Mapping Financial Fraud: Trends, Patterns, and Risks

Fraud has become a defining risk of the digital economy, affecting individuals across all demographics. The Central Bank of Ireland’s research paper “Caught in the Net” provides one of the most comprehensive analyses of fraud exposure in Ireland, examining who is most at risk, how fraud occurs, and what factors predict victimisation.

The Scale of Fraud in Ireland

The study reveals that fraud is widespread rather than exceptional. Around one in three Irish adults (35 per cent) report having experienced some form of fraud or scam. This high prevalence highlights a key insight: fraud is not confined to vulnerable or niche groups, it is a mainstream consumer risk. While many incidents involve relatively small financial losses, the aggregate cost is substantial, with reported fraud losses reaching hundreds of millions of euros annually. Importantly, the true scale is likely underestimated. A striking 38 per cent of victims do not report fraud to banks or authorities, meaning official statistics capture only part of the problem.

Types of Fraud: How People Are Being Targeted

The research identifies several dominant fraud types in Ireland. Online purchase scams are found to be the most common, affecting nearly half of all victims. Then there is card fraud, including stolen or misused debit/credit details. Phishing and impersonation scams such as emails, texts, or calls posing as trusted entities and also investment fraud which was found to be less frequent but associated with larger financial losses overall. These patterns align with broader payment fraud data, which shows that card payments and credit transfers account for the majority of fraudulent activity, with fraudsters often exploiting digital transactions. A key structural feature is the cross-border nature of fraud, with a large share of fraudulent payments transferred to accounts outside Ireland.

The Strongest Predictor: Risky Online Behaviour

One of the most important findings of the paper is that behaviour matters more than demographics. The Central Bank identifies risky online behaviour as the single strongest predictor of fraud victimisation, outweighing factors such as age, income, or education. 

Examples of risky behaviour include:

• Purchasing from unfamiliar or unverified websites
• Sharing financial details across insecure channels (email, messaging apps)
• Responding to unsolicited offers or promotions
• Sending money to individuals met only online
• Not using security measures such as multi-factor authentication 

This shifts the narrative away from “who gets scammed” to “how people interact with digital environments.”

Behavioural and Psychological Drivers

The findings suggest that fraud is often enabled by human decision-making under uncertainty, rather than purely technical vulnerabilities. Fraudsters exploit trust and urgency (e.g. “limited-time offers”), authority cues (impersonating banks or delivery services) and convenience habits (quick online purchases, saved card details). This aligns with the concept of “social engineering,” where manipulation, not hacking, is the primary tool. In payment fraud data, this is reflected in the rise of “manipulation of the payer” fraud, where victims are convinced to authorise payments themselves.

Reporting and Recovery: A Critical Gap

The paper highlights a crucial but often overlooked issue, reporting fraud significantly improves outcomes. 57 per cent of victims who reported fraud recovered their money. Compared to this, only 13 per cent of those who did not report recovered their losses. Despite this, many victims do not report incidents, possibly due to embarrassment, uncertainty, or the belief that losses are too small to pursue. This creates a feedback problem as underreporting reduces visibility of fraud trends and weakens systemic responses.

Who Is Most at Risk?

Contrary to common assumptions, fraud risk is not confined to older or less educated individuals. Instead, risk correlates with the frequency of online activity, engagement in e-commerce and digital payments and exposure to unsolicited communications. In other words, more digitally active individuals may face higher exposure, even if they are otherwise financially literate.

Policy and Consumer Implications

The findings carry important implications for policymakers, financial institutions, and consumers. There needs to be an increased focus on behavioural interventions. Traditional awareness campaigns may be insufficient. Targeted interventions should focus on promoting safer online habits, how to recognise scam patterns and encouraging scepticism toward unsolicited offers. Payment security should be strengthened. Technologies like Strong Customer Authentication (SCA) reduce fraud risk, but gaps remain, especially in cross-border transactions. Reporting must be encouraged as improving reporting rates could lead to the increased recovery of funds, provide better data for enforcement and ultimately, disrupt fraud networks. Finally, to address cross-border fraud, given the international nature of fraud flows, cooperation between jurisdictions is essential.

This report paints a clear picture: fraud in Ireland is widespread, evolving, and deeply tied to everyday digital behaviour. The most important takeaway is not that fraud is inevitable but that it is predictable and, to a large extent, preventable. By understanding the behavioural patterns that increase risk, individuals and institutions can take meaningful steps to reduce exposure. In a world where digital transactions dominate, fraud prevention is no longer just a technical issue, it is a behavioural one.