AI in Payment Processing

We are currently living out future predictions, artificial intelligence (AI) is here and all around us. Alexa and Siri are our personal handheld assistants. We have online plug-in modules that help in our learning, efficiency, and accuracy, but AI in payment processing?

We have chatbots for most websites that offer assistance as soon as we enter the page.

With all these AI advancements, we now have access to a surplus of benefits that were previously unavailable. AI has made daily life easier and more convenient.

8 Benefits of AI in Payment Processing

Moreover, the surge of safety measures that escalated during COVID-19’s peak created a significant impact on the global payments industry. This resulted in more digitized payment methods and an online consumer world.

With today’s evolving technological advancements, it is no surprise that AI has made its mark on every industry. This includes the modernization of payment processing.

Algorithms and data analytics have become crucial in industry growth, especially in the financial and payments industry.

However, with any groundbreaking technology, some challenges must be overcome before reaping the benefits.

Artificial Intelligence Defined

Artificial intelligence simulates human intelligence demonstrated by machines or computers. AI has multiple subcategories that make up the technology as a whole creating smart machines. There are 2 types of AI. Cloud-based and edge.

Cloud-based AI may be helpful when data storage is of concern. Remote devices connect to a central cloud that stores the necessary data. 

However, edge AI is stored and processed directly on a device or server close by. Edge AI also offers more security and can serve even when internet capabilities may be lacking.

Computer Vision (CV)

Computer vision is an interdisciplinary technology that uses computer analysis to create a high-level understanding. CV can decipher digital images, numbers, or videos. Computer vision aims to generate an advanced und

Natural Language Processing (NLP)

Natural language processing (NLP) is an interdisciplinary technology in the linguistics subfield. It is designed to process and analyze an understanding of the natural human language.

Machine Learning (ML)

Machine learning (ML) is an interdisciplinary technology that uses historical data to create new algorithms. 

This allows software applications to become more accurate without being programmed explicitly to do so. The altering of output is a “learned” understanding that improves performance.

male agent watching record of crime in a tv screen

AI Benefits in Payment Processing

Fraud Prevention

In a soon-to-be cashless society, digital payments are on the rise. With such high volumes of online payments, there is a greater probability of resulting in fraud from data hackers. However, with AI benefits, fraud is put to a halt and caught before any devastating results occur.

Traditional fraud detection programs consider set variables such as geographic location, transaction amount, merchant type, etc to determine a fraudulent transaction. A transaction would automatically be flagged as fraudulent if the purchase was in a new location, at an unfamiliar merchant, or higher than normal.

However, this conventional approach comes with restrictions. It cannot be used in high-volume situations, and would often provide inaccurate results. With heightened digital transaction volumes, payment gateways can no longer rely on traditional fraud-detection measures. Gateways must look into utilizing AI’s powerful advancements.

Fraud detection is now easier than ever with AI’s advanced technology. One of AI’s top qualities is being able to detect patterns and unusual activity. In recent years, banks have been using AI to help in protecting their consumers.

With AI, data is stored and analyzed, AI can then decipher transactional history and behavioral patterns. If AI were to pick up on any suspicious or unusual activity, the customer or bank is notified. If the activity was, in fact, legitimate the customer can confirm via email, phone, or text with their bank.

AI gateways account for a variety of factors to provide a risk score. If a merchant has a good record, the risk score will be low. If a time zone, IP address, or location is obscure in a digital transaction, there will be a higher risk score.

Once the risk score is determined, alongside a few other factors, a transaction can then be logically determined as legitimate or fraudulent. This advancement allows for easier anomaly determination over a wider range and higher transaction volumes.

If the account information has been compromised, the account holder can immediately deactivate the account or block the transaction. 

This allows for the rapid protection of a consumer’s information. As AI advances, it provides payment processors with the ability to safely process a large number of transactions with more accuracy.

Reducing False Card Declines

Nothing is more frustrating than a card declining at check-out. Especially when it shouldn’t be. When a card is falsely declined, the card holder’s bank may reap a negative impact of declined trust and reputation.

Declines mostly occur due to a set number of reasons. This includes when a card is run above a set threshold, or if the transaction is flagged as fraudulent.

AI payments can use specific algorithms and data points to properly identify transaction outliers rather than a predetermined rule-based system. Saving merchants, customers, and banks time, status, and headaches.

Replacing Traditional Payment Cards And Currency

AI is now utilizing computer vision. You may be most familiar with this in terms of digital wallets. Computer vision is utilized in digital payment methods replacing physical cards with applications like Apple Pay, Google Pay, or Samsung Pay.

