Monthly Platform Intelligence Note
Last Reviewed: April 2026
Intelligence Summary
Scam.SG indexed 722,821 data nodes and served 22,325 searches in April 2026, with business claim demand concentrated in Computer Programming, Information Technology Consultancy And Related Activities and Wholesale Trade sectors.
Primary Intelligence Metric
Integrated Sources
6Verified data connections
Avg Nodes / Source
120,470Nodes per data provider
All ACRA-registered entities indexed on Scam.SG, including verification status, active warnings, and MAS watchlist flags.
Singapore Operational Context
In April 2026, the SPF reported at least 13 confirmed cases of scammers impersonating police officers on Google Meet video calls, resulting in losses of at least S$32,000. This variant — where fraudsters use SPF branding and official-looking profiles to extract banking credentials — illustrates the continuing evolution of government official impersonation scams, the fastest-growing category in the SPF 2025 Annual Brief (+123.6%). Business identity fraud follows the same impersonation logic at scale: Scam.SG's verification layer makes legitimate entities searchable, scored, and distinguishable from fraudulent imitators.
Search, verification, and scam-reporting volumes recorded on the platform during this period.
Intelligence Trend Observation
Profile searches are growing faster than claim activity this month, suggesting more users are browsing the platform for due diligence without yet acting on what they find.
Top SSIC sectors by number of business profile claim attempts this period.
IT consultancies face persistent verification demand due to digital-only client relationships and project-based billing structures that create exposure to business identity fraud. Singapore's position as a regional technology hub makes its IT service sector a sustained target for impersonation attempts, particularly in client-acquisition scenarios.
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.
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.