Beyond Incident Counts: A Family-Office Fraud Dashboard That Measures Harm and Recovery

Why fewer reports can be a misleading success

A family office that counts only reported scam attempts may conclude that one group is safer simply because it reports less. The conclusion may fail if incidents are undiscovered, embarrassing to disclose or difficult to classify. It may also overlook a smaller number of events with severe financial and personal consequences. The office needs a dashboard that separates exposure, reporting and harm. Its purpose is to improve support and controls, not to rank family members by supposed vulnerability or turn ordinary financial independence into a surveillance problem.

Read the study’s contrasts and uncertainty

Havers and colleagues analyzed 35,069 respondents in the 2019/20 Crime Survey for England and Wales [1]. Their questions separated any cybercrime from repeated victimization and financial loss. Older respondents reported fewer overall incidents but greater severity in some comparisons. The reported financial-loss odds ratio for people aged 75 and above was statistically significant in the presented model, while the repeat-victimization estimate had a p value of 0.074 and should not be described as conclusive. The data predate the pandemic and current AI-enabled scams. They support examining distinct outcomes, not assigning a fixed risk score to an individual based on age.

Build a small, consent-aware incident record

For each voluntarily reported event, record the date discovered, communication channel, claimed identity, requested action, actual action and whether funds or credentials were exposed. Separate an attempted contact from an authorized transfer made under deception and from a confirmed financial loss. Record what remains unknown. Use only information necessary for response, limit access and avoid copying sensitive account details into a general dashboard. Give the affected person a clear explanation of who can see the record. If another person helps report, preserve the beneficiary’s participation and autonomy wherever possible rather than treating assistance as a transfer of authority.

Measure the response pathway

Track time from discovery to contact with the appropriate bank or service provider, confirmation that relevant accounts are protected, and completion of the agreed response plan. An incident may require specialist legal, financial or technical support; the dashboard should name the responsible person without pretending to supply that expertise. Record repeated contacts after the original event, including recovery scams that exploit a victim’s wish to retrieve money. Distinguish money at risk, confirmed loss and recovered funds, and preserve the dates of each measure. A recovery figure without an exposure denominator or time window can create false reassurance.

Include harm that a balance sheet misses

Ask whether the event changed the person’s willingness to use ordinary services, contact others or participate in family decisions. This should be a voluntary support conversation, not a clinical assessment performed by investment staff. Record only the information needed to arrange help and follow-up. The source study could not examine emotional and physical consequences adequately, so this proposed extension requires careful local evaluation. A family office should not present improved reporting as an increase in crime without considering whether trust in the reporting route has improved. Likewise, fewer reports after a punitive response may indicate silence rather than safety.

Implementation ownership and review

Owner: Fraud response coordinator. Action: Separate attempts, exposure, confirmed loss and repeat contacts in a restricted incident record. Evidence: Time-stamped incident categories and consent-aware access record. Measure: Unclassified events and reporting barriers.

Owner: Bank liaison and security lead. Action: Track containment, provider contact and recurring recovery-scam contact. Evidence: Response timeline, provider confirmations and follow-up plan. Measure: Time to containment and unresolved exposure.

Owner: Family governance liaison. Action: Review support needs and systemic failures without demographic scoring. Evidence: Aggregated review and voluntary support feedback. Measure: Unresolved harm, recurrence and reporting practices that deter disclosure.

Review patterns without stereotyping

At a regular review, examine recurring channels, failed verification steps and barriers to reporting. Aggregate where possible and suppress small-group detail that could identify individuals unnecessarily. Prioritize controls tied to actual failure mechanisms, such as an unreliable callback process, rather than generalized assumptions about age. Stop a reporting practice if it discourages disclosure or exposes sensitive information beyond the response team. This dashboard is a proposed governance tool, not an intervention evaluated by Havers and colleagues. Success should mean timely, respectful response and reduced unresolved harm, with an honest record of what remains uncertain.

Source, attribution and limits

[1] Benjamin Havers; Kartikeya Tripathi; Alexandra Burton; Sally McManus; Claudia Cooper. Cybercrime victimisation among older adults: A probability sample survey in England and Wales. PLOS ONE (2024-12-18). https://doi.org/10.1371/journal.pone.0314380. CC BY 4.0.

Pre-pandemic self-reported survey data may undercapture incidents and do not describe current threats or family offices specifically. Some subgroup estimates are imprecise; emotional and physical consequences could not be examined adequately.

Prepared by the Family Office Private Wealth Journal editorial research desk with AI assistance at the direction of Dr. Freedom Cheteni. Original research authors retain full credit and are not authors or endorsers of this companion. This proposed process has not been evaluated in a new empirical study; no independent peer-review acceptance is claimed. This is educational analysis, not individualized investment, legal or tax advice.

Implementation record

Open the cited sources

1. [1] Benjamin Havers; Kartikeya Tripathi; Alexandra Burton; Sally McManus; Claudia Cooper. Cybercrime victimisation among older adults: A probability sample survey in England and Wales. PLOS ONE (2024-12-18). ↗