Smartphones store account information and purchases can be completed digitally. Computer vision also allows banking accounts to be opened online, rather than needing to step inside the financial organization or bank.

Know Your Customer (KYC) Verification

Computer vision significantly decreases the time needed to process documents for know your customer (KYC) scans for money services businesses. Customers are required to submit less information to proceed. The process is expedited and a decision is made sooner. This allows for a smoother customer experience.

Artificial Inteligence in Reporting

Computer vision combined with ​​natural language processing (NLP) has made reading and understanding documents seamless, without the need for human interference.

CV and NLP have significantly increased efficiency and reduced the need for additional manual work.

Economical and Efficient

With computer vision and natural language processing technology, interactive chatbots and virtual assistants reduce HR and overhead budgets.

These advancements also increase operational hours with no additional cost.

Rather than waiting to reach a live representative, AI now gives consumers access to a chatbot or virtual assistant.

These virtual assistants offer round-the-clock support and mimic natural language and conversation, all through intelligent AI technology.

Two females at a shopping mall holding bags and looking at a phone screen

Predicting Customer Consumption Behavior

It is crucial for banks, fintech companies, and credit card companies to maintain behavioral scoring based on customer transaction histories.

Being able to understand individualized consumer transaction behavior is important for several reasons.

AI data analysis and transaction history storage help cardholders understand their spending behaviors. This can indicate how a cardholder can improve their habits and save more money.

Understanding financial patterns not only helps a customer better understand their finances but also helps provide individualized industry insights.

This information can generate true data-driven and personalized marketing campaigns. With AI incorporation, transaction history and account information is available in an instant.

AI in Payment Processing For Consumer Lending Advancements

US debt has skyrocketed to an all-time high of over $14 trillion. This poses a higher risk to lenders when taking on clients and possibly acquiring a loss of investment. 

As AI advancements continue to evolve in learning consumer patterns and behaviors, financial institutions can take advantage of this technology. Banks can assess credit risk and useful customer financial information in real-time.

AI can increase revenue and profit by predicting consumer outcomes. When a bank has a better understanding of client financial behavior, it can reduce the timeline for credit applications. They can offer higher credit limits to clients that are reliable, or anticipate if a client were to default before it happens.

If a financial institution can gain this type of insight, it can take preventative measures sooner. Consumers can then be sent more reminders when payments are due, or they can be offered new loan terms. This will help customers to make their payments accordingly, and ultimately save the account.

Many financial services merchants are still stuck on using traditional analysis programs. These outdated techniques, although may possess some automation, are limited to a few data points. 

They are not flexible in evolving. These techniques do not carry enough advancement to keep up with understanding the complexity of credit risk factors.

AI capabilities will result in key benefits and profitable longevity. By upgrading to AI, the financial future can become efficient, seamless, and personalized.

AI risk assessment will gain a more holistic financial insight. It helps make the best decision for consumers as it is smarter and faster. This maintains exceptional client experience.

Frustrated cashier at supermarket staring at the payment screen

Artificial Intelligence Obstacles in Payment Processing

There are many benefits to implementing AI in any industry, including payment processing. However, with most advancements, some hurdles must be overcome and challenges that may pose a threat to a seamless experience.

Engineering Expenses

Although AI provides useful insights into real-time consumer behaviors, some institutions are hesitant to adopt the latest technology. Engineering specific AI models can be time-consuming, and the process can be costly. AI engineering also may require a lot of manual tweaking and time before it is finalized. This type of talent and these resources can be hard to find.

Impersonal Experiences

AI increases efficiency and reduces overhead costs. However, replacing customer service representatives with artificial assistance leaves consumers with an impersonal and unmemorable experience.

Consumers generally want to speak to a live representative in real-time when they are dealing with questions or concerns.

Having to go through obstacles to reach a live support person can lead to frustration.

Benefits of AI in Payment Processing Conclusion

As artificial intelligence’s influence in the payment industry becomes more apparent, businesses are benefiting immensely. AI may be costly to develop and may leave some consumers feeling as though they’ve had an impersonal experience. But implementing AI’s innovative technology has proven worthwhile.

The power supplied by AI is unmatchable to traditional business practices, data analysis, and algorithm determinants.

AI has reduced human error, increased efficiency, and accomplished processes that in traditional landscapes would have taken far more time.

Payment gateways use AI to manage the increase of digital transactions. AI also increases security, speed, and the ability to cope with a large volume of transactions in real-time.

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