To better understand how artificial intelligence can be used in payments, it makes sense to take a step back in time to when online shopping first started. The financial industry is one of the industries that have benefitted the most from artificial intelligence. It is exploring fast-paced technological innovation to automate more than just payments. The main purpose of using artificial intelligence in the financial sector is to improve the flow of services. The biggest barrier to adoption right now is the lack of proof points — businesses are eager to see more specifics and use cases around the business applications of AI. While AI has gained popularity in consumer tech, its payments applications thus far are more limited, making some businesses hesitant to dive in.

In the financial services industry, biometric verification is used by mobile apps and other digital payment agents to authenticate a transaction. For example, smartphones can send information with a payment request including behavioral biometric information. These additional signals will make authentication more robust and fraud detection better by identifying inconsistencies in biometric information and payment behavior. Table 1 gives an estimated number of journal articles, reports and other authoritative documents which include news articles and web page articles that helped to shape the direction of the study.

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The other important aspect noted was that financial inclusion is important to bridge the gap between the physical, digital and the psychological use of money. Authors like Arifin (Muneeza et al. 2018) indicate that the emergence of innovative digital technologies such as blockchain and crowdfunding is showing new sustainable ways to support the poor. Retailers and financial institutions are adopting artificial intelligence and machine learning in their business to solve various business problems such as cybersecurity and document digitization. However, many of these companies are also using AI to improve their payment processes for their clients and customers. These types of applications are usually layered into an existing payments technology stack, which could include straight-through processing or robotic process automation .

These robots explain various banking products offered by the bank, the robots can also explain the amount of debt rural customers have and even offer suggestions on the need to save . AI-trained robots can become financial advisors to rural households (Deloitte 2018b; Paul 2019). As a result, AI is helping a lot to allow previously vulnerable groups to be able to access formal financial services . Argued that financial inclusion has been taken as the soft side of financial services with limited attention given to it from the regulators, and policymakers despite its importance in the empowerment of the marginalized population. However, Salampasis and Mention also suggested that the emergence of fin-tech, a new breed of financial innovation, is increasingly closing the gap between unbanked, underbanked and developed societies. Salampasis and Mention believe that digital technology is opening previously closed doors in the digital economy for many individuals leading to more equitable growth and society.

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On the other hand, many emerging payments and banking technology and apps are employing AI from the start. These newer fintechs have the leg up on existing payments players that must affect change from legacy systems to newer technology, which can be a slow and laborious process. Established payments companies will need to increase agility and take some calculated risks in deploying AI and other technology to maintain pace with newer players.

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. These personal recommendations of products and services is a great showcase of Artificial Intelligence in digital payments. Overall, the use of AI and machine learning in fintech has the potential to improve the efficiency and accuracy of financial services, and it can also help to enhance the customer experience.

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We also discuss the winning AI strategies used by fintechs and legacy financial institutions so far, as well as provide recommendations for how banks can best approach an AI-enabled digital transformation. The application of AI in these mobile banking settings makes perfect sense as a driver of the convenience of digital banking. In fact, the dominant channel for chatbot integration will be mobile banking, accounting for 79 percent of successful integrations in 2023, Juniper Research’s chatbot study found. The implementation of chatbots in settings including mobile banking apps will result in a 3,150 percent increase in banking chatbot interactions between 2019 and 2023. AI uses big data to build user profiles for payment settings, analyzing transactional history and past behaviors to establish a pattern. When unusual activity occurs, AI alerts the bank or customer, prompting them to block the account or re-confirm the transaction via text, email or other communication methods.

The app is essentially a chatbot service that is linked to Starbucks’ product, pricing, and payment databases. It is programmed to ask for more details on the items in the customer’s order, as well as allow them to customize their drinks just as they would with an in-person barista. The pilot software most likely accomplishes this by checking each payment against a pre-established baseline of normal payment behavior specific to the client company. Citigroup claims the software can trigger alerts in real-time to show human employees that there is a new type of payment.

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To much fanfare, Open AI, a startup that raised $1 billion from Microsoft MSFT , released Chat GPT, an interface to interact with their AI model. If you fintech trends believe Wordfence should be allowing you access to this site, please let them know using the steps below so they can investigate why this is happening.

