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Good practice Imported

ScamShield – AI-Powered National Scam Prevention Platform

Singapore · Singapore · See the Singapore profile · See the Singapore profile

Evidence: Descriptive / self-reported Top 9% 96/100 · Ask Evidence Copilot about this practice

Singapore's ScamShield app and 24/7 helpline use an AI classifier to flag scam calls, texts and links; it has blacklisted over 120,000 scam entities since May 2022 and passed 900,000 downloads, part of a national effort that helped cut scam losses nearly 25% in 2025.

913.1 SGD million
National scam losses (2025)
1,100 SGD million
National scam losses (2024)
120,000+
Scam entities blacklisted/blocked (since May 2022)
900,000+
App downloads
ScamShield – AI-Powered National Scam Prevention Platform

Details

Maturity
Established
Promoter
GovTech Singapore (Open Government Products), with the Ministry of Home Affairs, Singapore Police Force & National Crime Prevention Council
Period
2020–present
Keywords
scam prevention, AI/machine learning, public safety, fintech security, government digital services

Context

ScamShield is a national anti-scam platform built by GovTech Singapore's Open Government Products team with the Ministry of Home Affairs, Singapore Police Force and National Crime Prevention Council, combining a 24/7 helpline (2020) with a free mobile app (2022) and an AI classifier flagging scam messages/links.

Results

Singapore Police Force data shows scam losses rose from $651.8 million (2023) to $1.1 billion (2024, 51,501 cases) before falling to $913.1 million in 2025 — the first year in the series both case numbers and losses declined. Since May 2022 the platform has blacklisted 120,000+ scam entities and the app has passed 900,000 downloads.

Conclusions

ScamShield is a detection-and-blocking tool, not a digital-literacy programme, and its effect cannot be cleanly separated from other national measures (bank controls, telecom filtering, campaigns) rolled out alongside it; losses of over $900 million in 2025 show the problem is mitigated, not solved.

Implementation

Implementation detail (cost, timeline, staffing, conditions for success) is not yet available for this practice.

Commonly funded by

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Data sources

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Attachments

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