Monthly Platform Intelligence Note
Last Reviewed: May 2026
Intelligence Summary
Scam.SG indexed 866,474 data nodes and served 23,479 searches in May 2026, with business claim demand concentrated in Wholesale Trade and Education sectors.
Primary Intelligence Metric
Integrated Sources
6Verified data connections
Avg Nodes / Source
144,412Nodes per data provider
All ACRA-registered entities indexed on Scam.SG, including verification status, active warnings, and MAS watchlist flags.
Singapore Operational Context
In May 2026, the Singapore Police Force hosted the Anti-Scam Conference 2026 — themed "United Against Scams" — bringing together representatives from over 20 countries to coordinate cross-border enforcement and intelligence sharing. The SPF also announced the establishment of a new Cyber Command in the second half of 2026, unifying counter-scam operations, investigations, and intelligence capabilities under a single structure. Scam.SG's business verification platform directly supports Singapore's national objective of reducing the information asymmetry that enables fraud actors to impersonate legitimate ACRA-registered entities.
Search, verification, and scam-reporting volumes recorded on the platform during this period.
Intelligence Trend Observation
Active warning records are accumulating faster than claim activity, suggesting the platform's risk intelligence coverage is outpacing the rate at which legitimate businesses are coming forward to verify themselves.
Top SSIC sectors by number of business profile claim attempts this period.
Wholesale distributors operate in high-value B2B supply chains where counterparty verification is commercially critical. Claim activity in this sector reflects suppliers and buyers conducting pre-transaction due diligence — a pattern consistent with the large order sizes and credit exposure typical of wholesale relationships.
Education providers — including tuition centres, enrichment schools, and private institutions — face growing impersonation risk as parents seek to verify credentials before enrolment. The sector's high consumer-trust dependency makes verification signals commercially valuable for legitimate operators.
Data Sources & Methodology
Scam.SG currently draws on integrated data sources covering ACRA-registered business entities, MAS regulatory and investor alert tables, community-sourced scam reports, and enforcement signals from public agencies. For a full list of data sources, visit scam.sg/data-sources.
Disclaimer: The data in this publication is presented for informational and transparency purposes only. It does not constitute legal advice, regulatory assessment, or a recommendation regarding any business entity named or described herein. Scam.SG is operated by OnScam (SG) Pte. Ltd. and is not affiliated with any Singapore government agency.