How AI is transforming fintech: from automation to improved customer experience

Artificial intelligence (AI) continues to be a major area of interest in fintech,  according to Pulse of Fintech H1 '24 . More and more companies are investing in this technology, primarily to improve efficiency and reduce costs. However, despite the growing demand for AI in the banking sector and the financial industry, the implementation of AI still poses challenges, mainly due to the difficulty of finding the right experts.

With 17 years of experience in recruiting the best mid- to C-level IT professionals , we at INDIGO Tech Recruiters know exactly how to find the right team for your business to drive innovation. In this article, we will tell you about the most common use cases for AI in fintech as well as the experts and experience needed to implement AI in your fintech product.

AI in the automation of fintech processes

According to Invesco, an American independent investment management company, ensuring operational efficiency through machine learning automation will soon become the norm in the financial industry. In 2020, Invesco reported that 51% of fintech companies have already implemented AI to optimize processes. How does it work?

Here are some examples of how AI implementation in financial technology can automate transactions:

• Accelerated transaction processing: Using artificial intelligence, financial institutions can speed up transaction processing and verification, which will speed up payment approvals and reduce errors.
• Fraud detection and prevention: AI-powered systems can detect suspicious activity in real-time and flag potentially fraudulent transactions before they cause damage.
• Credit Scoring and Loan Approval: Traditionally, credit risk assessment involves manual verification. However, with the help of artificial intelligence, your system can analyze a wide range of financial data, such as a customer’s social behavior and payment history, to assess creditworthiness faster and more accurately.
• Customer support automation: AI chatbots and virtual assistants can free your team from answering hundreds of routine customer queries. Plus, chatbots learn from interactions to provide more personalized and accurate responses over time.

Many companies are using AI to automate fintech processes today. For example, one of the most well-known online payment systems,  PayPal , uses AI to detect potential fraud. It relies on AI-based filters with machine learning capabilities to assign risk scores to each transaction, increasing the accuracy of fraud detection.

If you’re planning to use AI for financial services, the first step is to assemble the right team. To help, we’ve created a table of the technologies, specialists, and technology stacks you’ll need to automate various processes.

Finding the right fintech talent can be a difficult and time-consuming task on your own. To make the process easier, you can always reach out to INDIGO Tech Recruiters and we will help you find the best talent for any of your projects. Now, let’s move on and explore other applications of AI in fintech.

Data analysis using AI

Fintech relies heavily on big data to deliver personalized services, accurately assess risks, and make better decisions. Additionally, some argue that big data analytics can help create better fintech solutions and predict their impact, according  to research .

What is the role of AI in data analytics? With its ability to quickly analyze massive data sets, this technology allows it to identify patterns that humans would struggle to detect and gain valuable insights. As a result, financial companies can benefit from:

• Accurate predictions: By analyzing historical data, AI can predict future trends and help fintech companies make winning strategic decisions.
• Customer Articles: Artificial intelligence-based analysis of customer behavior, transaction history, and customer feedback allows financial institutions to personalize their offerings and thus increase customer satisfaction.
• Market trend analysis: AI can process large amounts of market performance information in real time, allowing fintech solutions to provide deep insights into market trends and meet growing market needs.
• Risk reduction: AI-powered tools can conduct deep analysis of various financial data and almost instantly detect risks such as fraud, data leaks, and loan defaults.

So, AI is helping fintech take data analytics to the next level, making it faster, more automated, and more accurate. Some financial companies have already seen the benefits of AI-powered data analysis.

A great example of how  Bad Financial , a data analytics platform, is using AI to help financial companies personalize their offerings and create more powerful marketing campaigns. The platform features what it calls an “insight engine” that generates insights from customer data and highlights those that can be quickly and easily acted upon.

What kind of professionals are needed to implement AI-based data analytics in fintech? Here's a quick overview:

INDIGO Tech Recruiters has the experience, resources, and capabilities to find the perfect match for your fintech project. Just contact us and we will find the best specialists for you.

SHImproving customer experience in fintech

This is according to James Sanchez, a leader in customer success at LeanLaw.  AI will be a major driver in improving customer relationships . This is especially true for millennials, Gen Z customers, and Gen Alpha customers, who prefer self-service over traditional channels, so building meaningful relationships with them requires making this option convenient and effective. However, self-service is just one of many ways AI can improve customer interactions. Others include:

• Personalization: It makes customers feel understood and valued. By analyzing individual customer data, preferences, and behaviors, AI allows companies to create personalized financial products and services. For example, AI can suggest lower interest rates on personal loans to trusted customers.
• 24/7 Customer Support: Chatbots and AI-powered virtual assistants can provide assistance anytime, anywhere to help customers quickly resolve issues without having to contact a representative.
• Proactive engagement: AI-powered software can predict customers’ financial patterns based on historical data and help them with everyday money tasks. For example, such tools can send bill payment reminders or suggest investment opportunities based on their personal financial goals.

By improving customer interactions, AI technologies help companies maintain loyalty, which leads to better positioning in the market. For example, in 2018, Bank of America launched  Erica, an AI-powered virtual assistant . Erica responds to customers in less than 44 seconds on average. He tracks their subscriptions, provides insights into their spending behavior, notifies them of important events, and even has a great sense of humor.

However, using AI to improve customer experience in fintech requires a deep understanding of both the technology and the industry. Here is a quick table listing the technologies, specialists, and technology stack that may be required for different use cases:

If you are looking to find AI specialists to improve the customer experience with your fintech product, keep in mind that INDIGO Tech Recruiters has over 300,000 top tech professionals in its talent pool.

Increasing productivity and reducing costs with AI

Integrating AI tools into financial products has a positive impact on your bottom line by increasing efficiency and reducing operational costs. Let’s look at some of the ways AI can do this:

• Automate routine tasks: By automating repetitive tasks like data entry, transaction processing, and customer support, AI reduces the workload on your employees. This means you’ll need fewer staff to do the same work that all your employees did before AI was implemented.
• Better, Faster Decisions: AI’s ability to analyze vast amounts of data beyond human capabilities enables smarter, more informed decisions at every level—from individual loan approvals to market expansion strategies—leading to lower risk and better profitability.
• Cost optimization: AI systems can identify inefficiencies in your core operations and suggest ways to address them, such as better resource or staff allocation. This results in reduced costs for both infrastructure and human resources.

While AI implementation may seem expensive, its long-term implications can make fintech companies much more money. And the following real-world case study is proof of that.

Lemonade , America’s highest-rated insurance company, implemented AI bots into its system, and now half of their claims are paid in seconds without any human intervention. This allows them to keep their rates at $5 per month. In doing so, they have reduced operating costs, but not at the expense of customer experience. In fact, they have achieved both — reduced costs and provided a better customer experience. Notably, thanks to AI, Lemonade reported a 115% increase in revenue in the first quarter of 2023 while operating costs increased by only 4%.

What team and technology do you need to achieve AI productivity and profitability? Here’s an overview:

If you are interested in hiring any of these professionals, contact INDIGO Tech Recruiters and we will find them for you within a few weeks.

Summing up

Data and real-world use cases have shown that using AI for financial services leads to increased team productivity, better data analysis, faster workflows, improved customer engagement, and lower costs. And it’s definitely worth investing in.

However, implementing AI in fintech requires specialized expertise that may not be available in-house or easily found outside your company. That’s why we at INDIGO Tech Recruiters help fintech companies staff their projects with the best talent who have all the necessary skills and knowledge. So, whether you need a few specialists to complement your technical team or assemble an entire new team,  contact us and we will help you with all your talent sourcing queries.