section stringclasses 7
values | item stringlengths 4 29 | reports stringlengths 4 6 ⌀ | reported_loss_aud float64 69.9M 3.15B ⌀ | note stringlengths 5 66 ⌀ | source_url stringclasses 5
values |
|---|---|---|---|---|---|
year | 2021 | null | 1,760,000,000 | source mix differs before 2023; ACCC 2021 report: nearly A$1.8B | https://www.scamwatch.gov.au/system/files/Targeting%20scams%20-%20report%20of%20the%20ACCC%20on%20scams%20activity%202021.pdf |
year | 2022 | null | 3,150,000,000 | source mix differs before 2023; ACCC 2022 report: just over A$3.1B | https://www.accc.gov.au/system/files/Targeting%20scams%202022.pdf |
year | 2023 | null | 2,741,000,000 | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2023.pdf |
year | 2024 | null | 2,030,000,000 | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2024.pdf |
year | 2025 | null | 2,180,000,000 | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
source 2025 | Scamwatch | 200675 | 334,800,000 | before removing duplicates | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
source 2025 | ReportCyber | 58876 | 774,200,000 | before removing duplicates | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
source 2025 | AFCX | 202943 | 842,300,000 | before removing duplicates | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
source 2025 | ASIC | 1565 | 135,000,000 | before removing duplicates | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
source 2025 | IDCARE | 47589 | 535,800,000 | before removing duplicates | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
combined 2025 | after removing duplicates | 481523 | 2,180,000,000 | 274577 reports with a loss | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
scam type 2025 | Investment | null | 837,700,000 | -11.4% | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
scam type 2025 | Payment redirection | null | 166,800,000 | +9.3% | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
scam type 2025 | Romance | null | 139,900,000 | -10.8% | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
scam type 2025 | Phishing | null | 97,600,000 | +15.5% | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
scam type 2025 | Remote access | null | 69,900,000 | -34.1% | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
payment method 2025 (Scamwatch) | Cryptocurrency | 3993 | 121,300,000 | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
payment method 2025 (Scamwatch) | Bank transfer | 8858 | 118,100,000 | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
older Australians 2025 | 65+ share of Scamwatch losses | null | null | 26.5% of losses vs about 17.1% of population | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
disruption 2025 | Scam websites referred | 8400+ | null | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
disruption 2025 | Scam websites removed | 7500+ | null | report cites a 30% increase; NASC estimates A$89.4M avoided loss | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
disruption 2025 | Phone numbers referred | 4246 | null | null | https://www.nasc.gov.au/system/files/targeting-scams-report-2025.pdf |
Scam & Fraud Statistics: US, UK, Canada, Australia, India (2020-2025)
Fifteen small tables of scam, fraud and data-breach statistics, each compiled from official published sources (FBI IC3, FTC, UK Finance, Canadian Anti-Fraud Centre, Australian National Anti-Scam Centre and Scamwatch, India's NCRP, NCRB, RBI and the 1930 helpline, and Have I Been Pwned). Most files include a source_url column linking each figure to the original publication.
