Cross-border e-commerce is growing, representing 31% of all global online sales. According to Capital One, U.S. buyers and Chinese merchants dominate this market: 

• 32% of American consumers have purchased from a foreign online retailer in the last year
• 43% of Chinese B2B merchants target the U.S., more than any other country

As cross-border e-commerce increases, online marketplaces need an efficient and accurate way to analyze Chinese merchants’ legitimacy. Existing tools lack context-specific international data coverage, so many marketplaces end up turning away quality Chinese merchants and artificially cap their revenue potential.

Our latest CorShield update addresses this gap. CorShield is now the first fraud model to automatically predict a Chinese merchant’s likelihood of identity fraud at onboarding.

Read on to learn more, and reach out to get started today.

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Existing merchant onboarding is error-prone and lacks localization

When online marketplaces onboard Chinese sellers, they typically rely on manual processes to assess merchant legitimacy. For example, a risk analyst might conduct online research for additional merchant data, or reach out to merchants individually for additional documentation. 

Besides creating additional friction, these processes can also generate inaccuracies. Merchant documentation is China-specific, but risk teams often lack sufficient data on Chinese sellers and context on the local market in order to evaluate these data points correctly. 

For example, many U.S.-based marketplaces use merchant email metadata to verify a business’s legitimacy, but email addresses are not as commonly used in China. Phone number metadata is a much more valuable signal.

Even when risk teams receive the right kind of merchant documentation, they may not have the right database to use as a benchmark for evaluation. Data on Chinese merchants is not easily available on U.S.-based search engines like Google.

These blindspots create significant potential for human error and can lead many online marketplaces to decline legitimate, high quality Chinese merchants. This ultimately limits the variety of sellers for the buyers in their marketplace, resulting in lower gross merchandise value (GMV) and reduced appeal of the platform.

As we’ve worked with more online marketplaces, we asked ourselves: is there a way to automate Chinese merchant verification that improves fraud detection while enhancing approval rates?

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Automated, context-specific merchant fraud model 

With CorShield, online marketplaces can automatically predict a Chinese merchant’s legitimacy at onboarding. By reducing the potential for human error, CorShield empowers risk teams to onboard more legitimate merchants and maximize revenue.

How does it work?

1. Merchant submits onboarding application. This often includes phone number, name of business, email address, and relevant business owner information. CorShield will also independently detect behavioral data such as applicant IP address.
2. CorShield cross-checks application information. CorShield uses proprietary datasets to triangulate known information on the merchant, and check this against applicant information. This identifies the most meaningful cases of third-party and first-party merchant fraud. 
3. CorShield generates a fraud score and top reasons. For each merchant, CorShield will return a score 0 to 100 and 3 reasons for the score. This information allows risk teams to make onboarding decisions quickly, and follow up with merchants accurately.

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Want to learn more?

This is just the latest improvement to our CorShield fraud model. We’re excited to roll out additional functionality soon.

Reach out if you’d like to learn more, or if you have a merchant fraud use case you’d like us to tackle.

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