Role of AI In Fintech: Its Use Cases, Benefits And Challenges

“AI in fintech is expected to go from 44.08 billion USD(2024) to 50 billion USD in 2029, with an expected growth rate of about 2.91%” (Statista 2024) 

Suppose you enter a bank, and a robot assists you with all your finances-related doubts and issues. Or the robot tells you the best investment plan based on your activities. Fascinating, isn’t it? That’s precisely what AI in fintech can turn into a reality.

Digital transformation in the financial sector paved the way for “Fintech”—digital solutions designed specifically to optimize financial or banking services. Combining that with the current revolutionary technology, Artificial Intelligence, the fintech solutions witness another massive upgrade. 

Machines weren’t just doing mechanical work anymore; they could interact with customers via chatbot or provide a proper analysis report for any timeline you wish to know. The transformation has reached the NLP stage with the introduction of generative AI, where bots can talk to customers in a human-like manner. 

According to the Globenewswire, the generative AI in fintech market is expected to reach USD 19,963 million by 2032, making it one of the prominent transformational assets in the coming future. 

However, many are still contemplating the integration of AI in fintech, let alone the talk of generative AI in fintech. The blog delves into artificial intelligence, its benefits, use cases in the business, and why investing in AI/ML development services can be advantageous for your financial institution.  

How Is AI Used In Fintech

Managing complicated, high-volume data by humans alone isn’t possible. Manual collection, storage, and organization of data are bound to be full of errors here and there. But these errors can be completely eliminated with AI solutions designed for fintech. 

AI provides financial institutions with the agility demanded by the current ever-evolving landscape. By integrating AI in fintech, optimizing the workflow to ensure relevancy and accuracy is possible. 

While the first thing that comes to mind with AI is definitely convenience, it offers a lot more than just making life easy. Many financial institutions use AI to automate repetitive tasks, which reduces the cost and time invested and simultaneously improves the workflow. 

These AI tools, when combined with data analytics, can easily provide useful insights in a well-organized manner. This makes it easier for service providers to customize offers and suggestions in accordance with users’ spending/investing financial habits. 

Artificial intelligence in fintech also makes the system highly secure, whether it’s due to improved monitoring or fraud detection. It can also make the integrated or yet-to-be-integrated digital products highly secure. 

Why Should One Integrate AI in Fintech? 

AI brings a lot of value to the financial services business. From automation to efficient services and better internal management to improved accuracy. In one sentence, AI can transform every aspect of financial services. 

An avid card user would know about or have at least heard about credit scores. They are good metrics for judging financial habits (for themselves) and reliability (for service providers). Financial institutions leverage AI’s intelligent data analytics to design the credit score based on the user’s income, spending habits, credit history, etc. 

AI also tracks user patterns. It tracks user data, habits, and interactions with various websites, platforms, etc., to understand their interests and suggest relevant offers. For the current fast-paced generation, relevant ads significantly increase conversion chances. 

For example, someone who likes to travel would prefer a bank that generally has offers on tickets and hotel bookings. Doing so is possible with AI and is needed today to avoid getting lost in the endless emails that flood people’s inboxes daily. 

Another benefit of AI for fintech is its cost and time effectiveness. This can be seen in two ways: one is using AI to complete time-consuming tasks in a few minutes, and another facet of this same point is allowing your employees to selectively research based on the data collected. 

Lastly, it improves convenience and security. With AI, the solutions designed would be highly secure because of the latest technology it is built on. Convenience in the form of automation, personalized suggestions, and a lot more is possible with AI.  

We created a finance management system to help users manage their savings. Have a look at that here. If you are interested in cryptocurrency, then this case study on a highly secure crypto trading platform might intrigue you. 

Top 05 Use Cases Of AI In Fintech

The examples of how fintech AI is transforming the financial industry are far too many, but here we have picked up some of the prominent ones to discuss. These use cases show that Artificial Intelligence in fintech is not exactly a new concept. Rather, the transformation has been happening for quite some time. 

Some of the cases where AI and fintech work really well are: 

5 Ways AI Can Optimize The Fintech Industry

• Fraud Detection System 
• Market Trends Predictions 
• Personalization 
• Algorithmic Trading 
• Digital Banking 

Fraud Detection System 

There are many uses of AI in fintech, but the most crucial one is preventing fraud. AI tools powered by Machine Learning and NLP can understand a large volume of data and analyze it to identify user patterns. Doing so allows the system to recognize suspicious activities that suddenly go off the usual route. 

And while a lot of financial institutions do not disclose their financial records or data, they can still announce about integrating AI in fintech. Upgrading with the latest technology as and when needed helps improve operational efficiency and customer trust in your financial institution. 

Predicting Market Trends 

AI’s predictive analysis is really helpful when it comes to understanding market trends. The AI tool can process huge datasets and make predictions about the market or a company’s standing in the market based on past data, performance, and more.

Analyzing market trends, such as demands, conditions, stock market behavior, etc., can help both users and financial institutions understand the shift and plan their marketing and investment strategies accordingly. 

