How FinTechs can stop payment fraud before it starts

July 15, 2025

Payment fraud remains one of the most persistent threats to financial institutions and payment platforms in 2025.

According to Resistant AI, earlier this year, Cash App’s parent company, Block, agreed to pay up to $255m to settle claims that weak anti-fraud measures allowed criminals to misuse its systems for money laundering and scams. This case highlighted the escalating cost of inadequate fraud prevention and the urgent need for more robust, layered defences across the payments ecosystem.

Fraud in digital payments is no longer an isolated incident—it’s a structural challenge embedded in the design of modern platforms. The problem often begins at the onboarding stage, where fraudsters exploit weaknesses in document verification and identity checks to gain access. Using tactics like synthetic identity creation and account takeovers, bad actors can establish footholds on platforms under false pretences. Once inside, they rapidly move funds through mule networks and abuse platform features designed for speed and convenience, leaving institutions struggling to contain the damage.

These vulnerabilities create ripple effects throughout an organisation’s infrastructure. When criminals bypass onboarding controls, their activities quickly infect transaction systems, necessitating stronger anomaly detection, behavioural analysis, and transaction monitoring. To effectively combat this, payment platforms need to adopt a layered defence strategy that integrates secure onboarding, document fraud detection, and transaction monitoring—not as siloed tools, but as part of a cohesive fraud prevention ecosystem.

In essence, payment fraud is the deliberate misuse of a payment application or tool to conduct illegal financial activity. It targets two critical moments in the process: onboarding and transactions. While “fraud” and “financial crime” are traditionally distinct—fraud being deception for personal gain and financial crime encompassing broader offences like money laundering or terrorist financing—these categories are increasingly converging.

For instance, authorised push payment (APP) fraud may appear to be a simple scam, but it often relies on complex money mule networks and laundering operations. This merging of fraud and financial crime underlines why modern fraud prevention requires both advanced technology and holistic oversight.

At the onboarding stage, criminals use document forgery and stolen data to create synthetic identities, mule accounts, and fake businesses. They may even hijack legitimate profiles to evade detection. When KYC (know your customer) and KYB (know your business) controls fail, fraudulent accounts gain unrestricted access to exploit systems. True protection demands verification that goes beyond surface-level checks—ensuring both document authenticity and application legitimacy.

Once fraudsters are embedded, transactional payment fraud begins. Using stolen or synthetic credentials, they initiate high-velocity transfers, laundering money through legitimate-looking transactions. AI-powered transaction monitoring offers one of the most effective countermeasures, enabling adaptive behavioural analysis that evolves faster than traditional rules-based systems. Such AI tools help detect suspicious patterns hidden within ordinary activity, particularly in cases involving money mules or synthetic mule accounts.

While AI alone cannot solve all challenges, it empowers compliance teams to do more with less—streamlining detection and allowing human investigators to focus on complex, high-risk cases. Prevention, however, remains the ultimate goal. By stopping bad actors before they ever enter the system, payment platforms can reduce the risk of cascading fraud that undermines trust and financial integrity.