• With card-not-present fraud posing a $130 billion threat, according to Juniper Research, sophisticated fraud prevention and detection technologies powered by AI will be a growing area of investment for payments companies.
• AI and machine learning are quickly becoming a valuable tool for payments companies and financial institutions to reduce fraud in all environments, but particularly in securing e-commerce transactions.
• Here the latest data and trends to stay up to date on the most dynamic market of the moment.
• It’s already clear that digital commerce has expanded beyond the desktop and even beyond mobile.
• According to the 2019 Global FinTech Adoption Index, 25% of small & medium businesses use AI technologies in banking, financing, and financial management.
• In conclusion, when we look at the fascinating world of artificial intelligence and the innovative changes it has brought to the payment ecosystem, it is impressive how much it has already been accomplished.

The study used unobtrusive research techniques to analyze objectively the impact of AI on digital financial inclusion. The techniques include conceptual and documentary analysis of peer-reviewed journals, reports and other authoritative documents on AI and digital financial inclusion. The 4IR is affecting almost every facet of our daily life, impacting how individuals relate to technology and changing how and where work is done .

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OpenML Engine software can help banking data science teams create machine learning models for fraud detection using the fraud models provided. It is likely that Citi TTS has used some form of this to create their own models for their banking and commerce clients. Citigroup, or Citi Treasury and Trade Services , and how they use predictive analytics to facilitate their accounts payable process. We also cover their new partnership with Feedzai to offer payments fraud detection solutions to Citi TTS clients. Maturing mobile P2P will enhance the opportunity—and need—for providers to monetize their product, since a bump in volume has put the industry in a better position than ever to begin capturing revenues from the services.

How does Artificial Intelligence (AI) work with digital payments?

This is one of the top application of artificial intelligence in the payments industry. Andy Tylor, the CEO of Douugh is a big advocate of the huge potential of artificial intelligence in payment cards. He says, “Looking at the future of banking, it was clear artificial intelligence would play a pretty big role”. Here the latest data and trends to stay up to date on the most dynamic market of the moment. Among the fraud prevention solutions available on the market at the moment, artificial intelligence plays a big role in detecting and anticipating fraud. For security reasons, the PayPal chatbot asks the user to log into their account each time they use it to access personal data.

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Wang and He also described digital financial inclusion as broad access to and use of formal financial services by the excluded or underserved individual. Digital financial inclusion began to attract the attention of many people as a result of the success of M-PESA, one of the payment innovations introduced in Kenya (Beck et al. 2018). With M-PESA, mobile money is used for digital payments (Dubus and Van Hove 2017; Van Hove and Dubus 2019).

Although some innovative firms have already started to implement chatbots, their usage is yet to become mainstream. Nimble AppGenie being a tech-savvy development firm is always up-to-date, offering solutions that match the latest market trends. Although advanced, in order to achieve an optimal performance, these tools need to be used in conjunction with human interaction. They are extremely useful to answer to routine questions and solve common problems of customers, while saving human intervention for when needed. When the customer is ready for the purchase, they can make their payment via the chatbot, which helps them along the way with the different checkout and authentication steps.

As a market-leading mobile app and web development company, Nimble AppGenie is helping businesses around the world reach the success they desire. Nvidia, Share of financial services professionals who think that artificial intelligence is important to succeed in the industry worldwide in 2020, by position. PayPal also claims to leverage machine learning for fraud and risk mitigation across their payments platform.

A strategy that focuses on the use of artificial intelligence for offering personalized services to clients using chatbots can even be implemented by hospitals, restaurants, and hotels. When it comes to payment, personalized suggestions based on customer queries will help speed up consumption. Banks and financial institutions are particularly opaque when it comes to how they implement and leverage AI for their business. Mastercard is a key example of this because they use most of their AI applications internally and have only recently begun to make their technology more transparent to the greater financial industry. The chatbot also covers questions about refunds, and can also help the customer request or check the status of a refund.

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. This study article is premised on desktop research to investigate the impact of AI on digital financial inclusion.

Moreover, digital financial inclusion is characterized by retail agents with digital devices connected to communication infrastructure that will transmit and receive transaction details. This activity allows customers to convert cash into electronically stored value also referred to as cash in or to convert back the stored values back into cash which can also be referred to as cash-out . With digital financial inclusion, additional financial services like credit, insurance and even savings can be offered by banks and non-banks to the financially excluded and those underserved individuals through digital tools like AI. Increasingly, digital payments are being used for financial transactions (Muneeza et al. 2018).