Scams and Fraud

The rapid evolution of technology, shifting consumer behaviours, and the increasing demand for instant payments have reshaped financial transactions. As online and mobile banking and ecommerce continue to grow, so do the threats associated with fraud and scams. From credit card fraud and identity fraud to wire fraud and tax fraud, financial criminals are becoming more sophisticated, exploiting vulnerabilities in payment systems and security protocols.

Managing fraud risks has never been more complex. Several key factors contribute to the growing challenge:

• Technology advancements – the widespread adoption of AI, GenAI, ML, biometrics, graph analytics, and blockchain is transforming the way fraud is detected and prevented. While these tools provide enhanced security, fraudsters are also leveraging cutting-edge technology to develop more sophisticated attack methods.
• Evolving fraud patterns – fraudsters continuously refine their methods, making it difficult for businesses to keep up. From payment fraud and Ponzi schemes to investment scams and social engineering, criminals use various tactics to deceive financial institutions, merchants, and consumers. Authorised push payment (APP) fraud and instant payment fraud have become particularly concerning, as real-time transactions leave little room for intervention once fraud occurs.
• Regulatory compliance – banks, fintechs, PSPs, and ecommerce platforms must adhere to AML, KYC, PSD3, Open Banking, and AI-related regulations, which are constantly evolving. Ensuring compliance while maintaining seamless customer experiences presents a major challenge for financial institutions operating globally.

Fraud and scam trends in fintech and ecommerce

Fraud continues to be on the rise, as fraudsters leverage GenAI and other technologies that can help them become even more dangerous and hard to spot. With 2025 unfolding, several emerging trends in finance and ecommerce fraud are becoming increasingly prevalent:

• Deepfakes and GenAI-powered scams: deepfakes and GenAI are used as techniques to generate fake content to make scammers look like genuine people. Using a random image of a stranger, fraudsters create deepfake scam videos or even resort to scam phone calls to engage with potential victims and become more trustworthy.
• Biometric breaches: with the increasing adoption of biometric security measures, there is a growing concern over the potential for biometric data breaches, which could lead to unauthorised access and fraud.
• Cryptocurrency scams: scammers revert to cryptocurrency scams, using social engineering techniques to lure novices into trading or investing in cryptocurrencies.

Financial fraud affects a broad range of industries, from banking and fintech to ecommerce and digital marketplaces. Some of the most prevalent fraud types include:

• Phishing – bad actors trick individuals into sharing personal information for seemingly legitimate reasons, usually via scam emails, while impersonating renowned companies. For instance, they might ask customers to reset their passwords or update their account information through a link provided by the scammers. This leads to a fake front page resembling the official page of the company. Scammers then steal the personal data provided by the victims, taking over their accounts and accessing sensitive information. When similar activities are carried out using phones rather than a digital medium, the process is called vishing.
• Account takeover – fraudsters gain unauthorised access to someone else’s account, often through phishing or exploiting weak passwords, to make fraudulent transactions or steal sensitive information. Account handover is when a real user gives control over their account to a fraudster, in exchange for an amount of money, usually for older accounts.
• Identity fraud – an individual uses stolen personal information to make unauthorised purchases, open accounts, or even apply for credit cards and other services. Fraudsters may acquire this data through phishing attacks, data breaches, or social engineering tactics. Synthetic identity fraud occurs when a bad actor uses a combination of fake and real data to create a new identity that appears to be a real person. This fraud type can impact the real person connected to the fake identity by damaging their credit history, for instance.
• Card testing – fraudsters use stolen card information to make small, low-value transactions to test if the card is active and valid. If successful, they proceed with larger fraudulent purchases.
• Friendly fraud (first-party misuse/chargeback fraud) – involves a legitimate customer ordering an item, receiving it in good condition, and later disputing the charge with their bank, claiming the transaction was unauthorised or the product was not received.
• Policy abuse –  customers exploit merchants’ policies to gain unfair advantages. This can include creating multiple accounts, misusing promotions, or violating return conditions.
• Tax fraud – individuals or businesses manipulate tax filings to evade payments, leading to significant revenue losses for governments and legal risks for financial institutions.
• Instant payments fraud – as instant payment systems become more popular, fraudsters exploit their speed and irrevocability to bypass traditional fraud prevention measures.

Fraud prevention and detection: strategies for banks, merchants, and PSPs

To effectively combat fraud schemes, businesses must adopt a multi-layered approach to fraud prevention and detection, incorporating technology, data intelligence, and human expertise. Essential strategies include:

• AI & ML-driven fraud detection – Advanced risk scoring and real-time transaction monitoring help identify fraudulent activities before they cause harm.
• Risk assessment & profiling – Behavioural analytics and geolocation tracking help detect suspicious activity based on user habits and transaction patterns.
• Biometric authentication & device intelligence – Facial recognition, fingerprint scanning, and device fingerprinting add additional layers of security, reducing the risk of account takeovers.
• Graph analytics & behavioural analysis – These tools help uncover hidden connections between fraudulent entities, enabling proactive fraud prevention.
• Collaboration & data sharing – Industry-wide initiatives such as fraud registries, data consortiums, and intelligence-sharing networks help detect emerging fraud patterns and prevent large-scale attacks.

The Paypers – your resource for fraud insights and solutions

At The Paypers, we provide comprehensive insights into the ever-evolving fraud landscape, offering:

• Educational content explaining key concepts such as fraud meaning, scam meaning, and fraud types.
• Expert interviews and webinars with industry leaders discussing fraud management, risk assessment, and fraud detection solutions.
• Reports and case studies on the latest fraud prevention strategies and regulatory developments.