Fraud prevention needs safeguards beyond individual awareness

Fraud prevention places a demanding requirement on every potential victim: recognize an attack while dealing with everything else in life. OXIL argues that individual awareness carries too much of this responsibility. Its research reports that 89% of people have received what they believe was a scam attempt. For fraud leaders, the practical question is what protections remain when a person does not recognize the threat.

A person can understand scam techniques and still face circumstances that make judgment harder at a particular moment, according to OXIL’s research. That changes the design problem. Prevention has to account for periods of vulnerability and what institutions can do before, during, and after an attack. OXIL calls this broader model “safeguarding”: using institutions, professionals, controls, and support around a person to reduce fraud risk.

Fraud prevention places a heavy burden on individuals

Conventional prevention combines awareness with technical interception. People receive anti-phishing training and advice about suspicious contact, while fraud systems identify malicious messages, transactions, or infrastructure. OXIL argues that this approach is incomplete when protection depends heavily on a person applying that knowledge at the point of attack. OXIL is advocating adoption of safeguarding, so its characterization of the existing model should be read in that context.

OXIL’s Research team, with support from Google.organization, has proposed safeguarding as a broader framework for scam prevention. Its research includes analysis of 28.6 million domain-name-based scam and fraud signals made available through the Global Signal Exchange. OXIL uses this work to support a model that places more responsibility on organizations surrounding people who encounter scams. The proposal extends fraud controls beyond education and interception to intervention, reporting, support, and recovery.

OXIL argues that a person’s capacity to recognize a scam can change with their circumstances. The design implication is direct. Organizations following this model would treat individual vigilance as one control among several, with others available when a person has difficulty recognizing or responding to an attack.

Vulnerability changes with circumstances

Some barriers to fraud education can be persistent. OXIL argues that people with linguistic or cognitive disabilities may struggle to engage with training. Accessibility therefore matters to system design because people differ in their ability to consume, understand, retain, or apply educational material. OXIL’s reported targeting figures include three groups:

OXIL also reports circumstances that may affect people more broadly. Its research gives three figures for financial worries, loneliness, and bereavement:

OXIL says tiredness, financial pressure, and a hectic work-life balance are among the most common factors making scams harder to spot. It uses these examples to argue that vulnerability can change over time. Someone who ordinarily recognizes suspicious contact may face different conditions during grief, financial stress, exhaustion, or periods of competing demands. Under this model, fraud controls need to accommodate changes in a person’s circumstances.

This distinction changes how organizations can think about vulnerable populations. A fixed classification identifies people who meet predetermined criteria. OXIL proposes safeguarding for all adults because its model treats vulnerability as something that can arise with circumstances. The approach focuses attention on the conditions affecting a person when a scam reaches them.

Awareness remains one preventive control. OXIL’s findings give fraud leaders a reason to examine what happens when someone has difficulty applying that awareness during a specific encounter. The design question is what institutional controls operate once an attack reaches the individual.

Fraud controls need to span the incident lifecycle

OXIL describes the technology community’s focus as intercepting a message. Interception can remove a malicious message before the recipient has to judge it. OXIL’s safeguarding proposal extends the operating model across three stages: before, during, and after an incident. Each stage creates a different task for the institutions involved.

Before an incident, organizations can detect signals, share intelligence, educate customers, and block known threats. During an incident, OXIL’s model calls for institutions or trusted intermediaries to recognize possible manipulation and intervene. After an incident, the work shifts to reporting, support, investigation, and recovery. This lifecycle lets organizations assign controls beyond the initial attempt to stop a scam.

OXIL reports that among people who reported a scam, 41% felt nothing changed and 35% felt they had to solve everything themselves. These figures concern people who had already reported an incident, making them relevant to OXIL’s case for stronger post-incident support. OXIL also says its research found that many victims blame themselves or feel embarrassed, which can keep them silent and make recovery harder. These findings support OXIL’s focus on what institutions do after fraud occurs.

The language used after an incident is also part of OXIL’s argument. It characterizes banks as using “before” solutions for “after” problems when customers call after being defrauded. Banks are among the organizations whose practices OXIL wants its safeguarding framework to change, so this remains OXIL’s characterization of current practice. For banks, police, public bodies, and other organizations, the operational question is whether post-incident processes help an affected person report the event and pursue available support.

Safeguarding distributes responsibility across institutions

OXIL proposes roles for support workers, police, healthcare professionals, public bodies, banks, and other intermediaries that may identify risk or help someone respond. Under this model, education also reaches people and institutions in a position to intervene. The aim is a wider network able to act before, during, or after fraud. This is the shift in responsibility OXIL is advocating.

Information sharing is central to that proposal. OXIL points to the Global Signal Exchange as a platform through which scam-related information can be shared. This proposal reflects OXIL’s preferred operating model and its interest in broader adoption. For executives, it raises a concrete governance question: which organizations can receive relevant fraud information, and what actions are they authorized to take with it?

OXIL also argues that safeguarding should apply to all adults. Its reasoning follows from its view that vulnerability can emerge with bereavement, financial stress, exhaustion, disability, or other circumstances. Under that approach, controls respond to a person’s situation instead of depending on membership in a fixed category. Safeguarding then becomes an operating principle for detection, intervention, case handling, reporting, and recovery.

For technology and risk leaders, this creates a specific control-design question: what happens after an attack reaches someone struggling to assess or respond to it? Organizations can examine customer support, case handling, reporting routes, information sharing, and recovery processes. OXIL’s proposal places these functions inside the fraud-control model alongside education and technical interception.

Key takeaways for leaders

• Reduce reliance on individual vigilance: Fraud prevention should treat awareness as one control among several. Leaders should build protections that still work when customers cannot recognize or respond effectively to a scam.
• Design for changing vulnerability: Bereavement, financial pressure, exhaustion, disability, and other circumstances can affect a person’s ability to spot fraud. Controls should respond to changing conditions rather than rely only on fixed definitions of vulnerable groups.
• Cover the full fraud lifecycle: Prevention should extend beyond intercepting malicious messages. Leaders should assess controls before, during, and after incidents, including intervention, reporting, case handling, support, and recovery.
• Distribute responsibility across institutions: OXIL’s safeguarding model gives banks, public bodies, police, healthcare professionals, and other intermediaries a larger role in fraud prevention. Leaders should clarify how relevant fraud intelligence is shared and who is authorized to intervene or provide support.