AI and Machine Learning in Fintech- Benefits and Use Cases

Updated on Feb 6th, 2024


It is safe to say that AI is a digital breakthrough for almost every industry across the globe. AI can do wonders if you want to manage your business strategies smartly or automate the processes. Today, practically every organization uses AI or plans to move to AI to make sense of big data. 

One such industry is fintech. AI and ML in finance have enabled disruption that has made traditional financial institutions obsolete.  

This article explains all the possible ways finance businesses can leverage AI. Scroll down to read further. 

  • AI investments in the field of fintech are bringing a new revolution.  
  • Businesses can now take a futuristic approach to business management using AI-driven data processing and analytics.  
  • AI in fintech is expected to reach $26.67 billion by 2026, at a compound annual growth rate (CAGR) of 23.17% during 2022-26. 
  • The growth of AI in fintech is fueled by advancements in automated trading technologies, smarter fraud prevention, more effective risk management, faster customer support, and tighter ongoing compliance. 

Benefits of AI and Machine Learning in Fintech 


Here is why investing in AI development for your finance business can help you: 

  • Better Operational Efficiency: Automation eliminates the chances of manual error and ensures cost-effective processes. 
  • Robust Fraud Prevention: AI can uncover potential security issues in processes and transactions to prevent fraudulent activities.  
  • Reduced Biases: AI and ML algorithms can help reduce the chances of manual biases in the finance processes.  
  • Better Customer Engagement: AI and ML bring personalization to fintech businesses and encourage customer engagement. 
  • Highly Scalable Operations: Adjust your growing business’s needs with a resilient system. 
  • Make Processes Time-Efficient: By eliminating manual processes and automating the systems, even the time-consuming processes can be efficient. 

Top Use Cases of AI and Machine Learning in Fintech 

Let’s talk about some of the popular use cases of AI and ML in finance.  


1. Data Analytics and Decision-Making

This is one of the most popular use cases of AI in finance. AI aggregates and processes data from a wide range of sources. This data can be analyzed to create detailed reports on financial aspects. For instance, imagine you are a bank and want to boost your service quality by investing in customer-friendly features for your mobile app. You integrate a function for users to get the hang of where their money is going on a weekly/monthly basis. Constant updates in this data will help them understand where they can opt for cost-cutting and ensure better savings for the future.  

Similarly, other businesses may collect their financial information and make data-driven strategic economic changes to support their growth.

Read More: Financial Software Development – A Complete Guide for Businesses

2. Security and Fraud Detection

According to a report, 46% of organizations experienced financial fraud, corruption, or other economic crimes in the last 24 months.  

FinTech companies are more susceptible to financial crimes than any other organization. This is specifically true in the volatile risk market and technology-driven industry. Cybercriminals are coming up with more ways to exploit the financial details of a company, and traditional mitigation methods are lagging in curbing the issues.  

AI and machine learning in finance technics can help these organizations here. They collect real-time data and identify the trends and patterns pertaining to each transaction or financial connection. These technologies allow for real-time data processing and automated anomaly detection, enabling companies to identify potential loopholes. For instance, to overcome credit card fraud, they ensure tracking of each transaction and immediately block suspicious ones. Similarly, traders can eliminate the risk of investment fraud by using these systems to deny the transaction.

3. Asset Management

Investment management is a highly volatile arena. Something that may have been delivering the best outcomes may stop performing over time due to uncertain reasons. To combat this, investors need more robust forecasts and reliable market insights.  

AI-driven asset management is the solution here. They deploy more complex algorithms to help investors make the most of their investments. These systems allow the restructuring of the investment processes and offer advanced asset/ wealth management tools. These solutions collect a wide range of data from the past and, in real-time, analyze trends and patterns.  

This highlights the investment options more likely to deliver results and make smart decisions. They can also leverage forecasting to determine which options are performing better to secure their financial future.  

4. Customer Support

Imagine going to the bank to wait in line for hours to update your passbook. Or standing in a long queue to ask for a query.  

Although it seems like a thing of the past, some people live these scenarios. AI/ML–based customer support systems are here for their rescue. These chatbots are accessible via the bank website or application and instantly help customers find answers to almost everything they need. A striking example is Erica, Bank of America’s chatbot that can help customers extract balance sheets, past transactions, portfolios, savings suggestions, etc.  

Not only customer query management, but these chatbots can also help you take your services to the next level. Algorithms help analyze patterns in a customer’s finance management behavior and suggest services they can benefit from. For instance, if the person invests in an option for three years on a return of 3%, bots can offer them to go for another option that is expected to give them better results within the same duration. 

This brings a high level of personalization to other monotonous interactions with your finance brand and offers an uncompromised quality of customer service.  

5. Automation in Insurance

AI has taken the insurance industry to the next level. Let’s consider an example to understand it better. 

Matt is going home from work one day when his GPS comes up with alternate paths, he can take in order to minimize the risk of accidents. He hops in his car and decides to take one of those. He safely drives to his home and mistakenly bumps into a rock. This damages his car, and soon his car’s smart system gets activated to guide him. He is suggested to click the pictures, and by the time he’s done, the vehicle assesses the damage value and sends the records to the insurance office while filling in the required forms and documents. All Matt has to do now is track the process to know the current status of disbursal.  

While this example significantly explains the impact of AI-driven services on insurance, that’s not the end. Insurance companies today have better access to customer risk and have policies customized for high profits.  

6. Loans Process Automation

Process automation is potentially one of the best advantages of AI in finance. Not only does the right set of technologies help fintech brands gear up to meet the challenges of the volatile market, but it also controls the operational costs and ensures high efficiency. It also helps overcome the challenges of skilled resources and increased personnel costs and improve the quality of overall processes effectively. 

AI-enabled processes easily initiate loan operations while taking care of document processes and financial comparisons and make the process quicker. Customers don’t have to stand in lines or wait for days for loan disbursement. Fintech businesses can also implement biometric systems to record information like credit scores, asset scores, etc. All this makes the process smoother, less time-consuming, and less risky.

7. Personalization

AI and ML in fintech allows businesses to personalize their services with power fintech solutions. Powered by natural language processing, fintech customers can use smart wallets, wealth management systems, banking bots, etc. to analyze their financial status. This allows them to make better decisions and use the fintech services to their full potential. 


Invest in AI-based Fintech Software Development with Industry Experts 

AI is a great way for fintech organizations to take a futuristic business approach. Investing in AI to drive innovation at your institution is a required step for businesses to stay competitive. As an expert in AI development, we help fintech organizations take the right approach to build cutting-edge AI solutions. Our skilled teams understand the current market trends and help you leverage them with the right technology mix. Our business consulting experts help you identify potential business problems and organizational challenges to deliver better results.  

We are proud of the extensive range of services we offer that include: 

  • Readiness assessment 
  • Wide AI development services range under a single roof 
  • Industry-specific AI development services 
  • Decades of experience working with businesses of various scales 
  • Global team presence 
  • CMMI certified experts  

And a lot more. Let’s help you feel the best AI implementation experience. Share your requirements to get started. 

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