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Good practice Imported

AI-Powered Scam-Site Detection — The Pensions Regulator and PSAG's Machine-Learning Tool Against Pension Fraud

United Kingdom · Brighton · See the United Kingdom profile

Evidence: Descriptive / self-reported Top 62% 53/100 · Ask Evidence Copilot about this practice

The UK's Pensions Regulator and Pension Scams Action Group built a machine-learning tool to flag fraudulent pension websites: 830 sites reviewed, 29 high-risk ones taken down, 94 referred to partner agencies, against £17.7m lost to pension scams in 2023.

830 websites
Websites reviewed
29 sites
High-risk sites taken down
94 referrals
Sites referred to partner agencies
17.7 £ million
Money lost to pension scams (2023)
46959 £
Average loss per victim (2023)
11 %
Schemes correctly aware to report scams to Action Fraud
550 industry participants (more than)
Webinar attendees at tool's unveiling (April 2025)
AI-Powered Scam-Site Detection — The Pensions Regulator and PSAG's Machine-Learning Tool Against Pension Fraud

Details

Maturity
Pilot
Promoter
The Pensions Regulator (TPR) and the Pension Scams Action Group (PSAG)
Period
Tool unveiled April 2025; in active use as of mid-2026
Keywords
fraud detection, pension scams, machine learning, financial regulation, consumer protection

Context

The Pensions Regulator (TPR), the UK's pensions watchdog, worked with the multi-agency Pension Scams Action Group (PSAG) to build a machine-learning tool that scans the web for websites impersonating or facilitating fraudulent pension schemes. The context is substantial financial harm: according to Action Fraud, more than £17.7 million was lost to pension scams in 2023, at an average loss of £46,959 per victim, while TPR's own research found that only 11% of pension schemes correctly knew to report suspected scams to Action Fraud despite existing guidance.

Activities

The tool was unveiled at an industry webinar in April 2025 attended by more than 550 pensions-industry participants. A parallel initiative, a new Fraud and Cyber Crime Reporting and Analytics Service, was due to replace Action Fraud later in 2025 to improve national fraud-intelligence sharing with police.

Results

As of the tool's public reporting, PSAG had reviewed 830 websites, had 29 assessed as high-risk taken down, and referred 94 to partner agencies for further action.

Conclusions

Public reporting to date covers detection and takedown activity but not downstream outcomes — there is no published figure yet for money recovered or scams prevented as a direct result of sites the tool flagged, and the 29-of-830 takedown rate reflects an early-stage, low-volume operation rather than a mature, audited enforcement programme.

Implementation
Indicative cost
Low (< €50k) — No budget disclosed; conservative low estimate given the modest, early-stage scale reported (830 sites reviewed).
Time to results
Short (< 1 year)
Staffing & skills
Built collaboratively by The Pensions Regulator (TPR) with the multi-agency Pension Scams Action Group (PSAG)

Conditions for success

  • Multi-agency collaboration between the regulator and partner enforcement bodies to action referrals
  • Public awareness building via industry webinars (500+ attendees)

Common failure modes

  • No published figure yet for money recovered or scams prevented as a direct result of flagged sites
  • Only 11% of pension schemes correctly knew to report suspected scams to Action Fraud despite existing guidance
  • The 29-of-830 takedown rate reflects an early-stage, low-volume operation rather than a mature, audited enforcement programme

Commonly funded by

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Data sources

Where this practice's information was retrieved from, and when.

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