⚡ Fraud Prevention Software in Hong Kong
Fraud prevention software is designed to detect, prevent, and mitigate fraudulent activities during digital transactions and user interactions, particularly in e-commerce, payments, advertising, and account access.
Hong Kong is an East Asian special administrative region of China with a population of around 7.5 million people.
According to our research, fraud prevention software is detected on 0.4% of websites from Hong Kong.
⭐ Most Popular in 2026
The following chart shows the top fraud prevention software in Hong Kong in 2026, based on market share.
The most popular is Visa Protect with an impressive share of 32.9%, followed by
Arcot with 18.3% and
Authorize.net with 12.2%.
Visa Protect 32.9%
Arcot 18.3%
Authorize.net 12.2%Human 11%
AppsFlyer 9.8%
ClickCease 8.5%
NoFraud 7.3%
Signifyd 6.1%
ThreatMetrix 4.9%
Riskified 4.9%
Confiant 3.7%
DoubleVerify 3.7%
TruValidate 3.7%Forter 3.7%
- Sift 2.4%
🚀 Highlights
Here is a list of the top solutions that is more popular in Hong Kong than worldwide.
Differences between global and country rankings are shown in parentheses.
- 2.
Arcot (-1)
- 4.
Human (-6)
- 7.
NoFraud (-5)
- 9.
ThreatMetrix (-2)
- 10.
Riskified (-5)
- 12.
DoubleVerify (-1)
- 14.
Forter (-2)
- 15. Sift (-17)
- 16.
Arkose Labs (-10)
- 17.
TrafficGuard (-17)
✨ Best Fraud Prevention Software
Below is a more detailed list of the top 25 of the 27 fraud prevention software solutions used on sites from Hong Kong, ranked by their market share.
🗃️ About This Data
- We evaluate the popularity of technologies based on the number of websites where we detect their usage.
- Technologies without a detectable web footprint, and those we do not track, are not reflected in the calculated market share.
- This report is based on the analysis of 18,312 websites from Hong Kong.
- We currently track the presence of 42 fraud prevention software solutions across the web.
- Of these, 27 were detected on websites from Hong Kong.
- Statistics were last calculated on .
- For more details, see our methodology and disclaimer.
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