Revolution Age: How AI Is Set to Break the Barrier and Shape the Future of Digital Payments

With recent breakthroughs in artificial intelligence, digital payments could become the next target of the AI revolution.

Valued at $81 billion, the digital payments market struggles with many challenges. While only 16% of executives feel that their business’ digital transformation is succeeding, small businesses lack access to essential tools like real-time balances and payment alerts for efficient cash flow management.

But how can artificial intelligence be the answer to the industry’s current challenges? AI is a technology that has been in the making for many years now, and it continues to transform and grow with each passing year. With all the recent hype it is receiving, it's high time to consider applying this technology to improve business practices.

In this article, I will explore three crucial use cases for artificial intelligence that can come in handy for digital payment providers.

3 critical ways AI will profoundly assist digital payment players

Enhancing fraud detection

As online transactions increase in volume, so does the risk of fraudulent activities. As of 2022, 90% of financial firms experienced increased digital fraud in the past 12 months. Simultaneously, fraudulent online returns cost retailers $22.8 billion in 2022, with fraud accounting for an estimated 10.7% of all returns in the US.

To tackle this challenge, AI-based algorithms, and machine learning (ML) models can be trained with large digital transactions and payment data to distinguish legitimate transactions from fraudulent ones based on several factors.

For instance, using AI-based fraud detection algorithms in the e-commerce sector allows for monitoring of large transactions and checking them for signs of suspicious activities. This is done as a defensive measure against hackers who can potentially gain access to other people’s accounts. ML algorithms can check new transactions against previously recorded customer behavior data, detect potentially suspicious behavior, and send alerts to the individuals in question.

If someone tries to exploit vulnerabilities in the payment process, such as making unauthorized transactions by using a stolen credit card or taking over a user account, an AI can analyze IP addresses, device fingerprints, historical user behavior, and other data points. This information is then used to identify suspicious patterns in real-time, reducing the likelihood of fraudulent operations succeeding.

Like this, AI implementation can help the payment industry in processing transactions with lower risks.

Improving customer experience

AI solutions are incredible tools to facilitate your customers' journey with a financial service. A study found that using chatbots, an AI computer program that stimulates online chat, in banking will help save about $7.3 billion in operational costs globally by 2023.

In fact, a significant number of financial institutions and digital payment providers are already using chatbots to respond to simple queries or requests from their customers. Beyond that, technological advancements in the AI sector have also given birth to virtual assistants that can vastly improve customer experience by offering personalized advice and recommendations.

In the banking sector, for example, such programs can utilize machine learning to study the actions performed by clients on their respective platforms. These assistants would then point clients towards making use of platform services that are suitable for each client’s specific situation, such as loan applications, credit score checks, and more.

Examples of such virtual AI assistants include Bank of America’s Erica, Douugh’s Sophie, and others, all sharing features meant to improve client experience and assist in maintaining their financial health. Powered by AI and ML algorithms, these assistants can offer suggestions on customers’ spending choices based on the previous history of their transactions. They can also run an analysis of someone’s financial position with the bank and guide them toward services that could be beneficial to those people.

Increasing ability to make accurate real-time decisions

Most digital payments involve real-time data processing, meaning that human decision-makers must keep up with this speed. However, such a fast-paced environment is prone to mistakes. According to a report by the World Economic Forum, 95% of cybersecurity incidents occur in most organizations due to human errors that can easily cause significant financial and even data losses. This is a problem AI can help address.

Artificial intelligence can build data collection models to make accurate predictions and categorizations over provided information. In the case of banks, these prediction models can be used to qualify customers for credit services. An AI can conduct real-time data extraction from various sources, including utility invoices, tax returns, bank statements, etc. By doing so, it can quickly assess a customer’s income levels and their ability to make regular loan payments. From there, appropriate loan limits and pricing can be determined.

And as the decision-making process is automated from start to end and requires no human input, the task can be accomplished almost instantaneously. This reduces the risk of mistakes made on the bank’s side due to the human factor, while customers don’t have to wait for prolonged periods of time to receive credit approval.

AI solutions to grow your business

AI is becoming a reality in our everyday lives. It goes without saying that businesses need to test and adopt these advanced solutions to stand out from the competitors and ensure growth by offering outstanding services.

And the digital payments space is one industry set to experience massive growth stimulated by AI- and ML-based tools and algorithms in the next few years. As I see it, AI solutions can enhance operational efficiency and effectiveness by monitoring payment transactions, enhancing fraud detection, and making accurate real-time decisions while avoiding human errors. They also have great potential to improve customer experience and accessibility.