AI and machine learning are the two terms that are currently in the thick of the technology debate as they have become a mainstream solution across numerous sectors worldwide, thanks to faster processing speeds, cloud computing, and advances in big data. Big data refers to extremely large sets of data that are analyzed to reveal trends, patterns, and associations relating to human behavior and their interactions. This may refer to both structured and unstructured data. AI experts have the potential to mine big data for information and use it in machine learning projects and other advanced analytics applications.
AI services have long been used in credit card systems and banking to detect and spot fraudulent activity. AI is now making its way into other areas of the financial services and payments industry. Let us analyze the various aspects in which AI plays a crucial role in the payments industry.
1.Enhancing Fraud Detection
Approximately two decades ago, e-commerce brought about a revolution in the way goods were bought and sold in an online setting. People are no longer bound by time zones or borders. This has brought us to a world where real-time payments required real-time fraud detection. Owing to the number of transactions that happen electronically, it is impossible to have humans alone to monitor these transactions.
According to a report by Capgemini, French consulting and technology multinational, global digital payment transactions are expected to reach 726 billion by the year 2020. Machine learning, a subset of AI, can intelligently analyze and monitor large amounts of data in real-time and look for commonalities between non-fraudulent and fraudulent transactions. AI systems can be used to send alerts to individuals if they spot an activity that doesn’t appear normal for that user. The system will be able to learn a normal user’s behaviour over time and spot outliers to this behaviour and will be able to alert them at the right time.
2. Computer Vision-Powered Retail and Payment Transactions
An AI-powered store is a recent concept to the world of retail and payments. It refers to recognition sensors placed throughout the store that will help skip the traditional checkout process by detecting what people are picking up and charging them for those items. One such notable company that is pioneering this concept is Amazon. Due to this feature, customers need not wait in long queues to check out. Computer vision is now being increasingly used in the payment process also. Companies have started experimenting with facial recognition systems, to authorize payments and are also using credit cards and other payment systems as a replacement. The main advantage of gesture detection, facial recognition, and voice recognition systems is that it is hard to fool them. In the future, we can just use our face and voice to authorize payment transfers and transactions and skip using cash or a credit card.
Nowadays, many companies are moving towards a hyper-personalized approach to payments and lending. It helps provide tailored offerings, a better view of customers and helps learn the normal spending behavior for each person.
3. Personalized Service
Companies are also looking to bring AI services into other areas of their business. AI-based chatbots are now being adopted by payment and finance firms to answer questions, interact with customers, help make online purchases, and help navigate users through the company app or website.
A chatbot is the most promising and advanced expression of the interaction between humans and computers/machines. It is an artificial intelligence-enabled computer program that stimulates a conversation with a user in natural language. It communicates using telephones, messages, websites, and mobile apps.
Capital One, the bank holding company, has developed chatbot Eno to help customers check account balances, conduct basic account inquiries, and transfer funds between accounts. The smart payment technology provider, Ingenico Group, has partnered with IBM Watson to create an AI-enabled messaging chatbot to help merchants in the hotel, hospitality, and retail industries to conduct payment transactions with customers.
With natural language processing, the chatbot will be able to interact with customers in several languages to find out the interests of the customer and helps customers make payments through the app’s secure payment API (Application Programming Interface). AI and machine learning algorithms allow lenders to look at a variety of data sources for creating personalized profiles that help accurately predict credit risk to approve loans to people who were deemed uncreditworthy previously and offer better pricing to those who deserve it. Companies are adding to this personalized service by using artificial intelligence to analyze a consumer’s spending record and offer less costly options, or recommend eliminating certain products. AI helps monitor spending, cut back spending, provide suggestions on ways to increase savings, and find alternative products.
Conclusion
Artificial intelligence has come a long way in the past decade and has now become part and parcel of our lives. Though it may seem surprising, it is actually an undeniable fact that the data that has been created in the past few years is more than that created in the entire history of the human race. With the world going digital and businesses needing access to vast amounts of data and billions being invested in artificial intelligence and machine learning processes across the globe, artificial intelligence is certainly here to stay. The opportunities and possibilities offered by artificial intelligence are exciting and endless.
If you wish to become an AI expert, check out Global Tech Council.
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