Fraud Prevention: Rethinking the Evolving Landscape

By Ronen Assia, Managing Partner, Team8

As fraud continues to transform and expand, it’s important to understand the various typologies and methods used by fraudsters. Without this knowledge, identifying your vulnerabilities or maximizing ROI on fraud prevention efforts becomes nearly impossible. Fraud is no longer just a nuisance; it has become a significant economic threat with losses estimated to exceed $250 billion by 2031. The need for a revolutionary approach in fraud prevention is clear. Rapid development of Generative AI technologies promises immense potential but also poses new risks, necessitating a shift in the strategies we must deploy.

Fraud can no longer be viewed as a simple, isolated event that fits neatly into categories like ACH fraud or synthetic identity fraud. Instead, it should be understood as a series of actions fraudsters meticulously plan, investing time (and often money) to ultimately steal funds. To accurately define any instance of fraud, you must first identify the payment rail (e.g., ACH, card), the tactics employed by the fraudster (e.g., phishing, stolen identity), and the method by which money was stolen (e.g, chargebacks, authorized push payment).

With these typologies in place, each fraud incident can be analyzed as a sequence of actions that collectively enabled the fraudulent transaction, helping professionals to better communicate about various types. For example, you can talk about what portion of fraud was executed on ACH versus credit card versus check, or which forms of deceit – such as synthetic IDs, phishing, or deep fakes – were employed.

Our current understanding of fraud is often too narrow to effectively capture the multifaceted tactics employed by modern fraudsters. A more granular approach can provide clearer insights:

• Integrated Fraud Typologies: Breaking down fraud into specific actions, payment methods, and execution strategies helps in understanding the entire lifecycle of fraudulent activities.
• Examples and Case Studies: Detailed case studies can illustrate how different types of fraud, such as synthetic identity fraud or first-party fraud, are interconnected across various payment rails and actions.

Fraud needs to be tackled in a holistic manner. When someone uses phishing to steal an identity, opens a checking account, and then executes a series of transactions with insufficient funds, is that ACH fraud, phishing, or stolen identity? It’s all three. Fraud can involve synthetic identities to exploit ACH or credit card networks. In reality, an incident can simultaneously be first party fraud and card fraud; or both synthetic identity fraud and ACH fraud. Money mules, meanwhile, aren’t a distinct type of fraud but a tactic fraudsters use, often in combination with other methods, to move illicit funds out of the system.

Financial platforms need to consider the impact that technological advancements have on fraudulent activity and consider using vendors that are focused on specific fraud scenarios, rather than continue to rely on generic “payment fraud” solutions and hope for the best. Some of these technological advancement include:

• Hyper-Personalized Phishing: AI technologies are now able to craft phishing emails that are incredibly personalized, making them difficult to distinguish from legitimate communications.
• Advanced Document Forgery: The use of deep learning to create forged documents and IDs is alarming, as these often bypass conventional detection systems.
• Synthetic Media Threats: AI-generated audio and video clips can impersonate public figures or loved ones to manipulate victims, presenting a formidable challenge to existing security measures.

Building a Resilient Framework for Fraud Detection

While cyber and fraud may differ in business considerations, they are similar in how cyber criminals and financial criminals search for vulnerabilities in defense layers. It’s not just about leveraging the same technology but also adopting the same mindset.

On a practical level, a deep understanding of fraudsters’ technology stack – from devices and emulators to accounts and identities – positions you to identify the right fraud signals and reduce fraud more efficiently.

Adopting a multi-layered security approach that continuously learns and adapts to new fraud patterns is essential to defend against the dynamic nature of fraud. For maximum impact, fraud prevention systems need to be fully integrated and holistically applied across various scenarios including::

• Comprehensive Onboarding Checks: Enhanced due diligence during the customer onboarding process to prevent synthetic identity fraud.
• Advanced Authentication Measures: Implementing multi-factor authentication and biometric verification to fortify access controls.
• Enhanced Transaction Monitoring: Monitoring systems must be fully integrated with onboarding and authentication systems to properly identify fraud patterns that start well before the transaction itself.

A Need for Collective Action

Advancements in technology will likely make fraudsters more brazen, persistent, and unfortunately, more successful – unless technology rises to the challenge. The fintech industry has the power to deliver a new generation of fraud tools that can evolve just as rapidly. Developing a more robust language around fraud typology will empower fintechs and their future customers to cut through the noise and effectively combat fraud.