Cyber Fraud Fusion is a modern approach to fraud management that unites fraud, cybersecurity, risk and intelligence functions into a single collaborative model. It breaks down silos between teams and technologies to create a real-time view of threats across an organisation. The problem with fragmentation Traditionally, fraud teams focus on financial crime while cybersecurity handles technical incidents. Yet, attacks increasingly cross both domains - a phishing email may start in IT logs but end as a financial loss. PORGiESOFT Security recently introduced Fraud OS - Cyber Fraud Fusion to close this gap. The platform integrates and aggregates fraud incident data across SMS, email, websites and open-source intelligence (OSINT) to detect cross-channel fraud patterns and connect the dots. How Fraud Fusion works Data ingestion: Fraud signals from multiple sources are captured (tactical intelligence, transactions, working group notes, incident logs, alerts, external threat intelligence feeds

Why do consumers respond to smishing messages despite knowing it exists? The Smishing Report 2022 dedicated an entire section to this paradox - revealing that the issue lies less in awareness, and more in behaviour under pressure. The awareness gap According to wider analysis, 95% of consumers could not reliably detect fraudulent SMS messages. This reflects what psychologists call overconfidence bias - people believe they can spot scams, yet fail to apply that confidence under stress. The fraud moment PORGiESOFT Security’s victim research and OSINT analysis revealed a pattern called the fraud moment - a short window between receiving a message and deciding to act. During that short interval, emotional response overrides rational thought. The report identified three high-risk triggers: Financial anxiety – messages about refunds or fines. Social pressure – fake job or delivery updates. Authority bias – impersonations of government or banks. In each case, the victim’s emotional state det

PORGiESOFT Security researched and provided a quantitative map of the UK smishing ecosystem, detailing how threat actors, infrastructure and victims intersect. What did we learn? 1. Attack infrastructure Nearly 99 percent of all messages were written in English, confirming that UK consumers remain a primary focus for global smishing campaigns. The study identified nine distinct classes of smishing messages, from Class A (URL only, 58 %) to Class M (multiple fraud data points, 8.2 %) and smaller reply-based classes (Y and Z) that asked users to text “Y”, “YES”, or “STOP”. Each class revealed a different operational intent - whether to capture clicks, phone calls or conversation engagement. On the organisational side, 13 impersonation levels were mapped. The top three were: Banks (Level B) – 39.4 % of attacks Parcel Delivery Companies (Level P) – 26.3 % Government Departments (Level G) – 16.3 % Together, these sectors accounted for over 80 percent of all UK smishing incidents analysed.

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“2LOD” stands for Second Line of Defence, a risk management concept widely used in financial services, government and enterprise. In fraud prevention, 2LOD tools refer to the technologies, analytics and frameworks that provide oversight, assurance, and monitoring over frontline operations. Understanding the Three Lines Model 1st Line: Business units that own and manage risks day-to-day. 2nd Line: Risk and compliance teams that monitor and challenge the first line. 3rd Line: Internal audit that provides independent assurance. 2LOD tools help the middle layer function effectively. They don’t stop fraud directly but ensure that detection, monitoring and governance are robust. Examples of 2LOD anti-fraud tools Fraud Control Models - Intelligence-driven framework for mapping and benchmarking anti-fraud maturity. Fraud Risk Dashboards - Visual analytics showing real-time exposure across departments. Policy Assurance Systems - Tools to verify that fraud procedures are being applied consisten

Authorised Push Payment (APP) fraud has emerged as one of the most damaging forms of financial crime in the UK. Unlike traditional scams, APP fraud relies on deception rather than hacking. Victims are persuaded to transfer money themselves - to a criminal account they believe is safe. How APP fraud works A typical case begins with a convincing impersonation: a phone call from “the bank’s fraud team”, an SMS alert, or even a WhatsApp message appearing to come from a family member. The victim is told their account has been compromised and that they must transfer funds “for protection”. Once the transfer occurs, the funds are often dispersed through a web of mule accounts within minutes. The emotional dimension Fraudsters no longer rely solely on technical skill. They exploit emotion - fear, trust, love, urgency - to manipulate and confuse victims. PORGiESOFT Security’s behavioural analysis shows that victims generally report “feeling pressured by authority” during the scam. Why detection