Identity Verification for E-Commerce Platforms & Marketplaces

Basic age gates with age-confirmation checkboxes are considered insufficient in regulated industries. You can build a user-friendly age verification system by using document verification, which extracts key personal details, including the user’s date of birth. This is often combined with liveness detection and face matching to compare the submitted photo ID or video with the user’s live facial biometrics, ensuring access is granted only to age-appropriate users.

Since each country has unique laws, regulations, and data availability, choosing a KYC vendor with a wide document base is important. This helps your marketplace accept different types of ID documents from around the world, onboarding more genuine customers while scaling your business and complying with regulatory requirements. At iDenfy, we support 3000+ ID documents from 200 countries and territories.

Merchant onboarding is the process of verifying a merchant’s identity to ensure they are legitimate and meet the requirements to operate on an e-commerce platform. This involves collecting business information, including the address, tax ID number, legal name, and banking details, as well as other personal data. This measure also helps confirm that the merchant isn’t involved in money laundering and other fraudulent activities before they begin accepting payments on the marketplace.

Yes, you can use automation to streamline the whole Know Your Business (KYB) or business/merchant onboarding process, including using automation tools, like risk assessment, to identify and address potential risks linked to new merchants in real-time. This also helps e-commerce platforms to maintain ongoing compliance and access risk scores of another corporate client in seconds instead of assessing multiple data points manually, which involves asking merchants to send documents and manually verifying them, which often takes weeks and lacks accuracy.

To not get fined for every chargeback received, marketplaces can minimize chargebacks by adding more stringent AI-powered fraud prevention measures, including identity verification. For example, most automated fraud prevention tools use machine learning algorithms to analyze user behavior, transaction data, and other suspicious activity red flags, stopping fraudulent transactions before they even result in chargebacks.