7 Applications of Artificial Intelligence in Digital Payments

Introduction 

Artificial Intelligence (AI) comes across to many as an extremely complex topic. However, understanding the concepts of how AI works, and what it intends to do, is fairly simple. At its core, AI development is about computers and systems, being able to perform tasks, that would usually require the input of human intelligence. One example of this is Google mail, enabling quicker composing of emails by predicting what you are going to say next. Now, let’s dive into what are the applications of Artificial Intelligence in Digital Payments.

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However, the industry that is so far the most invested in AI development is the financial industry, with a particular focus on payments. AI technology is expecting to see exponential growth in the finance industry within the next 10 years, and signs of this are already visible. Being one of the crucial aspects of financial technologies, AI, coupled with ML has several use cases in the finance industry.

Applications of Artificial Intelligence in Digital Payments

1. Artificial Intelligence in Debit Cards

Dough, a FinTech start-up, built an AI engine to help Choice Financial was planning to integrate a new digital bank account and debit cards with Artificial Intelligence in payments.

Instead of launching the product by themselves, they reached an agreement to partner with Dough. The two companies will soon launch a debit card under the Dough brand, with the card having an AI virtual-assistant called Sophie. With the help of Choice Financial, Dough have been able to expand their business greatly since their launch in 2016.

2. Banking Chatbots 

The integration of artificial intelligence in banking chatbots is eventually going to become an expectation of banking customers. Although some innovative firms have already started to implement chatbots, their usage is yet to become mainstream.

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Chatbots integrated with AI will help users to receive faster responses to solve their payment issues and queries. Example queries would be the format an international payment should be to reach the recipient successfully. Another scenario could be an investigation about a missing payment.

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The Bank of America was the first major bank to integrate chatbots into their systems. They have named this AI chatbot, Erica. The intention of Erica, is to allow users to better manage their finances. This will be achieved through chatbot voice and text interactions that resolve queries and provide suggestions.

3. Fraud Detection 

In current times, payments take place in real-time, therefore, we need real-time fraud detection techniques.

The management of these transactions to eliminate fraud and errors by humans alone is becoming nearly impossible. A significant reason for this is the volume of online transactions that take place. According to the latest reports of global digital payments, the volume of transactions will reach a milestone of approximately 726 billion by the end of 2020.

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This is why Banks are starting to investigate how they can use machine learning and artificial intelligence in digital payments, to help the fight against payment fraud and other means of fraud. The hope is that artificial intelligence and machine learning will help banks to rapidly monitor all data of transactions in real-time.

This in turn should eliminate, or at least significantly reduce the occurrence of fraud from transactions. AI in payments will also help users and bank systems to spot illegal or suspicious transactions.

4. Reduced False Declines 

They are instances where the layered transaction protection put in place to reject suspicious activity, can actually cause great inconvenience to innocent customers. This unfortunate situation usually occurs at the checkout system online or in-store. When this occurs in-store, not only is it inconvenient for the customer, but it can also bring embarrassment. The effect on the economy is even grander.

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Researchers have concluded that $118 billion of false transaction declines take place each year in the USA alone. Much of these funds are never put back to the retailer. This is because of the reduction in customer loyalty and trust as a result of this customer experience. Through the use of AI pattern identity skills and device studying, MasterCard is planning to facilitate actual real-time authorization to prevent the occurrence of these false declines. If this works, it will provide a much more enjoyable shopping experience for buyers.

5. Personalized Services 

With the help of Machine Learning, chatbots will observe the activities of humans. This will involve studying their interests, and making personalized recommendations of products that the user will find useful. This is in addition to enabling payments to be made through the app’s API. These personal recommendations of products and services is a great showcase of Artificial Intelligence in digital payments.

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Moreover, artificial intelligence in digital payments is also allowing the lenders to have a look into the user’s creditworthiness to help them score credit more accurately. In the United States, lenders currently use the traditional FICO score to identify the credit score of an individual.

6. Increased Automation for Better Insights 

There is no doubt that the impact of Artificial Intelligence on the payment industry is incredibly exciting. From changing the way how people invest their money, to making the borrowing process more accessible to the public. AI in payments will bring a huge impact on global economic scenario.

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One of the major advantages of artificial intelligence in payments is that it helps companies to vastly improve the efficiency of their operational services. This is achieved through reduced payment processing time and providing automated user insights that are highly accurate.

7. More Informed Decisions 

AI in payments has the capacity to help guide making investment decisions through quantitative techniques. In particular through the analysis of big data. An increasing number of teams from key market players in recent years have adopted big data.

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Big data collects information that can be leveraged by investors to make informed choices on key issues. However, the time taken to analyze big data is extreme. Therefore AI is required to streamline this process. As this method to obtain information improves, this will of course increase the number of adopters in the coming years.

Conclusions 

Many industries have already started to extract the potential that Artificial Intelligence holds for them. It seems inevitable that the payment industry will be heavily affected by AI in a variety of positive ways. Since the future of the technology holds even more potential, the value AI software development brings to FinTech could be more than anyone has envisioned. This is just the beginning of the positive changes that AI can bring to various industries, especially for the payments industry.

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