteristics used to verify a customer’s identity. Biometric authentication is harder for hackers to crack than traditional password-based authentication systems.

Enhanced data encryption. AI-powered encryption tools help protect sensitive financial data. Encryption involves converting plain text data into an unreadable format that can only be decrypted with a specific key. 

AI-powered encryption tools can create more complex encryption keys that are harder for hackers to crack. AI also makes it possible to analyze past attacks, identify vulnerabilities, and improve encryption techniques.

2. Manage Regulatory Compliance (RegTech)

Regulatory compliance is a critical concern for all financial services companies, and fintech is no exception. 

The use of AI in fintech to manage regulatory compliance is known as RegTech. RegTech helps companies follow all compliance standards and prepares the associated paperwork promptly and precisely. 

Automated compliance software improves speed and accuracy across monitoring, reporting, and data management.

3. Predict Future User Behavior

AI can be used to analyze a customer’s prior interactions with banking apps, then predict what the customers’ follow-up requests might entail. 

Companies can reduce the number of overall requests by anticipating the user's needs and offering additional information in response to the original request. In this way, customers get their questions answered before ever needing to ask, and the entire system works more effectively and efficiently. 

Another example is the use of explainable AI (XAI) models in grouping risky and non-risky borrowers based on similar financial characteristics. This technology can also be used to predict future user behavior.

4. Create Risk Score Profiles for New Users

AI helps companies make sense of customer data, evaluate risk factors, and turn this data into a risk score profile. This data is then used to draw conclusions like how well a customer can pay or repay a financial debt (like in credit scoring). 

Companies can more easily predict whether a customer can repay a debt and even how to charge clients appropriately based on their risk factors.

5. Provide a Better Customer Service Experience

The availability of digital banking services is a requirement for many when selecting a financial institution to do business with. Offering an improved user experience is a significant contribution for AI-driven aspects of fintech. 

AI-chat bots and personalized banking solutions are other ways AI drives a better customer experience. Here’s how:

AI-chatbots. AI-powered chatbots like ChatGPT have exploded in popularity across industries but are particularly helpful in the financial industry. Wait times for financial serviceproviders can be long, and needs exceed that of a banker’s 9 to 5 schedule. 

Chatbots can be programmed to assist customers with various tasks like opening accounts, checking balances, and making transactions. AI chatbots help companies dramatically improve response times by making customer service available 24/7.

Personalized banking solutions.Machine learningalgorithms can analyze customer data more efficiently than any human being or other computer software. When AI scrutinizes transaction history and spending patterns, it can make personalized banking recommendations and customize financial advice based on a customer’s financial goals. 

In this way, neobanks and robo-advisors make personalized banking accessible to a broader audience by removing limiting factors like high fees and minimum account requirements. 

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6. Reduce Overhead Costs

AI can reduce overhead costs and improve operations across fintech companies by automating manual, repetitive tasks like data entry and document processing. It also reduces customer support costs by answering simple questions for customers. 

AI-powered data management can also help companies identify overspending and inefficient resource allocation.

What are the benefits of using AI in FinTech? The benefits of using AI in FinTech are improved customer service, reduced costs, better data and asset management, and increased business operation efficiency.

Which fintech niches rely heavily on AI?Fintech niches that rely heavily on AI include digital banking, cryptocurrency, RegTech, and financial records management. 

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7. Dramatically Improve Investment Analyses

AI and machine learningalgorithms can improve statistical investment analyses by identifying trends and patterns across complex financial data sets. 

Predicting future outcomes becomes dramatically simpler and more accurate when informed by AI data analysis. AutomatedAI solutions make investing easier, cheaper, and more accessible to everyday customers rather than just the wolfs of Wall Street.

Algorithmic trading is another example: AI systems can analyze market data to improve financial decision-making, reduce risk, and increase returns in trading.  

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8. Improve Data Analytics

In finance, AI improves data analytics by removing human error from data management. It also provides a foolproof way to determine how a decision was made, something you can’t see with a human data analyst. 

AI-powered data can help fintech companies to optimize their products and services, personalize user experiences, and improve customer retention through data-heavy decision-making capabilities.

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9. Robotic Process Automation (RPA)

AI models work to automate repetitive tasks like data transfers, payroll processing, call center operations, credit card applications, and compliance reporting. These are all examples of robotic process automation (RPA)

RPA powered by AI improves accuracy and reduces the risk of errors in routine tasks. FinTech employees can then focus on more complex and high-value tasks like data analysis and strategic planning.

10. Complex Financial Forecasting

Financial forecasters use both quantitative and qualitative data to help companies anticipate future sales or the impact of an investment. 

AI can be used to better understand the quantitative aspects by analyzing past financial data. Forecasters use this data combined with qualitative information to make predictions about how different financial decisions will impact a company’s bottom line. 

AI-driven data in financial forecasting operations facilitates better-informed decisions, improves financial planning, and helps to mitigate risks.

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Looking to the Future

The integration of artificial intelligence (AI) in fintech will continue transforming how financial services are delivered and experienced throughout 2023 and beyond. 

But it’s not just a matter of improved speed and efficiency — AI fintech makes financial services available that wouldn’t have otherwise been accessible to the masses. Companies can draw better conclusions from more accurate data, which leads to better predictions and decision-making. 

From investment analyses to financial forecasting, changes to AI technology will continue to revolutionize the financial services industry. 

Artificial intelligence does not come without risk. Dangers of bias and other harmful effects are important to consider when using AI, particularly from non-representative human data sets. However, the overall impact of AI in fintech is a net positive for both companies and consumers.

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