We are living in an exciting time where artificial intelligence is slowly taking over our daily lives.Alexa and Siri are slowly replacing personal assistants. We have AI-powered cameras at our workplaces, AI-powered robots to do our tasks, AI-powered automotive, and what not! So, it's no surprise that AI and digital transformation have encompassed all industries, and the payment industry is no exception. The proliferation of digital payment methods is pushing us towards cashless alternatives. With a massive volume of transactions being done online, there is a greater risk of data leaks, breaches of payment processing security, and fraudulent cases. This is where AI in the payment gateway industry plays its role!

The world is in an exciting phase of artificial intelligence that is slowly taking over our daily lives. We have AI-powered cameras at our workplaces, AI-powered robots to do our tasks, AI-powered automotive, and what not! So, it's no surprise that AI and digital transformation have encompassed all industries, and the payment industry is no exception. The proliferation of digital payment methods is pushing us towards cashless alternatives. With a massive volume of transactions being done online, there is a greater risk of data leaks, breaches of payment processing security, and fraudulent cases. This is where AI in the payment gateway industry plays its role!

Artificial Intelligence, also known as Artificial Intelligence, is well-known for streamlining processes safely. However, when it comes to digital payment solutions, AI goes beyond streamlining and providing security. AI brings automation to online payments and allows users to monitor them. It is fascinating to note seven amazing uses of AI within the payment industry. Although self-driving cars are not a new concept, have you ever considered that the technology behind self-driving cars could be used to fraudulently apply for loans or cards?

In recent years many successful machine learning applications have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to information-filtering systems that learn customers' buying behavior, to the most popular application of AI in financial services -- and perhaps the most limited -- the chatbot, a program that converses with customers through text or speech. So when we talk about Machine Learning, we talk about the process of using digitized labeled data which is stored as a data set in a database, and using automated processes to create analytics from which users can derive information. Whenever a Data Set (X) can be used to create analytics from which users are deriving information, the next step is to use Machine Learning with the help of algorithms to create a New Process changing the data to (X X 1), which in itself provides a new Data Set completing the Machine Learning Model. Payment systems generally generate a lot of data, because of industry standards, and the good thing to know is much of this data is well structured which reduces the effort needed to prepare it for use in machine learning algorithms. In recent years many successful machine learning applications have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to information-filtering systems that learn customers' buying behavior, to the most popular application of AI in financial services -- and perhaps the most limited -- the chatbot, a program that converses with customers through text or speech.

With the launch of VisaNet AI, we are seeing Visa in this particular case take matters into their own hands and develop products and services that are targeted at improving the services provided by their own clients, who are not able to keep up with the pace of technological advancement. For a long time we have known that data is the new oil, and that companies who wish to stay competitive in today's landscape, need to take aggressive steps into ensuring that their strategy, infrastructure and processes are data-driven. However, within the Payments industry we know that a lot of companies are still struggling to do so. VisaNet AI, which is a set of network services that helps deliver smarter authorization, clearing, and settlement for banks, merchants and consumers, is a great example of how companies should work on improving their core services. For years, we have worked with issuers, acquirers and merchants to drive through that the performance of their authorization is at the core of what payments should be.

How are Machine Learning Models going to change the Payments Industry? It wasn't so long ago that CEO's and large commercial banks were convinced that more bank locations would always be necessary to service and acquire new customers. However, in the last ten or five years we have seen an emergence of Digital Banks, that have never and will probably never own a physical location, but still manage to grow their user base and add additional services including insurance, mortgages, and loans. In the Banking industry, we have seen companies like First Bank of Nigeria, United Bank of Africa, Zenith Bank, Guaranty Trust Bank dominate for well over twenty years. However, just like the digitization of banking has forced incumbents to change their strategies, the digitization of payments has provided companies like Flutterwave, Paystack, Remita and lately even Korapay to take up some of the market shares, not by focusing on traditional businesses, but by focusing on startups who have grown to overshadow and sometimes even bankrupt traditional businesses.

AI or Artificial Intelligence is known for streamlining processes securely, but when it comes to the digital payment solution, AI goes beyond streamlining and offering security. AI brings automation and enables users to monitor online payments. A self-driving or autonomous car is no longer a new concept, but have you ever thought that the technology used behind a self-driving car can be used in finding fraudulent card or loan applications? Yes, the neural network technology or Artificial Neural Network (ANN) is the technology behind the autonomous car. It imitates the human brain and has played a vital role in finding the stolen identities from the Equifax data breach and other incidents.

Mr. Sunil Khosla, Head Digital Business, India Transact Services LimitedDigital payment is the fastest moving and most dynamic sector of financial services. The thriving growth of digital payments is matched by the pace of technological advancements in the sector which is faster than ever. Affordable internet, smart phone penetration, payment apps, booming e-commerce, and hassle-free online payments have all collectively contributed to the exponential rise of digital payments. We are living in a transformational era of human history where Artificial Intelligence (AI) forms a central part of this transformation. AI has a key role in digital transformation, especially in financial services sector.

The first Model Artificial Intelligence Governance Framework in Asia was released by Singapore in January this year, in collaboration with the World Economic Forum's Centre for the Fourth Industrial Revolution. AI, an emerging frontier in technology that allows technical systems to simulate human intelligence and behaviors, has vast applications in many fields. As part of its «Smart Nation» pursuits, Singapore launched its National Artificial Intelligence (AI) Strategy at the Singapore FinTech Festival and Singapore Week of Innovation and TeCHnology (SFF x SWITCH) conference. Within the next three years, AI-powered chatbots will become the first point of contact for residents to report issues with city services while marking systems in schools will soon be automated. Across the financial landscape, AI has also weaved itself into the workings of the industry.

As digital payments turn popular among Hong Kong consumers and more payment options are becoming available, EJ Insight invited David Lau, General Manager, Wirecard Hong Kong, Macau & Taiwan, to share his views on the opportunities, challenges and trends in this arena. Q: With a wide range of digital payment options from numerous players, is the Hong Kong market already too crowded? What sort of opportunities does Wirecard see in Hong Kong? A: Contrary to popular belief, the Hong Kong market is not that crowded yet. Despite the overwhelming reliance on the Octopus card, the bigger issue of digital payments has always been that the majority of digital payment systems and infrastructure are not robust enough, as of yet.