Safeguarding within payments: a modern approach to fraud management

The importance of fraud management and the power of new technologies and approaches to detect and protect against financial crime was discussed in detail during the expert session ‘Payments data: The ultimate weapon against financial crime?’ at Sibos 2023. The central question: what will fraud management look like in an increasingly complex digital future? This year's Sibos theme emphasises collaboration, which is essential for the prevention of fraud and financial crime. In this blog we will take a look at the insights from an eye-opening session that shed light on the current state of fraud management and money laundering.

The rising threat of financial crime

Society has embraced digital payments for convenience and efficiency, while commerce has identified the opportunities that lie within it. As such, criminals, whether individuals or enterprises, have found new avenues to exploit vulnerabilities. Financial crime and payment fraud encompasses many different malicious activities, including money laundering, credit card fraud, identity theft, account take over, and phishing attacks. Statistics were presented during the session: today, money laundering is a huge global problem. Approximately, it represents around 2 to 5% of the global GDP and only 1% of this crime is caught. The costs are enormous with around $274 billion on compliance costs alone. The growing scale and complexity of these threats have highlighted the need for smarter and more adaptive detection and prevention mechanisms.

Banks and payment providers must respond to potential fraudulent processes by investing in data management, fraud detection infrastructure, AI, and experts with the knowledge to handle new technologies. Money laundering networks are highly complex, while financial institutions often have a siloed view of these networks. The lack of standardisation makes it challenging to analyse data effectively. The broader the view and the more connected the data is, the better visibility you can have on money laundering networks.

The session highlighted two important research projects:

• Beju Shah, Head of the BIS Innovation Nordic Centre presented project 'Aurora' by BIS, which aims to improve AML (Anti-Money Laundering) performance and effectiveness while protecting privacy and sensitive data. It showcased the potential of artificial intelligence (AI) and privacy-enhancing technology (PET) in combating money laundering.
• Nick Maxwell, Head of the Future of Financial Intelligence Sharing (FFIS) within the RUSI Centre for Financial Crime and Security Studies discussed their international research program that underscored the unique opportunity for policymakers to unleash the potential of collaborative payments analytics in detecting economic crime risk. This requires significant policy changes, innovation, and public and private collaboration.

AI as the game changer for fraud management

With the capacity to process and analyse vast amounts of data at speed beyond human input, AI algorithms can detect patterns, anomalies, and trends that may escape human observation. This capability forms the foundation of a proactive and dynamic approach to fraud prevention for modern fraud prevention systems.

In combination with human-led systems, such as manual investigation and handling, consultancy and general customer service channels, AI detection and analysis can help to create a robust defence against financial crime and payment fraud. Like most defence systems, proactivity is key to ensuring a continuous barrier, especially when technological advancement also provides new ways for fraud and cyber-attacks to be committed.

Key to the modern consumer is the idea of frictionless experiences and frictionless payments. People don't want to have to go through multiple authentication processes, especially if it takes them out of the app or website they are using. As such, it's important to balance these 'experience' requirements with the need for effective detection and prevention.

Balancing act

The journey towards achieving this balancing act is not without challenges. These include having multiple payment service providers in the value chain. With more entities involved, data becomes fragmented and interrupted, which underlines the need for collaboration between these entities and a reliable fraud labelling process since this is a fundamental requirement for AI. This fragmentation restricts obtaining a holistic view of transactions and customer behaviours. Second to this is increased regulatory compliance. Regulations and monitoring requirements constantly change alongside rapid digitalisation and innovation, making compliance a time-consuming and costly affair. Finally, there is an increased need for end-to-end fraud detection. This is required at every stage of the customer journey.

These, alongside more practical challenges such as resource management, cost increases and general market trends have created a perfect storm - a confluence of escalating cyber threats, complex regulatory landscapes, and ever-increasing customer expectations.

In conclusion, AI has proven its potential to add significant value to the detection of financial crime. Although the infrastructure, data, and expertise requirements are high, there's also a high return on investment. This session highlighted the importance of collaboration and the potential of AI and privacy-enhancing technologies in combatting money laundering and financial crime. It's an exciting time for the industry, with the opportunity for significant policy changes and innovation in payments analytics.

Learn more about Worldline's Payment Fraud Management solution.