Payment Megatrends

///Payment Megatrends

Payment Megatrends


Payment Megatrends

Artificial Intelligence (AI) has now become reality. Actually, AI is everywhere. For example, it is in your e-mail spam filter, natural voice recognition, online shopping recommendations, or simply about the predictive keyboard on your smartphone.

In fact, Artificial Intelligence will be a huge game changer for payment.

What is Artificial Intelligence?

Artificial intelligence describes the ability of a technical system to replicate “human” behaviors such as learning and problem-solving. Furthermore, there are two subcategories:

Strong Artificial Intelligence: it aims to create a machine that has thinking skills and cannot be distinguished from those of a human being, so it must pass the Turing Test. In fact, no technological system has yet passed this test.

Weak Artificial Intelligence: it is a category for applications that focus on solving real-world problems with machines.

For example, Megatrend AI is to read pictures. Some algorithms can be used to recognize things such as numbers. It might work for a small sample size, but when it comes to handwriting recognition, this approach could fail.

Indeed, Deep Learning and Machine Learning technologies are evolving with ever increasing speed. So, these technologies are part of AI, which imitates the way the human brain works in processing data. So, it finds patterns when this deep learning model is trained using input data in order to predict behavior for new data.

Neural networks are like human brains: Experience makes them wiser

Deep learning uses a neural network algorithm, which is trained with input data. This imitates how the brain works. Deep learning is the most important AI technology. A neural network has many artificial neurons in the human brain.

These artificial neurons and input data are used to find a good model. So, the neural network is a combination of multiple layers that has artificial neurons, which has some weights. These weights are used to transform the data in each layer.

So, the neural network and the training data must be good in order to have good results.

Reduce the risk: the use of Deep Learning technology in payments

Risk decisions in payments are never 100% clear, so deep learning technology can be used for this.

The merchant doesn’t want to accept a payment with a high probability of a fraudulent action or a chargeback. However, rejecting a “good” payment normally results in conversion loss, which is lost revenue for the merchant.

To decide on acceptance or decline of the payment, there are many things to take into account. For example:

  • Time & date:
  • Merchant category codes
  • IP-addresses
  • Social information

A neural network consists of multiple layers of artificial neurons that mimic the behavior of the human brain. Deep learning uses neural networks to find a good model.

By training a neural network with historic risk data, then it will “learn” in order to predict risk for future payments. However, it is very important to have a good dataset and a good deep learning architecture.

So, an AI tool that uses deep learning will become very important for payment companies in the future AI Payment.

The payment industry uses data to make qualified risk decisions. Nowadays, risk analysis can use deep learning technology.

Chatbots and AI-assisted shopping

Chatbots are used for e-commerce to help consumers to find and research products more easily. WeChat is a chatbot application in China that will provide the reach for merchants and are already offering a platform for shops and payments.

There are AI-powered chatbots that will resolve the disadvantages of the smartphone’s limited display size and browsing capability and thus open up all-new sales channels for merchants that require flexible and well-integrated payment solutions.

Natural voice processing

In 2017, there were natural voice processing services such as Amazon Alexa or Google Assistant. It was used in home appliances such as Amazon Echo, the Sonos speaker system and even cars.

Smart Data for Offers & Advertising

So, AI technology is used to target offers better to consumers with the sample size one, which brings new possibilities for merchants to reach their customers.

Payment services and mobile payment services will play a key role here, and they are readily available channels to process data in real-time.

Facial Recognition Technologies and Biometric Identification

Most biometric identification technologies are based on AI-supported technology for decision making. In 2017, Apple launched a facial recognition technology in the new iPhone X.

AI will revolutionize checkout-processes completely and make payments online and in-store more secure. Furthermore, there would be sophisticated identification technologies in order to increase virtualized payment instruments.

Conclusion: AI’s implications for the payments industry

So, Apple, Facebook, Amazon, and Google are the big companies that are developing AI tools. In the case of the payment industry, AI will bring new opportunities to develop products.

It is very important that payment companies think far beyond payment data, and they must use AI tools such as deep learning technologies.

AI tools will change the online conversion process and lead to higher conversion rates and improved security. AI will impact the whole industry significantly in the years to come. AI will become the key differentiator for technology and payment companies.


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By |2019-03-15T19:30:22+00:00September 27th, 2018|Categories: Blockchain blogs, Blog|Tags: , , |1 Comment

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