Payments are arguably the face of fintech. When you think about financial technology, it is easy to think about solutions which are making payments faster, easier and more accessible.
In January 2024, we focused on generative artificial intelligence (AI) and how it has emerged onto the fintech scene following its boom in 2023. Artificial intelligence has many uses, and while it can be used for good, it can also be abused by bad actors. As a result, we set out to investigate the impact the popular technology is going to have on the cross-border payments sector – specifically looking at security.
AI is not a barrier for cross-border payments
Serena Smith, chief client officer, at i2c Inc, the card issuer and payment processor, explains that AI will not be the main hindrance for cross-border payments growth in 2024. It will play a big part in ensuring the new payment rails are well protected.
“Artificial Intelligence (AI) will play a pivotal role in elevating security within the cross-border payments space. It will be instrumental in detecting fraud, predicting potential risks, and monitoring transactions in real-time.
“However, the growth of cross-border payments faces several challenges, including intricate regulatory environments, high transaction fees, delays in transfer processes, and disparities in technological infrastructures across regions. Addressing these issues is essential for the sustained expansion and modernisation of cross-border payment systems.”
A proactive way of tackling fraud
Jonathan Shiery, partner, payments modernisation and digital assets, Guidehouse, the consulting firm, notes how AI can be utilised to stop crime in real-time. Consequently, organisations don’t need to take a responsive approach, but rather a proactive one.
“AI will be able to increase security procedures through behaviour prediction, identifying abnormal activity that may be fraudulent and notifying businesses when necessary. Additionally, AI and machine learning will both be able to identify potentially fraudulent activities in real-time and continually learn from past transaction data, allowing businesses to be better equipped and more proactive in preventing fraud from occurring.”
Eyal Moldovan, co-founder and CEO, 40seas, the cross-border trade financing platform, shared similar views, stating: “From a security perspective, AI can be put to work to detect fraudulent transactions more effectively. For instance, AI-driven algorithms can analyse vast datasets in real-time, identifying unusual patterns and anomalies, thus preventing fraudulent activities and enhancing the overall security of international financial transactions.”
Finding a needle in a haystack made possible
AI has the capability to explore complex data points which humans cannot analyse effectively within a certain time constraint says, Clark Frogley, head of financial crime solutions, Quantexa, the big data and enterprise intelligence provider.
“Uncovering criminals using cross-border payments to launder or hide money is like trying to find the proverbial needle in dozens of haystacks, spread across the globe. Although criminals seek to anonymise themselves and their networks, financial footprints and data trails do exist. But without AI and machine learning, it’s an almost impossible task.
“AI allows investigators to find connections in a complex web of multiple data points across potentially dozens of accounts and institutions. A combination of big data, network analytics and AI can sift through the transactions revealing the hard-to-find, hidden links between individuals, companies, and their counterparties, transactions, and addresses across the entire supply chain.
“By resolving seemingly unconnected entities, context-driven AI technology and analytics builds a detailed picture of the criminal’s network, and how the victim and the various professional enablers that facilitate and/or benefit from this activity are connected.”
AI is a two-sided coin
Claire Huddleston, sales and marketing director, Clear Junction, the payments provider, looks at the bigger picture and how AI can be misused in the wrong hands: “The positive developments that AI brings to the fintech industry also present opportunities for fraudulent activities. AI tools, such as ChatGPT, are being turned against fintech companies and their customers, with the creation of fake customer profiles and deceptive tactics to extract sensitive data from customers and financial personnel.
“As real-time connectivity increases transaction volumes, this provides more avenues for fraudsters, and traditional reactive approaches to fraud prevention are no longer sufficient. Instead, banks and fintechs must adopt proactive and pre-emptive measures. As more transactions go cross-border, the risks of breaching compliance obligations intensify. Unlike domestic transactions, international transactions come with greater counterparty and foreign exchange risk, and Anti-Money Laundering (AML), Know Your Customer (KYC), and sanctions screening work to do.
“It’s unsurprising that AI and machine learning tools are being used to automate and streamline what were slow and manually intensive fraud prevention and AML/KYC verification processes, and more quickly identify violations to reduce the risk of falling out of compliance.
“The great thing about AI is that it never gets bored. Its ability to speed-read vast amounts of data in milliseconds and conduct speedy customer ID verification to identify violations enhances the efficiency of these operations. In the blink of an eye, it can ingest large volumes of data, standardise it, categorise it, and index it, making it easier for businesses to analyse it.
“Predictive AI algorithms, capable of detecting suspicious fraud patterns at lightning speed, empower fintechs to move beyond rigid rules-based systems. This enables them to identify and halt bad actors before significant damage occurs.”
