Part 4
Payments

The payments industry is constantly evolving and Part 4 looks at how AI can revolutionize it at a time when people are no longer bound by borders or time zones. We know from our daily life that goods and services are purchased from across the globe, and at any time of the day. Research shows, for example, that night-times are when a lot of people shop online, especially for clothing and food.

For this reason, the old school system to detect fraud is no longer efficient: right now, what AI can help provide is real-time fraud detection to support the round-the-clock/round-the-globe payment sector. This part offers solutions and ideas around this dramatic shift, and the challenges and opportunities it presents.

The key issue is that as so many transactions happen at every moment, it is proving impossible for humans alone to provide oversight and control to ensure errors and fraud incidents are kept at a bearable level. This is where machine learning comes into play, as it allows the monitoring of activities and the early detection of anomalies to act on.

Furthermore, as AI is transforming the payments industry, consumers are increasingly pushing for more seamless experiences. If you add open banking and the PSD2 Directive, it becomes apparent that consumers will want to be able to safely and quickly make payments via their devices and across platforms without having to experience frictions.

Again, this is an area explored in this part with fascinating insights about the intersection between digital identity, security and privacy necessary to provide customers with the frictionless experience they are seeking.

And there are other ways AI is reshaping the payments industry. At a time of great competition for the retention of customers, AI can be used to provide recommendations about wise spending and savings by analysing the payment history of a client – this is a service that would be welcomed by clients if done in compliance with high privacy and transparency standards.

And, finally, great benefits can also involve the wider supply chain if, for example, an AI system were able to assess the likelihood of an invoice being settled right after it is issued. For companies, this would mean a massive step up in their logistics and overall efficiency across the supply chain.

This part explores all this, and beyond. This valuable knowledge can be a source of learning and understanding of the possibilities ahead of us.