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Scam.SG Community Report Bulletin

Q1 2026 Scam-Type Risk Bulletin

Scam report intelligence derived from the Scam.SG community report dataset  ·  January – March 2026

Top threat: Job ScamsQ1 2026 vs Q4 2025 comparisonTop 5 scam types analysed

Segment 1 — Overview

At a glance: Q1 2026 scam landscape

According to Scam.SG community reports, Job Scams (28.6%) topped the Q1 2026 rankings, followed by Investment Scams (27.1%) and Online Shopping Scams (25.7%). This marks a significant shift from Q4 2025, when Online Shopping led. Internet-based channels were the dominant scam delivery source in Q1 2026, overtaking WhatsApp and in-person contacts seen previously.

SourceScam.SG community scam report data, Q1 2026 & Q4 2025

Segment 2 — Scam-Type Volume & QoQ Trend

Quarter-on-quarter comparison: top 5 scam types

Percentages are calculated as a share of the report volume of the top-5 scam types only.

Q1 2026 top-5 reports

70

Jan – Mar 2026

Q4 2025 top-5 reports

52

Oct – Dec 2025

QoQ volume change

+34.6%

Volume of Top-5 Scam Types, Q4→Q1

#1 scam type Q1 2026

Job Scam

28.57% · 20 reports

#Scam typeQ1 2026 countQ1 % of top-5Q4 2025 countQ4 % of top-5Trend
1Job Scam2028.57%
1223.08%
+8 reports
2Investment Scam1927.14%
611.54%
+13 reports
3Online Shopping Scam1825.71%
1936.54%
-1 report
4Supplier Scam811.43%
815.38%
Flat
5Impersonation Scam57.14%
713.46%
-2 reports
Q1 2026 total reports (all reports): 82
Q4 2025 total reports (all reports): 61

SourceScam.SG community scam report data % calculated on top-5 scam types based on report volume only. Money loss rate by report volume is 100% for both quarters

Segment 3 — Scam-Type by Source Profile

How scams reached their victims: The Top 5 Type–Source combinations

Scam sources describe the channel through which a scammer made contact with or reached the victim — e.g. Internet, WhatsApp, In Person, Facebook.

Q4 2025 — Top 5

#Type — SourceCount
1Online Shopping Scam — Internet9
2Supplier Scam — In Person5
2Job Scam — WhatsApp5
2Impersonation Scam — Phone (voice)5
5Online Shopping Scam — Facebook4

Q1 2026 — Top 5

#Type — SourceCount
1Job Scam — Internet15
2Online Shopping Scam — Internet12
3Investment Scam — Social / Forums5
4Supplier Scam — In Person4
5Job Scam — In Person3

Key shift observed

In Q4 2025, scam delivery was fragmented across Internet, WhatsApp, In Person, Phone (voice), and Facebook. By Q1 2026, Internet became the dominant channel — accounting for the top two type–source pairings (Job via Internet: 15; Online Shopping via Internet: 12). WhatsApp dropped out of the top-5 entirely. This consolidation around Internet-based delivery suggests scammers increasingly relied on broad web exposure (job boards, search ads, fake listings) rather than direct messaging to reach victims.

SourceScam.SG community scam report data

Segment 4 — Scam-Type Deep Dive #1

#1 in Q1 2026

Job Scams — why, who, and how

All observations and inferences below are derived from Scam.SG community report data and Scam.SG scam-type definitions. No external data sources are used in this section.

Why Job Scams rank #1 in Q1 2026

Steepest quarter-on-quarter surge

Job Scam reports jumped from 12 (Q4 2025) to 20 (Q1 2026) — a 66.7% increase. No other top-5 scam type showed a comparable absolute rise in report volume within the Scam.SG dataset.

January hiring cycle vulnerability

Q1 (January–March) aligns with the post-Chinese New Year and new-year hiring period in Singapore — a time when more people are actively job-seeking and companies accelerate recruitment to fill up manpower gaps. Scam.SG's definition of Job Scams covers fake employment opportunities to deceive individuals into providing personal information or paying upfront fees for roles that do not exist; this seasonal context creates a fertile environment for volume uplift.