Personalized Assistance

We believe that the biggest advantage of AI for fintech has been improved customer services. Thanks to advanced algorithms and AI-powered chatbots, not only are customers’ queries resolved faster, but they also get personalized recommendations based on their interests. 

Employees can also bid goodbye to the countless back-and-forth calls with customers. With AI-based data generation, the strategy can be tailored to their preferences. This frees the employees to focus on things other than customer service. 

Algorithmic Trading 

Fintech AI has found its use in the trading and investment aspect as well. Using the algorithm to analyze the massive datasets and identify key market trend indicators to design the most impactful investment strategy. 

With AI, one can get accurate data devoid of any human biases. The objective data and faster results make AI an excellent addition to the trading market. Additionally, it can evaluate the user’s goals, reduce risks, and maintain transparency to maximize returns. 

Digital Banking

Everything is going digital, including banking. Today, there are online apps for every bank that allows clients to access services even outside the official hours. There’s no need to go to a bank branch for everything; a lot of services are covered by these apps. 

Powered by AI, these are loaded with features like chatbot, custom notifications, smooth transactions from a secure source, etc. Not only do these AI solutions reduce efforts and time, the automated processes also significantly reduce operational costs. 

Examples Of AI In Fintech Market

Upstart

Upstart is a unique business model that provides remarkable insights into a borrower’s credibility based on their education, work status, background, and more. Since the AI model analyses more than a person’s credit history to define the credit score, it makes the result more accurate and reliable. 

Vectra AI

Vectra AI is a cybersecurity company that uses AI to automate threat detection for faster response to security breaches. It uses machine learning to detect the minute changes in user behavior or traffic and point out anomalies. Thus, it enhances fintech using AI and ML, making it more secure. 

Kasisto

Kasisto designed a conversational AI solution for financial service providers named KAI. It targets the customer service for these institutions. The fintech AI solution reduces human contact through self-service and solutions. It allows them to make contactless payments, access account information and all without connecting with a human agent. 

Additional Read – Digital Transformation In Banking 

Challenges Involved In Implementing AI In Fintech

There are many advantages to integrating Artificial Intelligence in fintech. It can offer agility and efficiency like no other technology, but implementing that, too, comes with numerous challenges. 

AI development services are complicated and require a thorough knowledge of the fintech AI on the service provider’s end to ensure that the exact solution is implemented. Not all challenges can be tackled without a one-on-one consultation. 

But a few generalized ones can be resolved here. Some of the commonly occurring challenges are: 

Key Challenges In Implementing AI In Fintech

• Flawed Machine Logic 
• Data Security & Privacy 
• Complex Interface
• Regulatory Compliance 

Flawed Machine Logic 

AI is praised for its objective decisions and solutions; however, to achieve that, it needs to be trained properly on completely unbiased reports or data. This can influence the user’s perspective on how the institution itself operates, especially if the bot is facing the customers directly. 

This poses the biggest challenge, as any error in this step can significantly impact a company’s reputation. A few practices, such as data standardization, testing the solution, and recording the feedback before launching the final product, can be implemented to ensure proper AI training. 

Data Security & Privacy 

Since the advent of digital integration in management, one concern that has persisted is data security and privacy. With the introduction of AI for fintech, this concern has only grown. 

Fintech AI solutions process and store a massive amount of data, including clients’ personal details, ensuring security and privacy is essential. Some of the best practices to make the system secure include two-factor authentication, notifications about all the actions, biometrics, etc. 

Complex Interface

When investing in digital solutions, especially highly expensive AI solutions, one is bound to go overboard. Adding too much in one space can increase user complexity, which would reduce their retention. If the user finds it difficult to navigate, they may engage just enough or don’t use the app at all. 

Knowing where to draw the line is important when designing an app that has all the required features and yet is user-friendly. An easy-to-use interface, straightforward design, or custom notifications are some of the many ways this can be made possible. Connecting with a fintech software development company and letting the experts handle everything would be much easier. 

Regulatory Compliance 

Government rules and regulations tend to increase with every digital advancement to safeguard sensitive information from hackers and possible threats. This is especially the case for the fintech industry. It requires transparency and accountability by virtue of being a finance-related service. 

Complying with the rules isn’t just a requirement but more of a way for clients to be able to put their trust in the institution. To do this one right, consult a legal advisor for proper guidance and stay in touch with them regularly to accommodate any updates/changes. 

Integrate AI In Fintech Securely With OpenXcell

Integrating Artificial Intelligence in fintech can definitely elevate financial services. However, to utilize its full potential, it requires thoughtful consideration, correct implementation, and continual improvement. While these may seem like crucial roadblocks, the right consultation can easily curb all of them. 

Setting the right synergy between AI and fintech involves a lot, from planning to consultation to actualizing the final product. A lot goes into bringing these AI-based solutions to life, and OpenXcell’s team of experts can help you with that. 

Our team dedicates its time to building an advanced solution that can help your financial business grow and scale. We deliver quality products, and our huge clientele proves our words with concrete numbers. What sets us apart is our quality assurance, complete transparency, and client-oriented development. 

OpenXcell’s fintech expertise assures that the deliverables exceed expectations in terms of both the finished products and the services.