Building Trust and Safety in Online Dating: How Verified Profiles Beat Scams

June 30, 2025, marked a tipping point for dating apps. On that day the major platform Tinder made its new Face Check feature mandatory for every new user in California (see Axios). The brief selfie video that powers Face Check is designed to confirm that the person behind a profile photo is real, unique, and not hiding behind a duplicate account. Early feedback from pilot markets in Colombia and Canada showed a visible fall in fake-profile reports, so the company extended the test to one of its largest U.S. regions.

According to the FBI’s 2024 Internet Crime Report, Americans filed more than 859,000 internet-crime complaints last year with losses exceeding 16 billion dollars. People over sixty absorbed nearly five billion dollars of that damage. While the report groups many fraud types together, trust-and-safety leaders in dating know romance scams are among the most emotionally and financially devastating slices of the total. The message is clear: platforms that cannot prove authenticity risk losing users, revenue, and brand equity at once.

Why fake profiles survive traditional moderation

For years most dating services relied on a combination of manual review and retrospective takedowns. Yet fake profiles continue to slip through because five structural obstacles make them hard to catch early:

• Low-friction onboarding lets bad actors cycle through new email addresses and phone numbers in minutes.
• Cross-platform image reuse hides an offender’s reputation from any single app.
• AI generators create photorealistic faces that defeat basic reverse-image searches.
• Fragmented data sharing means a scammer banned on one site starts over elsewhere.
• Verification flows are often seen as conversion killers, tempting product teams to keep them optional.

Together these barriers explain why dating platforms face recurring trust-and-safety challenges, why user retention suffers when fake profiles multiply, and why an industry built on intimacy is experiencing a credibility gap.

Turning verification into a growth lever

The good news is that verification no longer needs to feel like a tax on growth. In March 2025 the well-known dating service Bumble launched a government-ID badge across eleven markets (see TechCrunch). Users can filter exclusively for verified matches, and early tests show stronger engagement among those who opt in. The pattern mirrors what Face Check is doing elsewhere: turning a safety feature into a visible trust signal that differentiates premium experiences.

Technology plays a critical role here. Automated image forensics now make it feasible to screen every profile photo in seconds rather than hours. The Vaarhaft Fraud Scanner for example integrates into an onboarding flow through a simple API call. The service detects AI-generated faces, image manipulation, embedded content like phone numbers or urls, and cross-platform duplicates while returning an explanatory heat map that highlights altered pixels. When a picture looks suspicious, the platform can trigger Vaarhaft SafeCam to capture a fresh live image through a secure web link sent to the user. The extra step applies only to the fraction of profiles that fail the automated check, which minimizes friction for legitimate customers while blocking bots and romance-scam farms at scale.

Dating teams that deploy verified media consistently report three commercial benefits: higher swipe-to-match ratios because users trust what they see, lower content-moderation overhead because fake accounts never go live, and stronger retention because members feel safer investing time in conversations that might lead to real-world meetings.

What comes next for platforms that prioritize authenticity

The next twelve months will decide whether mandatory verification pilots stay localized or go global. User feedback so far suggests the upside outweighs the friction, especially for demographics that have lost money or confidence to past scams. At the same time regulators are paying closer attention to biometric-data retention and transparency. Developers should therefore choose tools that prove compliance; Fraud Scanner’s fully European hosting and automatic deletion of media after analysis is one example.

Online dating will never be immune to fraud, but it is entirely possible to make scams the rare exception rather than an everyday risk. For a deeper dive into photo-forensics methods that expose AI-generated faces, read our article on detecting AI-generated profile pictures in online dating. Complementary insights on how the emerging C2PA standard can authenticate visual content are available here.

If your roadmap calls for safer sign-ups, fewer support escalations, and higher-quality matches, get in touch. A short demo of Fraud Scanner and SafeCam will show how quickly verified media can lift trust and revenue together.