Internet as the primary delivery channel

15 of 20 Job Scam reports in Q1 2026 were sourced via the Internet — the single largest type–source combination in the entire dataset. This means 75% of Job Scam reports in Q1 came through broad web-based channels (job portals, search listings, advertisements) rather than direct messaging platforms.

In-person contact as a secondary vector

3 Job Scam reports in Q1 2026 came via In-Person contact — making it the fifth-largest type–source pairing overall. This dual-channel pattern (Internet + In Person) is distinctive to Job Scams and was not observed for Investment or Online Shopping Scams in Q1.

Observed scam patterns from Scam.SG community reports

Pattern 1 — Scripted recruiter outreach via WhatsApp

Multiple Scam.SG reports describe receiving near-identical unsolicited WhatsApp messages from individuals claiming to represent Singapore-registered employment agencies — citing real UEN numbers to establish credibility. The scripts follow a consistent structure: an introductory greeting referencing a hiring role, a claim to have sourced the recipient's contact through a company database, and a request to forward details to a "Singapore person in charge." Community reporters flagged that the sending numbers were non-Singapore (+502, +56 area codes) despite the local UEN claims, and that follow-up contact either ceased or escalated to fee requests.

Pattern 2 — Task-based commission trap with escalating deposits

A recurring pattern in Scam.SG reports involves victims being onboarded to a proprietary online platform or website and assigned "promotional tasks" — such as rating products, completing brand surveys, or submitting daily check-ins — with promised daily commissions (S$50–S$500) and monthly salaries (up to S$8,750 cited in one report). An initial payout is made to build trust. Subsequently, victims are told their platform wallet has gone negative, or that a deposit is required to unlock the next task set. Deposits escalate with each round. Reports describe funds being transferred to bank accounts that change between transactions, and contact going silent after a threshold is crossed. One reporter described being guided through the process by a named "trainer" who directed them to a specific login URL.

Pattern 3 — Overseas placement with upfront fee extraction

Several Scam.SG reports originate from victims in India, Sri Lanka, and Bangladesh who were approached — often through a manpower consultant or via a family referral — with offers of Singapore-based employment. Victims received official-looking offer letters on company letterheads and were asked to pay fees labelled as MOM processing charges, insurance premiums, or visa costs (amounts ranging from INR 15,000 to INR 60,000 cited across reports). After payment, contact was severed and numbers blocked. In at least one case, a victim was physically directed to travel to a different Indian state for a supposed handover meeting, at which point the scammer disappeared. The Singapore companies named in these reports were either unverifiable, had no traceable presence, or were impersonated entities.

Pattern 4 — IPA submitted without worker knowledge

A distinct cluster of Scam.SG reports — originating primarily from Bangladeshi nationals — describes In-Principle Approvals (IPAs) for Singapore work passes being submitted by construction and engineering companies without the workers' knowledge or consent. Reporters state they did not authorise any company to apply on their behalf, do not recognise the prospective employer, and in some cases object to the salary offered. This pattern suggests a possible intermediary layer — brokers or agents in the origin country — submitting IPA applications using workers' passport details without proper authorisation, potentially as part of a broader deceptive placement scheme.

Pattern 5 — Platform-hopping to evade detection

Scam.SG reports reflect a consistent tactic of moving victims across platforms during the scam lifecycle: initial contact via WhatsApp or Facebook, handoff to Telegram for operational communication, and task completion via a standalone proprietary website or app. Reporters note that Telegram chat histories disappeared after they reported the matter to police, removing evidence. In one case, a reporter described an entirely AI-generated recruiter persona on Telegram that deflected all requests for a phone call and failed to provide a verifiable company address when pressed. The internet-based nature of these handoffs — rather than sustained single-channel communication — is consistent with the Scam.SG data showing Internet as the dominant job scam source in Q1 2026.

SourceScam.SG community report narratives — patterns observed across reports spanning Q4 2024 to Q1 2026. All patterns are inferred from reporter-submitted narratives on scam.sg and do not constitute verified findings or legal determinations.