Each CSV is its own config, because the files have different columns. Load one with:
from datasets import load_dataset
ds = load_dataset("ScanMyShadow/scam-fraud-statistics", "fbi-ic3-2025-report-in-numbers")
Files
| Dataset (full analysis) | File | Rows | What it contains |
|---|---|---|---|
| Australia Scam Reports & Losses 2021-2025 | australia-scams-2025-national-anti-scam-centre-data.csv |
22 | Australian scam reports and reported losses from the National Anti-Scam Centre (Scamwatch and partner data), by section and item. |
| Average Loss per Scam Victim by Type, 2025 | average-loss-per-victim-by-scam-type-2025-data.csv |
26 | Average reported loss per victim by scam type for the US, Canada, UK and Australia in 2025, with computed averages. |
| Canada CAFC Fraud Reports & Losses 2021-2025 | canada-fraud-2025-cafc-losses-and-top-scams.csv |
25 | Canadian Anti-Fraud Centre yearly losses 2021-2025 and 2025 top scams ranked by losses and by reports. |
| FBI IC3 Internet Crime Report 2025 Figures | fbi-ic3-2025-report-in-numbers.csv |
24 | FBI IC3 yearly complaints and losses 2021-2025 plus 2025 crime-type, age-group, crypto and Kill Chain figures. |
| HIBP Breaches Over 31M Accounts, 2024-2026 | have-i-been-pwned-breaches-2024-2026-data.csv |
20 | Twenty Have I Been Pwned breaches over 31 million accounts dated 2024-2026, with a type label. |
| How Scams Start: Contact Methods, 2025 | how-scams-start-contact-methods-2025-data.csv |
35 | Scam contact methods and losses from UK Finance, Australia Scamwatch and the FTC, with computed averages. |
| India 1930 Helpline Savings and UPI Fraud Data | india-1930-helpline-money-saved-and-upi-fraud-data.csv |
11 | India 1930 helpline cumulative amount saved and UPI fraud incidents and amounts, as published by Indian government sources. |
| India NCRP Cyber Fraud Complaints 2021-2025 | india-cyber-fraud-2021-2025-ncrp-complaints-losses.csv |
21 | India NCRP complaints and reported losses 2021-2025 with NCRB cyber crime cases by year and by state. |
| Investment Fraud Losses: US, UK, CA, AU, 2025 | investment-fraud-losses-us-uk-canada-australia-2025.csv |
5 | Investment fraud losses in 2025 across the US, UK, Canada and Australia with shares and year-on-year change. |
| RBI Bank Fraud Data by Category, 2020-2025 | rbi-bank-fraud-data-2020-21-to-2024-25-by-category.csv |
17 | RBI bank frauds of ₹1 lakh and above: yearly totals 2020-21 to 2024-25 and 2024-25 breakdown by category. |
| Scam Losses 2021-2025: US, UK, Canada, AU | scam-losses-2021-2025-trend-us-uk-canada-australia.csv |
20 | Yearly reported fraud and scam losses 2021-2025 for the US, UK, Canada and Australia, with a 2021-based index. |
| Scam Losses by Age Group, US & Australia 2025 | scam-losses-by-age-group-us-australia-2025-data.csv |
29 | Scam complaints and losses by age group for the US (FBI, FTC) and Australia (Scamwatch). |
| Scam Losses 2025: US, UK, Canada, Australia | scam-losses-us-uk-canada-australia-2025-data.csv |
5 | 2025 reported fraud and scam losses for the US, UK, Canada and Australia with per-resident figures. |
| Scam Payment Methods & Crypto Kiosks, 2025 | scam-payment-methods-crypto-kiosk-2025-data.csv |
21 | Scam payment methods, cryptocurrency and crypto kiosk figures for Australia (Scamwatch) and the US (FBI IC3), 2025. |
| UK Finance Fraud Figures 2025 | uk-fraud-2025-uk-finance-app-scam-numbers.csv |
11 | UK Finance 2025 fraud totals, APP scam types and reimbursement, plus survey and police fraud figures. |
Notes on use
- Figures are as published by each source and are not harmonised across countries: reporting rules, currencies and definitions differ. Columns named
*_computedare derived by us from published numbers. - Blank cells mean the source did not publish that figure. Some number columns hold text values where a source gave a range or a qualifier.
- Indian figures use lakh and crore (1 lakh = 100,000; 1 crore = 10,000,000).
- In
scam-losses-2021-2025-trend-us-uk-canada-australia, the Australia 2021-2022 values come from a different source mix than later years. have-i-been-pwned-breaches-2024-2026-data: breach data via Have I Been Pwned, licensed under CC BY 4.0.- This is statistical reporting only. It contains no personal data.
Licence and citation
Licensed under CC BY 4.0. Please credit "Scan My Shadow (scanmyshadow.com)" and link to the relevant analysis page above.
Scan My Shadow. Scam & Fraud Statistics: US, UK, Canada, Australia, India (2020-2025). Hugging Face, 2026. https://huggingface.co/datasets/ScanMyShadow/scam-fraud-statistics
Archived on Zenodo (cite all versions): 10.5281/zenodo.23602117
Maintained by Scan My Shadow. Also on Kaggle: https://www.kaggle.com/scanmyshadow
- Downloads last month
- 63