What consumers should do

  • Search any recruiter or employer name on Scam.SG before responding. Check the company TrustScore and whether any scam reports have been filed against the entity.
  • Never pay any upfront fee for training materials, uniforms, or background checks. Per Scam.SG's Job Scam guidance, legitimate employers do not require payment before you start work.
  • Do not provide NRIC, SingPass, or bank account details to unverified employers encountered through internet job listings — the Scam.SG platform flags personal information harvesting as a primary job scam mechanism. Visit Job Scams — What to look out for to learn more.
  • If a job found via an internet listing asks you to complete "tasks" (e.g. rating products, liking videos) with small initial payouts, treat it as a high-risk task-based scam variant identified on Scam.SG.
  • Report suspicious job offers on Scam.SG to warn the community via the Report a Scam form or Report Suspicious Activity form.

What businesses should do

  • Enrol in the Scam.SG Verification Programme. Scam.SG-verified businesses carry an active Verified Badge, giving job-seekers a visible, accessible signal that the employer is legitimate — directly countering the Internet-based fake listing threat. Visit the Scam.SG Business Directory to learn more.
  • Claim your Scam.SG company profile and maintain up-to-date contact information, so candidates can independently verify you through the Company Directory.
  • Proactively communicate to job applicants that your company will never ask for upfront fees — and provide a verified Scam.SG profile link in job postings as a trust signal.
  • If your company name is being impersonated in fake job listings, report it immediately via the Report a Scam form or the Report Suspicious Activity form and flag to Scam.SG to protect your brand and future applicants.
Scam.SG Verification Programme for Businesses

SourceAll guidance rooted in Scam.SG platform data and scam-type definitions — Scam Types / Job Scams

Segment 5 — Regulatory Context

Key regulatory developments: Q4 2025 – Q1 2026

The following regulatory actions by Singapore authorities provide context for the scam environment reflected in Q4 2025 and Q1 2026 Scam.SG community reports.

Facility Restriction Framework — operationalised 1 October 2025

The Singapore Police Force (SPF), together with the Monetary Authority of Singapore (MAS), the Infocomm Media Development Authority (IMDA), and GovTech Singapore, operationalised the Facility Restriction Framework for scam mules on 1 October 2025. As at 9 February 2026, the framework had resulted in 550 money mules, 801 SIM card mules, and 51 corporate entities being placed under restrictions. Under this framework, scam mules may face restrictions on banking services (including digital banking, ATM services, and card-based transactions), restrictions on subscriptions to new mobile lines, and restrictions on accessing existing Corppass accounts and the use of Singpass to register for high-risk services. Restrictions on Corppass and Singpass are being implemented in a later phase.

SourceSPF 2025 Annual Scams and Cybercrime Brief — SPF Annual Brief (Annual 2025)

Targeted public advisories

In July 2025, SPF collaborated with the Ministry of Finance to disseminate anti-scam advisories warning the public about fake SG60 voucher advertisements on social media and phishing websites. In a separate initiative, SPF partnered with Ticketmaster to alert the public about concert ticket scams linked to BLACKPINK's Deadline World Tour Concert in November 2025. These targeted, event-specific advisories demonstrate a shift toward proactive, context-sensitive scam prevention aligned with specific high-risk consumer moments.

SourceSPF Publications — SPF Police Advisory On Phishing Scams & SPF Police Advisory On Scams Involving The Sale Of Concert Tickets

Relevance to Scam.SG Q1 2026 report data

The Facility Restriction Framework's focus on money mule infrastructure is directly relevant to the continued presence of Job Scams at #1 in Q1 2026. Scam.SG's Job Scam type definition notes that some victims are unknowingly drawn into facilitating criminal activity — a mechanism consistent with money mule recruitment. The sustained volume of Job Scam reports in the Scam.SG dataset across both Q4 2025 and Q1 2026 suggests that mule recruitment operations continued to target Singapore residents even as regulatory enforcement ramped up.

The sharp rise of Internet as a scam source in Q1 2026 (displacing WhatsApp) may also partly reflect scammer adaptation — moving activity to less-regulated web channels as mobile-line restrictions (SIM card mule controls, IMDA barring measures) increased friction on phone-based approaches.

NoteRegulatory information sourced from SPF. Observations linking regulatory context to Scam.SG report data are editorial inferences by Scam.SG and do not constitute SPF or government determinations.

Segment 6 — Methodology

Data period, definitions & exclusions

Data Period

Q1 2026: 1 January 2026 – 31 March 2026
Q4 2025: 1 October 2025 – 31 December 2025
Reports reflect community submissions received and logged on the Scam.SG platform within each respective quarter.

Data Source

Scam.SG community scam report dataset, operated by OnScam (SG) Pte. Ltd., an appointed agent of Data Bureau (Singapore). Reports are user-submitted via the Scam Report Form.

Scam-Type Definitions

Scam-type classifications follow Scam.SG's own taxonomy as published on the Scam Types Directory. Definitions used in this bulletin:
  • Job Scam: Fraudsters offering fake employment opportunities to deceive individuals into providing personal information or paying upfront fees for roles that do not exist.
  • Investment Scam: Scammers luring people in through fraudulent schemes that promise high returns and quick wealth, only to result in financial loss.
  • Online Shopping Scam: Fraudulent schemes designed to deceive consumers during the purchasing process, exploiting trust in e-commerce platforms for financial gain.
  • Supplier Scam: Fraudsters create convincing fake supplier websites or impersonate established vendors to intercept orders or redirect payments to fraudulent accounts.
  • Impersonation Scam: Criminals pose as police officers, government agencies, bank staff, or even friends to create fear or urgency. By exploiting trust in authority, they manipulate victims into transferring money or providing sensitive personal information before the deception is discovered.

Scam Source Definition

"Scam source" refers to the channel through which the scammer made contact with or reached the victim. Sources in this bulletin include: Internet (web-based platforms, online listings), Social Networking / Online Forums, WhatsApp, Facebook, Phone (voice), and In Person. Source classifications are as recorded in Scam.SG community reports.

Percentage Calculation

All percentage shares are calculated as a proportion of the top-5 scam types by report count within the respective quarter — not as a proportion of all scam types or all reports on the platform. This is disclosed in all tables and charts.

Loss Rate

Both Q1 2026 and Q4 2025 show a 100% loss rate across the top-5 scam types (from scam.sg community report dataset), meaning all reported incidents within the top-5 involved a financial loss to the victim as recorded on the Scam.SG platform.

Exclusions

  • Scam types outside the top 5 for each quarter are excluded from percentage calculations and trend analysis.
  • Reports submitted outside the defined data periods are excluded.
  • This bulletin does not incorporate SPF official statistics, MAS data, or any government enforcement records for the purposes of scam-type volume analysis. Regulatory context (Segment 5) is presented separately and sourced independently.
  • TrustScore assessments and company-level data from Scam.SG are not used in the construction of the scam-type report counts in this bulletin.

Terminology

Platform terminology follows definitions found at the Terminology Page. TrustScore is a proprietary Scam.SG data-aggregation metric and not a regulatory determination.
Disclaimer: This bulletin is produced independently by Scam.SG, operated by OnScam (SG) Pte. Ltd., an appointed agent of Data Bureau (Singapore). It does not constitute legal advice or a regulatory determination.
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About Scam.SG

Scam.SG is the largest Singapore business company review and authenticity platform that provides business scam analysis and aggregate business authenticity to help consumers and/or business associates reduce the risk of falling into a scam. Our analysis uses proprietary algorithms to assess and score Singapore business entities based on publicly available data signals. Visit scam.sg/terminology for definitions of all platform terms.

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Scam.SG is operated by OnScam (SG) Pte. Ltd. We are not affiliated with, endorsed by, or sponsored by any government agency or department. The information provided on Scam.SG (the “Website”) is sourced from publicly available data, including but not limited to ACRA (Accounting and Corporate Regulatory Authority) data from data.gov.sg and other publicly accessible sources. Whilst we strive to ensure the accuracy and reliability of the data presented, we cannot guarantee its completeness or timeliness. Read more at our disclaimer page.


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